docs update

docs/build/html/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 0404ad38f8b7b0d4bcdda401dd97c652
+config: 130317d5cc5607ddb0ed4187804765bc
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/build/html/_sources/dev/extensions.rst

@@ -1,24 +1,16 @@
 Developer Documentation
 =======================
 
-MLX provides a open and flexible backend to which users may add operations 
-and specialized implementations without much hassle. While the library supplies
-efficient operations that can be used and composed for any number of 
-applications, there may arise cases where new functionalities or highly 
-optimized implementations are needed. For such cases, you may design and 
-implement your own operations that link to and build on top of :mod:`mlx.core`.
-We will introduce the inner-workings of MLX and go over a simple example to 
-learn the steps involved in adding new operations to MLX with your own CPU 
-and GPU implementations. 
+You can extend MLX with custom operations on the CPU or GPU. This guide
+explains how to do that with a simple example.
 
 Introducing the Example
 -----------------------
 
-Let's say that you would like an operation that takes in two arrays, 
-``x`` and ``y``, scales them both by some coefficients ``alpha`` and ``beta``
-respectively, and then adds them together to get the result 
-``z = alpha * x + beta * y``. Well, you can very easily do that by just 
-writing out a function as follows:
+Let's say you would like an operation that takes in two arrays, ``x`` and
+``y``, scales them both by coefficients ``alpha`` and ``beta`` respectively,
+and then adds them together to get the result ``z = alpha * x + beta * y``.
+You can do that in MLX directly:
 
 .. code-block:: python
 
@@ -27,44 +19,35 @@ writing out a function as follows:
     def simple_axpby(x: mx.array, y: mx.array, alpha: float, beta: float) -> mx.array:
         return alpha * x + beta * y
 
-This function performs that operation while leaving the implementations and 
-differentiation to MLX. 
+This function performs that operation while leaving the implementation and
+function transformations to MLX.
 
-However, you work with vector math libraries often and realize that the 
-``axpby`` routine defines the same operation ``Y = (alpha * X) + (beta * Y)``. 
-You would really like the part of your applications that does this operation 
-on the CPU to be very fast - so you decide that you want it to rely on the 
-``axpby`` routine provided by the Accelerate_ framework. Continuing to impose 
-our assumptions on to you, let's also assume that you want to learn how to add 
-your own implementation for the gradients of your new operation while going 
-over the ins-and-outs of the MLX framework. 
+However you may need to customize the underlying implementation, perhaps to
+make it faster or for custom differentiation. In this tutorial we will go
+through adding custom extensions. It will cover:
 
-Well, what a coincidence! You are in the right place. Over the course of this 
-example, we will learn:
-
-* The structure of the MLX library from the frontend API to the backend implementations.
-* How to implement your own CPU backend that redirects to Accelerate_ when appropriate (and a fallback if needed).
-* How to implement your own GPU implementation using metal.
-* How to add your own ``vjp`` and ``jvp``.
-* How to build your implementations, link them to MLX, and bind them to python.
+* The structure of the MLX library.
+* Implementing a CPU operation that redirects to Accelerate_ when appropriate.
+* Implementing a GPU operation using metal.
+* Adding the ``vjp`` and ``jvp`` function transformation.
+* Building a custom extension and binding it to python.
 
 Operations and Primitives
 -------------------------
 
-In one sentence, operations in MLX build the computation graph, and primitives 
-provide the rules for evaluation and transformations of said graph. Let's start 
-by discussing operations in more detail. 
+Operations in MLX build the computation graph. Primitives provide the rules for
+evaluating and transforming the graph. Let's start by discussing operations in
+more detail.
 
 Operations
 ^^^^^^^^^^^
 
-Operations are the frontend functions that operate on arrays. They are defined 
-in the C++ API (:ref:`cpp_ops`) and then we provide bindings to these 
-operations in the Python API (:ref:`ops`). 
+Operations are the front-end functions that operate on arrays. They are defined
+in the C++ API (:ref:`cpp_ops`), and the Python API (:ref:`ops`) binds them.
 
-We would like an operation, :meth:`axpby` that takes in two arrays ``x`` and ``y``,
-and two scalars, ``alpha`` and ``beta``. This is how we would define it in the 
-C++ API:
+We would like an operation, :meth:`axpby` that takes in two arrays ``x`` and
+``y``, and two scalars, ``alpha`` and ``beta``. This is how to define it in
+C++:
 
 .. code-block:: C++
 
@@ -83,10 +66,7 @@ C++ API:
         StreamOrDevice s = {} // Stream on which to schedule the operation
     );
 
-
-This operation itself can call other operations within it if needed. So, the 
-simplest way to go about implementing this operation would be do so in terms 
-of existing operations. 
+The simplest way to this operation is in terms of existing operations:
 
 .. code-block:: C++
 
@@ -100,25 +80,23 @@ of existing operations.
         // Scale x and y on the provided stream
         auto ax = multiply(array(alpha), x, s);
         auto by = multiply(array(beta), y, s);
-        
+
         // Add and return
         return add(ax, by, s);
     }
 
-However, as we discussed earlier, this is not our goal. The operations themselves 
-do not contain the implementations that act on the data, nor do they contain the
-rules of transformations. Rather, they are an easy to use interface that build 
-on top of the building blocks we call :class:`Primitive`. 
+The operations themselves do not contain the implementations that act on the
+data, nor do they contain the rules of transformations. Rather, they are an
+easy to use interface that use :class:`Primitive` building blocks.
 
 Primitives
 ^^^^^^^^^^^
 
-A :class:`Primitive` is part of the computation graph of an :class:`array`. It 
-defines how to create an output given a set of input :class:`array` . Further,
-a :class:`Primitive` is a class that contains rules on how it is evaluated 
-on the CPU or GPU, and how it acts under transformations such as ``vjp`` and 
-``jvp``. These words on their own can be a bit abstract, so lets take a step 
-back and go to our example to give ourselves a more concrete image. 
+A :class:`Primitive` is part of the computation graph of an :class:`array`. It
+defines how to create outputs arrays given a input arrays. Further, a
+:class:`Primitive` has methods to run on the CPU or GPU and for function
+transformations such as ``vjp`` and ``jvp``.  Lets go back to our example to be
+more concrete:
 
 .. code-block:: C++
 
@@ -134,11 +112,15 @@ back and go to our example to give ourselves a more concrete image.
         * To avoid unnecessary allocations, the evaluation function
         * is responsible for allocating space for the array.
         */
-        void eval_cpu(const std::vector<array>& inputs, array& out) override;
-        void eval_gpu(const std::vector<array>& inputs, array& out) override;
+        void eval_cpu(
+            const std::vector<array>& inputs,
+            std::vector<array>& outputs) override;
+        void eval_gpu(
+            const std::vector<array>& inputs,
+            std::vector<array>& outputs) override;
 
         /** The Jacobian-vector product. */
-        array jvp(
+        std::vector<array> jvp(
             const std::vector<array>& primals,
             const std::vector<array>& tangents,
             const std::vector<int>& argnums) override;
@@ -147,7 +129,8 @@ back and go to our example to give ourselves a more concrete image.
         std::vector<array> vjp(
             const std::vector<array>& primals,
             const array& cotan,
-            const std::vector<int>& argnums) override;
+            const std::vector<int>& argnums,
+            const std::vector<array>& outputs) override;
 
         /**
         * The primitive must know how to vectorize itself across
@@ -155,7 +138,7 @@ back and go to our example to give ourselves a more concrete image.
         * representing the vectorized computation and the axis which
         * corresponds to the output vectorized dimension.
         */
-        std::pair<array, int> vmap(
+        virtual std::pair<std::vector<array>, std::vector<int>> vmap(
             const std::vector<array>& inputs,
             const std::vector<int>& axes) override;
 
@@ -175,22 +158,22 @@ back and go to our example to give ourselves a more concrete image.
         void eval(const std::vector<array>& inputs, array& out);
     };
 
-The :class:`Axpby` class derives from the base :class:`Primitive` class and 
-follows the above demonstrated interface. :class:`Axpby` treats ``alpha`` and 
-``beta`` as parameters. It then provides implementations of how the array ``out`` 
-is produced given ``inputs`` through :meth:`Axpby::eval_cpu` and 
-:meth:`Axpby::eval_gpu`. Further, it provides rules of transformations in 
-:meth:`Axpby::jvp`, :meth:`Axpby::vjp`, and :meth:`Axpby::vmap`. 
+The :class:`Axpby` class derives from the base :class:`Primitive` class. The
+:class:`Axpby` treats ``alpha`` and ``beta`` as parameters. It then provides
+implementations of how the output array is produced given the inputs through
+:meth:`Axpby::eval_cpu` and :meth:`Axpby::eval_gpu`. It also provides rules
+of transformations in :meth:`Axpby::jvp`, :meth:`Axpby::vjp`, and
+:meth:`Axpby::vmap`.
 
-Using the Primitives
-^^^^^^^^^^^^^^^^^^^^^
+Using the Primitive
+^^^^^^^^^^^^^^^^^^^
 
-Operations can use this :class:`Primitive` to add a new :class:`array` to 
-the computation graph. An :class:`array` can be constructed by providing its 
-data type, shape, the :class:`Primitive` that computes it, and the 
-:class:`array` inputs that are passed to the primitive.
+Operations can use this :class:`Primitive` to add a new :class:`array` to the
+computation graph. An :class:`array` can be constructed by providing its data
+type, shape, the :class:`Primitive` that computes it, and the :class:`array`
+inputs that are passed to the primitive.
 
-Let's re-implement our operation now in terms of our :class:`Axpby` primitive.
+Let's reimplement our operation now in terms of our :class:`Axpby` primitive.
 
 .. code-block:: C++
 
@@ -238,27 +221,26 @@ This operation now handles the following:
 Implementing the Primitive
 --------------------------
 
-No computation happens when we call the operation alone. In effect, the 
-operation only builds the computation graph. When we evaluate the output 
-array, MLX schedules the execution of the computation graph, and calls
-:meth:`Axpby::eval_cpu` or :meth:`Axpby::eval_gpu` depending on the 
-stream/device specified by the user. 
+No computation happens when we call the operation alone. The operation only
+builds the computation graph. When we evaluate the output array, MLX schedules
+the execution of the computation graph, and calls :meth:`Axpby::eval_cpu` or
+:meth:`Axpby::eval_gpu` depending on the stream/device specified by the user.
 
 .. warning::
     When :meth:`Primitive::eval_cpu` or :meth:`Primitive::eval_gpu` are called,
     no memory has been allocated for the output array. It falls on the implementation
-    of these functions to allocate memory as needed
+    of these functions to allocate memory as needed.
 
-Implementing the CPU Backend
+Implementing the CPU Back-end
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Let's start by trying to implement a naive and generic version of 
-:meth:`Axpby::eval_cpu`. We declared this as a private member function of 
-:class:`Axpby` earlier called :meth:`Axpby::eval`. 
+Let's start by implementing a naive and generic version of
+:meth:`Axpby::eval_cpu`. We declared this as a private member function of
+:class:`Axpby` earlier called :meth:`Axpby::eval`.
 
-Our naive method will go over each element of the output array, find the 
-corresponding input elements of ``x`` and ``y`` and perform the operation 
-pointwise. This is captured in the templated function :meth:`axpby_impl`. 
+Our naive method will go over each element of the output array, find the
+corresponding input elements of ``x`` and ``y`` and perform the operation
+point-wise. This is captured in the templated function :meth:`axpby_impl`.
 
 .. code-block:: C++
 
@@ -296,19 +278,19 @@ pointwise. This is captured in the templated function :meth:`axpby_impl`.
         }
     }
 
-Now, we would like our implementation to be able to do this pointwise operation 
-for all incoming floating point arrays. Accordingly, we add dispatches for 
-``float32``, ``float16``, ``bfloat16`` and ``complex64``. We throw an error 
-if we encounter an unexpected type.
+Our implementation should work for all incoming floating point arrays.
+Accordingly, we add dispatches for ``float32``, ``float16``, ``bfloat16`` and
+``complex64``. We throw an error if we encounter an unexpected type.
 
 .. code-block:: C++
 
     /** Fall back implementation for evaluation on CPU */
-    void Axpby::eval(const std::vector<array>& inputs, array& out) {
-        // Check the inputs (registered in the op while constructing the out array)
-        assert(inputs.size() == 2);
+    void Axpby::eval(
+      const std::vector<array>& inputs,
+      const std::vector<array>& outputs) {
         auto& x = inputs[0];
         auto& y = inputs[1];
+        auto& out = outputs[0];
 
         // Dispatch to the correct dtype
         if (out.dtype() == float32) {
@@ -321,28 +303,26 @@ if we encounter an unexpected type.
             return axpby_impl<complex64_t>(x, y, out, alpha_, beta_);
         } else {
             throw std::runtime_error(
-                "Axpby is only supported for floating point types.");
+                "[Axpby] Only supports floating point types.");
         }
     }
 
-We have a fallback implementation! Now, to do what we are really here to do. 
-Remember we wanted to use the ``axpby`` routine provided by the Accelerate_
-framework? Well, there are 3 complications to keep in mind:
+This is good as a fallback implementation. We can use the ``axpby`` routine
+provided by the Accelerate_ framework for a faster implementation in certain
+cases:
 
 #.  Accelerate does not provide implementations of ``axpby`` for half precision
-    floats. We can only direct to it for ``float32`` types 
-#.  Accelerate assumes the inputs ``x`` and ``y`` are contiguous and all elements
-    have fixed strides between them. Possibly due to broadcasts and transposes, 
-    we aren't guaranteed that the inputs fit this requirement. We can 
-    only direct to Accelerate if both ``x`` and ``y`` are row contiguous or 
-    column contiguous. 
-#.  Accelerate performs the routine ``Y = (alpha * X) + (beta * Y)`` inplace. 
-    MLX expects to write out the answer to a new array. We must copy the elements 
-    of ``y`` into the output array and use that as an input to ``axpby``
+    floats. We can only use it for ``float32`` types.
+#.  Accelerate assumes the inputs ``x`` and ``y`` are contiguous and all
+    elements have fixed strides between them. We only direct to Accelerate
+    if both ``x`` and ``y`` are row contiguous or column contiguous.
+#.  Accelerate performs the routine ``Y = (alpha * X) + (beta * Y)`` in-place.
+    MLX expects to write the output to a new array. We must copy the elements
+    of ``y`` into the output and use that as an input to ``axpby``.
 
-Let's write out an implementation that uses Accelerate in the right conditions. 
-It must simply allocate data for the output, copy elements of ``y`` into it, 
-and then call the :meth:`catlas_saxpby` from accelerate. 
+Let's write an implementation that uses Accelerate in the right conditions.
+It allocates data for the output, copies ``y`` into it, and then calls the
+:func:`catlas_saxpby` from accelerate.
 
 .. code-block:: C++
 
@@ -356,17 +336,7 @@ and then call the :meth:`catlas_saxpby` from accelerate.
         // Accelerate library provides catlas_saxpby which does
         // Y = (alpha * X) + (beta * Y) in place
         // To use it, we first copy the data in y over to the output array
-
-        // This specialization requires both x and y be contiguous in the same mode
-        // i.e: corresponding linear indices in both point to corresponding elements
-        // The data in the output array is allocated to match the strides in y
-        // such that x, y, and out are contiguous in the same mode and
-        // no transposition is needed
-        out.set_data(
-            allocator::malloc_or_wait(y.data_size() * out.itemsize()),
-            y.data_size(),
-            y.strides(),
-            y.flags());
+        out.set_data(allocator::malloc_or_wait(out.nbytes()));
 
         // We then copy over the elements using the contiguous vector specialization
         copy_inplace(y, out, CopyType::Vector);
@@ -389,18 +359,20 @@ and then call the :meth:`catlas_saxpby` from accelerate.
             /* INCY = */ 1);
     }
 
-Great! But what about the inputs that do not fit the criteria for accelerate?
-Luckily, we can always just direct back to :meth:`Axpby::eval`.
-
-With this in mind, lets finally implement our :meth:`Axpby::eval_cpu`.
+For inputs that do not fit the criteria for accelerate, we fall back to
+:meth:`Axpby::eval`. With this in mind, let's finish our
+:meth:`Axpby::eval_cpu`.
 
 .. code-block:: C++
 
     /** Evaluate primitive on CPU using accelerate specializations */
-    void Axpby::eval_cpu(const std::vector<array>& inputs, array& out) {
+    void Axpby::eval_cpu(
+      const std::vector<array>& inputs,
+      const std::vector<array>& outputs) {
         assert(inputs.size() == 2);
         auto& x = inputs[0];
         auto& y = inputs[1];
+        auto& out = outputs[0];
 
         // Accelerate specialization for contiguous single precision float arrays
         if (out.dtype() == float32 &&
@@ -410,35 +382,33 @@ With this in mind, lets finally implement our :meth:`Axpby::eval_cpu`.
             return;
         }
 
-        // Fall back to common backend if specializations are not available
-        eval(inputs, out);
+        // Fall back to common back-end if specializations are not available
+        eval(inputs, outputs);
     }
 
-We have now hit a milestone! Just this much is enough to run the operation 
-:meth:`axpby` on a CPU stream! 
+Just this much is enough to run the operation :meth:`axpby` on a CPU stream! If
+you do not plan on running the operation on the GPU or using transforms on
+computation graphs that contain :class:`Axpby`, you can stop implementing the
+primitive here and enjoy the speed-ups you get from the Accelerate library.
 
-If you do not plan on running the operation on the GPU or using transforms on 
-computation graphs that contain :class:`Axpby`, you can stop implementing the 
-primitive here and enjoy the speed-ups you get from the Accelerate library. 
-
-Implementing the GPU Backend
+Implementing the GPU Back-end
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Apple silicon devices address their GPUs using the Metal_ shading language, and 
-all GPU kernels in MLX are written using metal. 
+Apple silicon devices address their GPUs using the Metal_ shading language, and
+GPU kernels in MLX are written using Metal.
 
 .. note::
 
-    Here are some helpful resources if you are new to metal!
+    Here are some helpful resources if you are new to Metal:
 
     * A walkthrough of the metal compute pipeline: `Metal Example`_
     * Documentation for metal shading language: `Metal Specification`_
     * Using metal from C++: `Metal-cpp`_
 
-Let's keep the GPU algorithm simple. We will launch exactly as many threads 
-as there are elements in the output. Each thread will pick the element it needs 
-from ``x`` and ``y``, do the pointwise operation, and then update its assigned 
-element in the output. 
+Let's keep the GPU kernel simple. We will launch exactly as many threads as
+there are elements in the output. Each thread will pick the element it needs
+from ``x`` and ``y``, do the point-wise operation, and update its assigned
+element in the output.
 
 .. code-block:: C++
 
@@ -457,15 +427,14 @@ element in the output.
         // Convert linear indices to offsets in array
         auto x_offset = elem_to_loc(index, shape, x_strides, ndim);
         auto y_offset = elem_to_loc(index, shape, y_strides, ndim);
-        
+
         // Do the operation and update the output
-        out[index] = 
+        out[index] =
             static_cast<T>(alpha) * x[x_offset] + static_cast<T>(beta) * y[y_offset];
     }
 
 We then need to instantiate this template for all floating point types and give
-each instantiation a unique host name so we can identify the right kernel for 
-each data type. 
+each instantiation a unique host name so we can identify it.
 
 .. code-block:: C++
 
@@ -488,29 +457,21 @@ each data type.
     instantiate_axpby(bfloat16, bfloat16_t);
     instantiate_axpby(complex64, complex64_t);
 
-This kernel will be compiled into a metal library ``mlx_ext.metallib`` as we 
-will see later in :ref:`Building with CMake`. In the following example, we 
-assume that the library ``mlx_ext.metallib`` will always be co-located with 
-the executable/ shared-library calling the :meth:`register_library` function. 
-The :meth:`register_library` function takes the library's name and potential 
-path (or in this case, a function that can produce the path of the metal 
-library) and tries to load that library if it hasn't already been registered 
-by the relevant static :class:`mlx::core::metal::Device` object. This is why, 
-it is important to package your C++ library with the metal library. We will 
-go over this process in more detail later. 
-
-The logic to determine the kernel, set the inputs, resolve the grid dimensions 
-and dispatch it to the GPU are contained in :meth:`Axpby::eval_gpu` as shown 
+The logic to determine the kernel, set the inputs, resolve the grid dimensions,
+and dispatch to the GPU are contained in :meth:`Axpby::eval_gpu` as shown
 below.
 
 .. code-block:: C++
 
     /** Evaluate primitive on GPU */
-    void Axpby::eval_gpu(const std::vector<array>& inputs, array& out) {
+    void Axpby::eval_gpu(
+      const std::vector<array>& inputs,
+      std::vector<array>& outputs) {
         // Prepare inputs
         assert(inputs.size() == 2);
         auto& x = inputs[0];
         auto& y = inputs[1];
+        auto& out = outputs[0];
 
         // Each primitive carries the stream it should execute on
         // and each stream carries its device identifiers
@@ -518,10 +479,10 @@ below.
         // We get the needed metal device using the stream
         auto& d = metal::device(s.device);
 
-        // Allocate output memory 
+        // Allocate output memory
         out.set_data(allocator::malloc_or_wait(out.nbytes()));
 
-        // Resolve name of kernel (corresponds to axpby.metal)
+        // Resolve name of kernel
         std::ostringstream kname;
         kname << "axpby_" << "general_" << type_to_name(out);
 
@@ -552,7 +513,7 @@ below.
         compute_encoder->setBytes(&alpha_, sizeof(float), 3);
         compute_encoder->setBytes(&beta_, sizeof(float), 4);
 
-        // Encode shape, strides and ndim 
+        // Encode shape, strides and ndim
         compute_encoder->setBytes(x.shape().data(), ndim * sizeof(int), 5);
         compute_encoder->setBytes(x.strides().data(), ndim * sizeof(size_t), 6);
         compute_encoder->setBytes(y.strides().data(), ndim * sizeof(size_t), 7);
@@ -575,28 +536,25 @@ below.
 
 We can now call the :meth:`axpby` operation on both the CPU and the GPU!
 
-A few things to note about MLX and metal before moving on. MLX keeps track 
-of the active ``compute_encoder``. We rely on :meth:`d.get_command_encoder` 
-to give us the active metal compute command encoder instead of building a 
-new one and calling :meth:`compute_encoder->end_encoding` at the end. 
-MLX keeps adding kernels (compute pipelines) to the active command encoder 
-until some specified limit is hit or the compute encoder needs to be flushed 
-for synchronization. MLX also handles enqueuing and committing the associated 
-command buffers as needed. We suggest taking a deeper dive into 
-:class:`metal::Device` if you would like to study this routine further.
+A few things to note about MLX and Metal before moving on. MLX keeps track of
+the active ``command_buffer`` and the ``MTLCommandBuffer`` to which it is
+associated. We rely on :meth:`d.get_command_encoder` to give us the active
+metal compute command encoder instead of building a new one and calling
+:meth:`compute_encoder->end_encoding` at the end. MLX adds kernels (compute
+pipelines) to the active command buffer until some specified limit is hit or
+the command buffer needs to be flushed for synchronization.
 
 Primitive Transforms
 ^^^^^^^^^^^^^^^^^^^^^
 
-Now that we have come this far, let's also learn how to add implementations to 
-transformations in a :class:`Primitive`. These transformations can be built on 
-top of our operations, including the one we just defined now. Which then gives 
-us the following :meth:`Axpby::jvp` and :meth:`Axpby::vjp` implementations.
+Next, let's add implementations for transformations in a :class:`Primitive`.
+These transformations can be built on top of other operations, including the
+one we just defined:
 
 .. code-block:: C++
 
     /** The Jacobian-vector product. */
-    array Axpby::jvp(
+    std::vector<array> Axpby::jvp(
             const std::vector<array>& primals,
             const std::vector<array>& tangents,
             const std::vector<int>& argnums) {
@@ -611,12 +569,12 @@ us the following :meth:`Axpby::jvp` and :meth:`Axpby::vjp` implementations.
         if (argnums.size() > 1) {
             auto scale = argnums[0] == 0 ? alpha_ : beta_;
             auto scale_arr = array(scale, tangents[0].dtype());
-            return multiply(scale_arr, tangents[0], stream());
+            return {multiply(scale_arr, tangents[0], stream())};
         }
         // If, argnums = {0, 1}, we take contributions from both
         // which gives us jvp = tangent_x * alpha + tangent_y * beta
         else {
-            return axpby(tangents[0], tangents[1], alpha_, beta_, stream());
+            return {axpby(tangents[0], tangents[1], alpha_, beta_, stream())};
         }
     }
 
@@ -625,34 +583,35 @@ us the following :meth:`Axpby::jvp` and :meth:`Axpby::vjp` implementations.
     /** The vector-Jacobian product. */
     std::vector<array> Axpby::vjp(
             const std::vector<array>& primals,
-            const array& cotan,
-            const std::vector<int>& argnums) {
+            const std::vector<array>& cotangents,
+            const std::vector<int>& argnums,
+            const std::vector<int>& /* unused */) {
         // Reverse mode diff
         std::vector<array> vjps;
         for (auto arg : argnums) {
             auto scale = arg == 0 ? alpha_ : beta_;
-            auto scale_arr = array(scale, cotan.dtype());
-            vjps.push_back(multiply(scale_arr, cotan, stream()));
+            auto scale_arr = array(scale, cotangents[0].dtype());
+            vjps.push_back(multiply(scale_arr, cotangents[0], stream()));
         }
         return vjps;
     }
 
-Finally, you need not have a transformation fully defined to start using your 
-own :class:`Primitive`.
+Note, a transformation does not need to be fully defined to start using
+the :class:`Primitive`.
 
 .. code-block:: C++
 
     /** Vectorize primitive along given axis */
-    std::pair<array, int> Axpby::vmap(
+    std::pair<std::vector<array>, std::vector<int>> Axpby::vmap(
             const std::vector<array>& inputs,
             const std::vector<int>& axes) {
-        throw std::runtime_error("Axpby has no vmap implementation.");
+        throw std::runtime_error("[Axpby] vmap not implemented.");
     }
 
 Building and Binding
 --------------------
 
-Let's look at the overall directory structure first. 
+Let's look at the overall directory structure first.
 
 | extensions
 | ├── axpby
@@ -666,40 +625,39 @@ Let's look at the overall directory structure first.
 | └── setup.py
 
 * ``extensions/axpby/`` defines the C++ extension library
-* ``extensions/mlx_sample_extensions`` sets out the structure for the 
-  associated python package
-* ``extensions/bindings.cpp`` provides python bindings for our operation
-* ``extensions/CMakeLists.txt`` holds CMake rules to build the library and 
-  python bindings
+* ``extensions/mlx_sample_extensions`` sets out the structure for the
+  associated Python package
+* ``extensions/bindings.cpp`` provides Python bindings for our operation
+* ``extensions/CMakeLists.txt`` holds CMake rules to build the library and
+  Python bindings
 * ``extensions/setup.py`` holds the ``setuptools`` rules to build and install
-  the python package
+  the Python package
 
 Binding to Python
 ^^^^^^^^^^^^^^^^^^
 
-We use PyBind11_ to build a Python API for the C++ library. Since bindings for
+We use nanobind_ to build a Python API for the C++ library. Since bindings for
 components such as :class:`mlx.core.array`, :class:`mlx.core.stream`, etc. are
-already provided, adding our :meth:`axpby` is simple!
+already provided, adding our :meth:`axpby` is simple.
 
 .. code-block:: C++
 
-    PYBIND11_MODULE(mlx_sample_extensions, m) {
-        m.doc() = "Sample C++ and metal extensions for MLX";
+   NB_MODULE(_ext, m) {
+        m.doc() = "Sample extension for MLX";
 
         m.def(
             "axpby",
             &axpby,
             "x"_a,
             "y"_a,
-            py::pos_only(),
             "alpha"_a,
             "beta"_a,
-            py::kw_only(),
-            "stream"_a = py::none(),
-            R"pbdoc(
+            nb::kw_only(),
+            "stream"_a = nb::none(),
+            R"(
                 Scale and sum two vectors element-wise
                 ``z = alpha * x + beta * y``
-                
+
                 Follows numpy style broadcasting between ``x`` and ``y``
                 Inputs are upcasted to floats if needed
 
@@ -711,17 +669,17 @@ already provided, adding our :meth:`axpby` is simple!
 
                 Returns:
                     array: ``alpha * x + beta * y``
-            )pbdoc");
+            )");
     }
 
-Most of the complexity in the above example comes from additional bells and 
+Most of the complexity in the above example comes from additional bells and
 whistles such as the literal names and doc-strings.
 
 .. warning::
 
-    :mod:`mlx.core` needs to be imported before importing 
-    :mod:`mlx_sample_extensions` as defined by the pybind11 module above to 
-    ensure that the casters for :mod:`mlx.core` components like 
+    :mod:`mlx.core` must be imported before importing
+    :mod:`mlx_sample_extensions` as defined by the nanobind module above to
+    ensure that the casters for :mod:`mlx.core` components like
     :class:`mlx.core.array` are available.
 
 .. _Building with CMake:
@@ -729,8 +687,8 @@ whistles such as the literal names and doc-strings.
 Building with CMake
 ^^^^^^^^^^^^^^^^^^^^
 
-Building the C++ extension library itself is simple, it only requires that you 
-``find_package(MLX CONFIG)`` and then link it to your library. 
+Building the C++ extension library only requires that you ``find_package(MLX
+CONFIG)`` and then link it to your library.
 
 .. code-block:: cmake
 
@@ -752,12 +710,12 @@ Building the C++ extension library itself is simple, it only requires that you
     # Link to mlx
     target_link_libraries(mlx_ext PUBLIC mlx)
 
-We also need to build the attached metal library. For convenience, we provide a 
-:meth:`mlx_build_metallib` function that builds a ``.metallib`` target given 
-sources, headers, destinations, etc. (defined in ``cmake/extension.cmake`` and 
-automatically imported with MLX package). 
+We also need to build the attached Metal library. For convenience, we provide a
+:meth:`mlx_build_metallib` function that builds a ``.metallib`` target given
+sources, headers, destinations, etc. (defined in ``cmake/extension.cmake`` and
+automatically imported with MLX package).
 
-Here is what that looks like in practice!
+Here is what that looks like in practice:
 
 .. code-block:: cmake
 
@@ -779,27 +737,29 @@ Here is what that looks like in practice!
 
     endif()
 
-Finally, we build the Pybind11_ bindings
+Finally, we build the nanobind_ bindings
 
 .. code-block:: cmake
 
-    pybind11_add_module(
-        mlx_sample_extensions
-        ${CMAKE_CURRENT_LIST_DIR}/bindings.cpp
+    nanobind_add_module(
+      _ext
+      NB_STATIC STABLE_ABI LTO NOMINSIZE
+      NB_DOMAIN mlx
+      ${CMAKE_CURRENT_LIST_DIR}/bindings.cpp
     )
-    target_link_libraries(mlx_sample_extensions PRIVATE mlx_ext)
+    target_link_libraries(_ext PRIVATE mlx_ext)
 
     if(BUILD_SHARED_LIBS)
-        target_link_options(mlx_sample_extensions PRIVATE -Wl,-rpath,@loader_path)
+      target_link_options(_ext PRIVATE -Wl,-rpath,@loader_path)
     endif()
 
 Building with ``setuptools``
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Once we have set out the CMake build rules as described above, we can use the
-build utilities defined in :mod:`mlx.extension` for a simple build process. 
+build utilities defined in :mod:`mlx.extension`:
 
-.. code-block:: python 
+.. code-block:: python
 
     from mlx import extension
     from setuptools import setup
@@ -809,48 +769,50 @@ build utilities defined in :mod:`mlx.extension` for a simple build process.
             name="mlx_sample_extensions",
             version="0.0.0",
             description="Sample C++ and Metal extensions for MLX primitives.",
-            ext_modules=[extension.CMakeExtension("mlx_sample_extensions")],
+            ext_modules=[extension.CMakeExtension("mlx_sample_extensions._ext")],
             cmdclass={"build_ext": extension.CMakeBuild},
-            packages = ["mlx_sample_extensions"],
-            package_dir = {"": "mlx_sample_extensions"},
-            package_data = {"mlx_sample_extensions" : ["*.so", "*.dylib", "*.metallib"]},
+            packages=["mlx_sample_extensions"],
+            package_data={"mlx_sample_extensions": ["*.so", "*.dylib", "*.metallib"]},
+            extras_require={"dev":[]},
             zip_safe=False,
-            python_requires=">=3.7",
+            python_requires=">=3.8",
         )
 
 .. note::
     We treat ``extensions/mlx_sample_extensions`` as the package directory
     even though it only contains a ``__init__.py`` to ensure the following:
-    
-    * :mod:`mlx.core` is always imported before importing  :mod:`mlx_sample_extensions`
-    * The C++ extension library and the metal library are co-located with the python 
-      bindings and copied together if the package is installed 
 
-You can build inplace for development using
+    * :mod:`mlx.core` must be imported before importing :mod:`_ext`
+    * The C++ extension library and the metal library are co-located with the python
+      bindings and copied together if the package is installed
+
+To build the package, first install the build dependencies with ``pip install
+-r requirements.txt``.  You can then build inplace for development using
 ``python setup.py build_ext -j8 --inplace`` (in ``extensions/``)
 
-This will result in a directory structure as follows:
+This results in the directory structure:
 
 | extensions
 | ├── mlx_sample_extensions
 | │   ├── __init__.py
 | │   ├── libmlx_ext.dylib # C++ extension library
 | │   ├── mlx_ext.metallib # Metal library
-| │   └── mlx_sample_extensions.cpython-3x-darwin.so # Python Binding
+| │   └── _ext.cpython-3x-darwin.so # Python Binding
 | ...
 
-When you try to install using the command ``python -m pip install .`` 
-(in ``extensions/``), the package will be installed with the same structure as 
-``extensions/mlx_sample_extensions`` and the C++ and metal library will be 
-copied along with the python binding since they are specified as ``package_data``.
+When you try to install using the command ``python -m pip install .`` (in
+``extensions/``), the package will be installed with the same structure as
+``extensions/mlx_sample_extensions`` and the C++ and Metal library will be
+copied along with the Python binding since they are specified as
+``package_data``.
 
 Usage
 -----
 
-After installing the extension as described above, you should be able to simply 
-import the python package and play with it as you would any other MLX operation!
+After installing the extension as described above, you should be able to simply
+import the Python package and play with it as you would any other MLX operation.
 
-Let's looks at a simple script and it's results!
+Let's look at a simple script and its results:
 
 .. code-block:: python
 
@@ -874,12 +836,12 @@ Output:
     c correctness: True
 
 Results
-^^^^^^^^^^^^^^^^
+^^^^^^^
 
-Let's run a quick benchmark and see how our new ``axpby`` operation compares 
-with the naive :meth:`simple_axpby` we defined at first on the CPU. 
+Let's run a quick benchmark and see how our new ``axpby`` operation compares
+with the naive :meth:`simple_axpby` we first defined on the CPU.
 
-.. code-block:: python 
+.. code-block:: python
 
     import mlx.core as mx
     from mlx_sample_extensions import axpby
@@ -898,7 +860,7 @@ with the naive :meth:`simple_axpby` we defined at first on the CPU.
     alpha = 4.0
     beta = 2.0
 
-    mx.eval((x, y))
+    mx.eval(x, y)
 
     def bench(f):
         # Warm up
@@ -919,30 +881,23 @@ with the naive :meth:`simple_axpby` we defined at first on the CPU.
 
     print(f"Simple axpby: {simple_time:.3f} s | Custom axpby: {custom_time:.3f} s")
 
-Results:
-
-.. code-block::
-
-    Simple axpby: 0.114 s | Custom axpby: 0.109 s
-
-We see some modest improvements right away! 
+The results are ``Simple axpby: 0.114 s | Custom axpby: 0.109 s``. We see
+modest improvements right away!
 
 This operation is now good to be used to build other operations, in
 :class:`mlx.nn.Module` calls, and also as a part of graph transformations like
-:meth:`grad`!
+:meth:`grad`.
 
 Scripts
 -------
 
 .. admonition:: Download the code
 
-   The full example code is available in `mlx <code>`_.
-
-.. code: `https://github.com/ml-explore/mlx/tree/main/examples/extensions/`_
+   The full example code is available in `mlx <https://github.com/ml-explore/mlx/tree/main/examples/extensions/>`_.
 
 .. _Accelerate: https://developer.apple.com/documentation/accelerate/blas?language=objc
 .. _Metal: https://developer.apple.com/documentation/metal?language=objc
 .. _Metal-cpp: https://developer.apple.com/metal/cpp/
 .. _`Metal Specification`: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf
 .. _`Metal Example`: https://developer.apple.com/documentation/metal/performing_calculations_on_a_gpu?language=objc
-.. _PyBind11: https://pybind11.readthedocs.io/en/stable/
+.. _nanobind: https://nanobind.readthedocs.io/en/latest/

docs/build/html/_sources/dev/metal_debugger.rst

@@ -1,29 +1,46 @@
 Metal Debugger
 ==============
 
+.. currentmodule:: mlx.core
+
 Profiling is a key step for performance optimization. You can build MLX with
-the ``MLX_METAL_DEBUG`` option to improve the Metal debugging and optimization
-workflow. The ``MLX_METAL_DEBUG`` debug option:
+the ``MLX_METAL_DEBUG`` option to improve the Metal debugging and
+optimization workflow. The ``MLX_METAL_DEBUG`` debug option:
 
 * Records source during Metal compilation, for later inspection while
   debugging.
 * Labels Metal objects such as command queues, improving capture readability.
 
-The ``metal::start_capture`` function initiates a capture of all MLX GPU work.
+To build with debugging enabled in Python prepend
+``CMAKE_ARGS="-DMLX_METAL_DEBUG=ON"`` to the build call.
 
-.. code-block:: C++
+The :func:`metal.start_capture` function initiates a capture of all MLX GPU
+work.
 
-    int main() {
-        metal::start_capture("/Users/Jane/Developer/MLX.gputrace");
+.. note::
 
-        auto a = arange(10.f, 20.f, 1.f, float32);
-        auto b = arange(30.f, 40.f, 1.f, float32);
-        auto c = add(a, b);
+   To capture a GPU trace you must run the application with
+   ``MTL_CAPTURE_ENABLED=1``.
 
-        eval(c);
+.. code-block:: python
 
-        metal::stop_capture();
-    }
+    import mlx.core as mx
+
+    a = mx.random.uniform(shape=(512, 512))
+    b = mx.random.uniform(shape=(512, 512))
+    mx.eval(a, b)
+
+    trace_file = "mlx_trace.gputrace"
+
+    if not mx.metal.start_capture(trace_file):
+      print("Make sure to run with MTL_CAPTURE_ENABLED=1 and "
+            f"that the path {trace_file} does not already exist.")
+      exit(1)
+
+    for _ in range(10):
+      mx.eval(mx.add(a, b))
+
+    mx.metal.stop_capture()
 
 You can open and replay the GPU trace in Xcode. The ``Dependencies`` view
 has a great overview of all operations. Checkout the `Metal debugger
@@ -35,8 +52,8 @@ documentation`_ for more information.
 Xcode Workflow
 --------------
 
-You can skip saving to a path by running within Xcode. First, generate an Xcode
-project using CMake.
+You can skip saving to a path by running within Xcode. First, generate an
+Xcode project using CMake.
 
 .. code-block::
 

docs/build/html/_sources/python/_autosummary/mlx.core.expm1.rst

@@ -0,0 +1,6 @@
+mlx.core.expm1
+==============
+
+.. currentmodule:: mlx.core
+
+.. autofunction:: expm1

docs/build/html/_sources/python/_autosummary/mlx.core.meshgrid.rst

@@ -0,0 +1,6 @@
+mlx.core.meshgrid
+=================
+
+.. currentmodule:: mlx.core
+
+.. autofunction:: meshgrid

docs/build/html/_sources/python/_autosummary/mlx.core.metal.start_capture.rst

@@ -0,0 +1,6 @@
+mlx.core.metal.start\_capture
+=============================
+
+.. currentmodule:: mlx.core.metal
+
+.. autofunction:: start_capture

docs/build/html/_sources/python/_autosummary/mlx.core.metal.stop_capture.rst

@@ -0,0 +1,6 @@
+mlx.core.metal.stop\_capture
+============================
+
+.. currentmodule:: mlx.core.metal
+
+.. autofunction:: stop_capture

docs/build/html/_sources/python/_autosummary/mlx.core.random.multivariate_normal.rst

@@ -0,0 +1,6 @@
+mlx.core.random.multivariate\_normal
+====================================
+
+.. currentmodule:: mlx.core.random
+
+.. autofunction:: multivariate_normal

docs/build/html/_sources/python/_autosummary/mlx.core.std.rst

@@ -0,0 +1,6 @@
+mlx.core.std
+============
+
+.. currentmodule:: mlx.core
+
+.. autofunction:: std

docs/build/html/_sources/python/metal.rst

@@ -3,7 +3,7 @@ Metal
 
 .. currentmodule:: mlx.core.metal
 
-.. autosummary:: 
+.. autosummary::
   :toctree: _autosummary
 
   is_available
@@ -12,3 +12,5 @@ Metal
   get_cache_memory
   set_memory_limit
   set_cache_limit
+  start_capture
+  stop_capture

docs/build/html/_sources/python/ops.rst

@@ -5,13 +5,13 @@ Operations
 
 .. currentmodule:: mlx.core
 
-.. autosummary:: 
+.. autosummary::
   :toctree: _autosummary
 
    abs
    add
    all
-   allclose 
+   allclose
    any
    arange
    arccos
@@ -51,6 +51,7 @@ Operations
    erf
    erfinv
    exp
+   expm1
    expand_dims
    eye
    flatten
@@ -83,6 +84,7 @@ Operations
    max
    maximum
    mean
+   meshgrid
    min
    minimum
    moveaxis
@@ -117,6 +119,7 @@ Operations
    square
    squeeze
    stack
+   std
    stop_gradient
    subtract
    sum

docs/build/html/_sources/python/random.rst

@@ -38,6 +38,7 @@ we use a splittable version of Threefry, which is a counter-based PRNG.
    gumbel
    key
    normal
+   multivariate_normal
    randint
    seed
    split

docs/build/html/_sources/usage/lazy_evaluation.rst

@@ -18,7 +18,7 @@ describe below.
 Transforming Compute Graphs
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Lazy evaluation let's us record a compute graph without actually doing any
+Lazy evaluation lets us record a compute graph without actually doing any
 computations. This is useful for function transformations like :func:`grad` and
 :func:`vmap` and graph optimizations.
 

docs/build/html/_static/documentation_options.js

@@ -1,5 +1,5 @@
 const DOCUMENTATION_OPTIONS = {
-    VERSION: '0.9.0',
+    VERSION: '0.10.0',
     LANGUAGE: 'en',
     COLLAPSE_INDEX: false,
     BUILDER: 'html',

docs/build/html/cpp/ops.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Operations &#8212; MLX 0.9.0 documentation</title>
+    <title>Operations &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../_static/documentation_options.js?v=cb265169"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -131,8 +131,8 @@
       
     
     
-    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.max.html">mlx.core.max</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -352,6 +354,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.square.html">mlx.core.square</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.subtract.html">mlx.core.subtract</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.sum.html">mlx.core.sum</a></li>
@@ -379,6 +382,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.gumbel.html">mlx.core.random.gumbel</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.key.html">mlx.core.random.key</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.seed.html">mlx.core.random.seed</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -432,6 +436,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>

docs/build/html/dev/extensions.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Developer Documentation &#8212; MLX 0.9.0 documentation</title>
+    <title>Developer Documentation &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../_static/documentation_options.js?v=cb265169"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -131,8 +131,8 @@
       
     
     
-    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.max.html">mlx.core.max</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -352,6 +354,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.square.html">mlx.core.square</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.subtract.html">mlx.core.subtract</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.sum.html">mlx.core.sum</a></li>
@@ -379,6 +382,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.gumbel.html">mlx.core.random.gumbel</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.key.html">mlx.core.random.key</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.seed.html">mlx.core.random.seed</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -432,6 +436,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>
@@ -763,12 +769,12 @@ document.write(`
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#operations-and-primitives">Operations and Primitives</a><ul class="visible nav section-nav flex-column">
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#operations">Operations</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#primitives">Primitives</a></li>
-<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#using-the-primitives">Using the Primitives</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#using-the-primitive">Using the Primitive</a></li>
 </ul>
 </li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-primitive">Implementing the Primitive</a><ul class="visible nav section-nav flex-column">
-<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-cpu-backend">Implementing the CPU Backend</a></li>
-<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-gpu-backend">Implementing the GPU Backend</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-cpu-back-end">Implementing the CPU Back-end</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-gpu-back-end">Implementing the GPU Back-end</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#primitive-transforms">Primitive Transforms</a></li>
 </ul>
 </li>
@@ -796,61 +802,45 @@ document.write(`
                   
   <section id="developer-documentation">
 <h1>Developer Documentation<a class="headerlink" href="#developer-documentation" title="Link to this heading">#</a></h1>
-<p>MLX provides a open and flexible backend to which users may add operations
-and specialized implementations without much hassle. While the library supplies
-efficient operations that can be used and composed for any number of
-applications, there may arise cases where new functionalities or highly
-optimized implementations are needed. For such cases, you may design and
-implement your own operations that link to and build on top of <code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.core</span></code>.
-We will introduce the inner-workings of MLX and go over a simple example to
-learn the steps involved in adding new operations to MLX with your own CPU
-and GPU implementations.</p>
+<p>You can extend MLX with custom operations on the CPU or GPU. This guide
+explains how to do that with a simple example.</p>
 <section id="introducing-the-example">
 <h2>Introducing the Example<a class="headerlink" href="#introducing-the-example" title="Link to this heading">#</a></h2>
-<p>Let’s say that you would like an operation that takes in two arrays,
-<code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code>, scales them both by some coefficients <code class="docutils literal notranslate"><span class="pre">alpha</span></code> and <code class="docutils literal notranslate"><span class="pre">beta</span></code>
-respectively, and then adds them together to get the result
-<code class="docutils literal notranslate"><span class="pre">z</span> <span class="pre">=</span> <span class="pre">alpha</span> <span class="pre">*</span> <span class="pre">x</span> <span class="pre">+</span> <span class="pre">beta</span> <span class="pre">*</span> <span class="pre">y</span></code>. Well, you can very easily do that by just
-writing out a function as follows:</p>
+<p>Let’s say you would like an operation that takes in two arrays, <code class="docutils literal notranslate"><span class="pre">x</span></code> and
+<code class="docutils literal notranslate"><span class="pre">y</span></code>, scales them both by coefficients <code class="docutils literal notranslate"><span class="pre">alpha</span></code> and <code class="docutils literal notranslate"><span class="pre">beta</span></code> respectively,
+and then adds them together to get the result <code class="docutils literal notranslate"><span class="pre">z</span> <span class="pre">=</span> <span class="pre">alpha</span> <span class="pre">*</span> <span class="pre">x</span> <span class="pre">+</span> <span class="pre">beta</span> <span class="pre">*</span> <span class="pre">y</span></code>.
+You can do that in MLX directly:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">mlx.core</span> <span class="k">as</span> <span class="nn">mx</span>
 
 <span class="k">def</span> <span class="nf">simple_axpby</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">array</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="n">mx</span><span class="o">.</span><span class="n">array</span><span class="p">,</span> <span class="n">alpha</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> <span class="n">beta</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">mx</span><span class="o">.</span><span class="n">array</span><span class="p">:</span>
     <span class="k">return</span> <span class="n">alpha</span> <span class="o">*</span> <span class="n">x</span> <span class="o">+</span> <span class="n">beta</span> <span class="o">*</span> <span class="n">y</span>
 </pre></div>
 </div>
-<p>This function performs that operation while leaving the implementations and
-differentiation to MLX.</p>
-<p>However, you work with vector math libraries often and realize that the
-<code class="docutils literal notranslate"><span class="pre">axpby</span></code> routine defines the same operation <code class="docutils literal notranslate"><span class="pre">Y</span> <span class="pre">=</span> <span class="pre">(alpha</span> <span class="pre">*</span> <span class="pre">X)</span> <span class="pre">+</span> <span class="pre">(beta</span> <span class="pre">*</span> <span class="pre">Y)</span></code>.
-You would really like the part of your applications that does this operation
-on the CPU to be very fast - so you decide that you want it to rely on the
-<code class="docutils literal notranslate"><span class="pre">axpby</span></code> routine provided by the <a class="reference external" href="https://developer.apple.com/documentation/accelerate/blas?language=objc">Accelerate</a> framework. Continuing to impose
-our assumptions on to you, let’s also assume that you want to learn how to add
-your own implementation for the gradients of your new operation while going
-over the ins-and-outs of the MLX framework.</p>
-<p>Well, what a coincidence! You are in the right place. Over the course of this
-example, we will learn:</p>
+<p>This function performs that operation while leaving the implementation and
+function transformations to MLX.</p>
+<p>However you may need to customize the underlying implementation, perhaps to
+make it faster or for custom differentiation. In this tutorial we will go
+through adding custom extensions. It will cover:</p>
 <ul class="simple">
-<li><p>The structure of the MLX library from the frontend API to the backend implementations.</p></li>
-<li><p>How to implement your own CPU backend that redirects to <a class="reference external" href="https://developer.apple.com/documentation/accelerate/blas?language=objc">Accelerate</a> when appropriate (and a fallback if needed).</p></li>
-<li><p>How to implement your own GPU implementation using metal.</p></li>
-<li><p>How to add your own <code class="docutils literal notranslate"><span class="pre">vjp</span></code> and <code class="docutils literal notranslate"><span class="pre">jvp</span></code>.</p></li>
-<li><p>How to build your implementations, link them to MLX, and bind them to python.</p></li>
+<li><p>The structure of the MLX library.</p></li>
+<li><p>Implementing a CPU operation that redirects to <a class="reference external" href="https://developer.apple.com/documentation/accelerate/blas?language=objc">Accelerate</a> when appropriate.</p></li>
+<li><p>Implementing a GPU operation using metal.</p></li>
+<li><p>Adding the <code class="docutils literal notranslate"><span class="pre">vjp</span></code> and <code class="docutils literal notranslate"><span class="pre">jvp</span></code> function transformation.</p></li>
+<li><p>Building a custom extension and binding it to python.</p></li>
 </ul>
 </section>
 <section id="operations-and-primitives">
 <h2>Operations and Primitives<a class="headerlink" href="#operations-and-primitives" title="Link to this heading">#</a></h2>
-<p>In one sentence, operations in MLX build the computation graph, and primitives
-provide the rules for evaluation and transformations of said graph. Let’s start
-by discussing operations in more detail.</p>
+<p>Operations in MLX build the computation graph. Primitives provide the rules for
+evaluating and transforming the graph. Let’s start by discussing operations in
+more detail.</p>
 <section id="operations">
 <h3>Operations<a class="headerlink" href="#operations" title="Link to this heading">#</a></h3>
-<p>Operations are the frontend functions that operate on arrays. They are defined
-in the C++ API (<a class="reference internal" href="../cpp/ops.html#cpp-ops"><span class="std std-ref">Operations</span></a>) and then we provide bindings to these
-operations in the Python API (<a class="reference internal" href="../python/ops.html#ops"><span class="std std-ref">Operations</span></a>).</p>
-<p>We would like an operation, <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby()</span></code> that takes in two arrays <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code>,
-and two scalars, <code class="docutils literal notranslate"><span class="pre">alpha</span></code> and <code class="docutils literal notranslate"><span class="pre">beta</span></code>. This is how we would define it in the
-C++ API:</p>
+<p>Operations are the front-end functions that operate on arrays. They are defined
+in the C++ API (<a class="reference internal" href="../cpp/ops.html#cpp-ops"><span class="std std-ref">Operations</span></a>), and the Python API (<a class="reference internal" href="../python/ops.html#ops"><span class="std std-ref">Operations</span></a>) binds them.</p>
+<p>We would like an operation, <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby()</span></code> that takes in two arrays <code class="docutils literal notranslate"><span class="pre">x</span></code> and
+<code class="docutils literal notranslate"><span class="pre">y</span></code>, and two scalars, <code class="docutils literal notranslate"><span class="pre">alpha</span></code> and <code class="docutils literal notranslate"><span class="pre">beta</span></code>. This is how to define it in
+C++:</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cm">/**</span>
 <span class="cm">*  Scale and sum two vectors element-wise</span>
 <span class="cm">*  z = alpha * x + beta * y</span>
@@ -867,9 +857,7 @@ C++ API:</p>
 <span class="p">);</span>
 </pre></div>
 </div>
-<p>This operation itself can call other operations within it if needed. So, the
-simplest way to go about implementing this operation would be do so in terms
-of existing operations.</p>
+<p>The simplest way to this operation is in terms of existing operations:</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="n">array</span><span class="w"> </span><span class="nf">axpby</span><span class="p">(</span>
 <span class="w">    </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">x</span><span class="p">,</span><span class="w"> </span><span class="c1">// Input array x</span>
 <span class="w">    </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">y</span><span class="p">,</span><span class="w"> </span><span class="c1">// Input array y</span>
@@ -886,19 +874,17 @@ of existing operations.</p>
 <span class="p">}</span>
 </pre></div>
 </div>
-<p>However, as we discussed earlier, this is not our goal. The operations themselves
-do not contain the implementations that act on the data, nor do they contain the
-rules of transformations. Rather, they are an easy to use interface that build
-on top of the building blocks we call <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code>.</p>
+<p>The operations themselves do not contain the implementations that act on the
+data, nor do they contain the rules of transformations. Rather, they are an
+easy to use interface that use <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> building blocks.</p>
 </section>
 <section id="primitives">
 <h3>Primitives<a class="headerlink" href="#primitives" title="Link to this heading">#</a></h3>
 <p>A <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> is part of the computation graph of an <code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code>. It
-defines how to create an output given a set of input <code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code> . Further,
-a <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> is a class that contains rules on how it is evaluated
-on the CPU or GPU, and how it acts under transformations such as <code class="docutils literal notranslate"><span class="pre">vjp</span></code> and
-<code class="docutils literal notranslate"><span class="pre">jvp</span></code>. These words on their own can be a bit abstract, so lets take a step
-back and go to our example to give ourselves a more concrete image.</p>
+defines how to create outputs arrays given a input arrays. Further, a
+<code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> has methods to run on the CPU or GPU and for function
+transformations such as <code class="docutils literal notranslate"><span class="pre">vjp</span></code> and <code class="docutils literal notranslate"><span class="pre">jvp</span></code>.  Lets go back to our example to be
+more concrete:</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="k">class</span><span class="w"> </span><span class="nc">Axpby</span><span class="w"> </span><span class="o">:</span><span class="w"> </span><span class="k">public</span><span class="w"> </span><span class="n">Primitive</span><span class="w"> </span><span class="p">{</span>
 <span class="w">  </span><span class="k">public</span><span class="o">:</span>
 <span class="w">    </span><span class="k">explicit</span><span class="w"> </span><span class="n">Axpby</span><span class="p">(</span><span class="n">Stream</span><span class="w"> </span><span class="n">stream</span><span class="p">,</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="n">alpha</span><span class="p">,</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="n">beta</span><span class="p">)</span>
@@ -911,11 +897,15 @@ back and go to our example to give ourselves a more concrete image.</p>
 <span class="cm">    * To avoid unnecessary allocations, the evaluation function</span>
 <span class="cm">    * is responsible for allocating space for the array.</span>
 <span class="cm">    */</span>
-<span class="w">    </span><span class="kt">void</span><span class="w"> </span><span class="nf">eval_cpu</span><span class="p">(</span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
-<span class="w">    </span><span class="kt">void</span><span class="w"> </span><span class="nf">eval_gpu</span><span class="p">(</span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
+<span class="w">    </span><span class="kt">void</span><span class="w"> </span><span class="nf">eval_cpu</span><span class="p">(</span>
+<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span>
+<span class="w">        </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">outputs</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
+<span class="w">    </span><span class="kt">void</span><span class="w"> </span><span class="nf">eval_gpu</span><span class="p">(</span>
+<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span>
+<span class="w">        </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">outputs</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
 
 <span class="w">    </span><span class="cm">/** The Jacobian-vector product. */</span>
-<span class="w">    </span><span class="n">array</span><span class="w"> </span><span class="nf">jvp</span><span class="p">(</span>
+<span class="w">    </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;</span><span class="w"> </span><span class="n">jvp</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">primals</span><span class="p">,</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">tangents</span><span class="p">,</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">argnums</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
@@ -924,7 +914,8 @@ back and go to our example to give ourselves a more concrete image.</p>
 <span class="w">    </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;</span><span class="w"> </span><span class="n">vjp</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">primals</span><span class="p">,</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">cotan</span><span class="p">,</span>
-<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">argnums</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
+<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">argnums</span><span class="p">,</span>
+<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">outputs</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
 
 <span class="w">    </span><span class="cm">/**</span>
 <span class="cm">    * The primitive must know how to vectorize itself across</span>
@@ -932,7 +923,7 @@ back and go to our example to give ourselves a more concrete image.</p>
 <span class="cm">    * representing the vectorized computation and the axis which</span>
 <span class="cm">    * corresponds to the output vectorized dimension.</span>
 <span class="cm">    */</span>
-<span class="w">    </span><span class="n">std</span><span class="o">::</span><span class="n">pair</span><span class="o">&lt;</span><span class="n">array</span><span class="p">,</span><span class="w"> </span><span class="kt">int</span><span class="o">&gt;</span><span class="w"> </span><span class="n">vmap</span><span class="p">(</span>
+<span class="w">    </span><span class="k">virtual</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">pair</span><span class="o">&lt;</span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;</span><span class="p">,</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&gt;</span><span class="w"> </span><span class="n">vmap</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">axes</span><span class="p">)</span><span class="w"> </span><span class="k">override</span><span class="p">;</span>
 
@@ -953,20 +944,20 @@ back and go to our example to give ourselves a more concrete image.</p>
 <span class="p">};</span>
 </pre></div>
 </div>
-<p>The <code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code> class derives from the base <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> class and
-follows the above demonstrated interface. <code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code> treats <code class="docutils literal notranslate"><span class="pre">alpha</span></code> and
-<code class="docutils literal notranslate"><span class="pre">beta</span></code> as parameters. It then provides implementations of how the array <code class="docutils literal notranslate"><span class="pre">out</span></code>
-is produced given <code class="docutils literal notranslate"><span class="pre">inputs</span></code> through <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_cpu()</span></code> and
-<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_gpu()</span></code>. Further, it provides rules of transformations in
-<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::jvp()</span></code>, <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::vjp()</span></code>, and <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::vmap()</span></code>.</p>
+<p>The <code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code> class derives from the base <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> class. The
+<code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code> treats <code class="docutils literal notranslate"><span class="pre">alpha</span></code> and <code class="docutils literal notranslate"><span class="pre">beta</span></code> as parameters. It then provides
+implementations of how the output array is produced given the inputs through
+<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_cpu()</span></code> and <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_gpu()</span></code>. It also provides rules
+of transformations in <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::jvp()</span></code>, <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::vjp()</span></code>, and
+<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::vmap()</span></code>.</p>
 </section>
-<section id="using-the-primitives">
-<h3>Using the Primitives<a class="headerlink" href="#using-the-primitives" title="Link to this heading">#</a></h3>
-<p>Operations can use this <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> to add a new <code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code> to
-the computation graph. An <code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code> can be constructed by providing its
-data type, shape, the <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> that computes it, and the
-<code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code> inputs that are passed to the primitive.</p>
-<p>Let’s re-implement our operation now in terms of our <code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code> primitive.</p>
+<section id="using-the-primitive">
+<h3>Using the Primitive<a class="headerlink" href="#using-the-primitive" title="Link to this heading">#</a></h3>
+<p>Operations can use this <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> to add a new <code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code> to the
+computation graph. An <code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code> can be constructed by providing its data
+type, shape, the <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code> that computes it, and the <code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code>
+inputs that are passed to the primitive.</p>
+<p>Let’s reimplement our operation now in terms of our <code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code> primitive.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="n">array</span><span class="w"> </span><span class="nf">axpby</span><span class="p">(</span>
 <span class="w">    </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">x</span><span class="p">,</span><span class="w"> </span><span class="c1">// Input array x</span>
 <span class="w">    </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">y</span><span class="p">,</span><span class="w"> </span><span class="c1">// Input array y</span>
@@ -1012,25 +1003,24 @@ data type, shape, the <code class="xref py py-class docutils literal notranslate
 </section>
 <section id="implementing-the-primitive">
 <h2>Implementing the Primitive<a class="headerlink" href="#implementing-the-primitive" title="Link to this heading">#</a></h2>
-<p>No computation happens when we call the operation alone. In effect, the
-operation only builds the computation graph. When we evaluate the output
-array, MLX schedules the execution of the computation graph, and calls
-<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_cpu()</span></code> or <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_gpu()</span></code> depending on the
-stream/device specified by the user.</p>
+<p>No computation happens when we call the operation alone. The operation only
+builds the computation graph. When we evaluate the output array, MLX schedules
+the execution of the computation graph, and calls <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_cpu()</span></code> or
+<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_gpu()</span></code> depending on the stream/device specified by the user.</p>
 <div class="admonition warning">
 <p class="admonition-title">Warning</p>
 <p>When <code class="xref py py-meth docutils literal notranslate"><span class="pre">Primitive::eval_cpu()</span></code> or <code class="xref py py-meth docutils literal notranslate"><span class="pre">Primitive::eval_gpu()</span></code> are called,
 no memory has been allocated for the output array. It falls on the implementation
-of these functions to allocate memory as needed</p>
+of these functions to allocate memory as needed.</p>
 </div>
-<section id="implementing-the-cpu-backend">
-<h3>Implementing the CPU Backend<a class="headerlink" href="#implementing-the-cpu-backend" title="Link to this heading">#</a></h3>
-<p>Let’s start by trying to implement a naive and generic version of
+<section id="implementing-the-cpu-back-end">
+<h3>Implementing the CPU Back-end<a class="headerlink" href="#implementing-the-cpu-back-end" title="Link to this heading">#</a></h3>
+<p>Let’s start by implementing a naive and generic version of
 <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_cpu()</span></code>. We declared this as a private member function of
 <code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code> earlier called <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval()</span></code>.</p>
 <p>Our naive method will go over each element of the output array, find the
 corresponding input elements of <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code> and perform the operation
-pointwise. This is captured in the templated function <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby_impl()</span></code>.</p>
+point-wise. This is captured in the templated function <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby_impl()</span></code>.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="k">template</span><span class="w"> </span><span class="o">&lt;</span><span class="k">typename</span><span class="w"> </span><span class="nc">T</span><span class="o">&gt;</span>
 <span class="kt">void</span><span class="w"> </span><span class="n">axpby_impl</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">x</span><span class="p">,</span>
@@ -1066,16 +1056,16 @@ pointwise. This is captured in the templated function <code class="xref py py-me
 <span class="p">}</span>
 </pre></div>
 </div>
-<p>Now, we would like our implementation to be able to do this pointwise operation
-for all incoming floating point arrays. Accordingly, we add dispatches for
-<code class="docutils literal notranslate"><span class="pre">float32</span></code>, <code class="docutils literal notranslate"><span class="pre">float16</span></code>, <code class="docutils literal notranslate"><span class="pre">bfloat16</span></code> and <code class="docutils literal notranslate"><span class="pre">complex64</span></code>. We throw an error
-if we encounter an unexpected type.</p>
+<p>Our implementation should work for all incoming floating point arrays.
+Accordingly, we add dispatches for <code class="docutils literal notranslate"><span class="pre">float32</span></code>, <code class="docutils literal notranslate"><span class="pre">float16</span></code>, <code class="docutils literal notranslate"><span class="pre">bfloat16</span></code> and
+<code class="docutils literal notranslate"><span class="pre">complex64</span></code>. We throw an error if we encounter an unexpected type.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cm">/** Fall back implementation for evaluation on CPU */</span>
-<span class="kt">void</span><span class="w"> </span><span class="nf">Axpby::eval</span><span class="p">(</span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
-<span class="w">    </span><span class="c1">// Check the inputs (registered in the op while constructing the out array)</span>
-<span class="w">    </span><span class="n">assert</span><span class="p">(</span><span class="n">inputs</span><span class="p">.</span><span class="n">size</span><span class="p">()</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mi">2</span><span class="p">);</span>
+<span class="kt">void</span><span class="w"> </span><span class="nf">Axpby::eval</span><span class="p">(</span>
+<span class="w">  </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span>
+<span class="w">  </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">outputs</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
 <span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">x</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">inputs</span><span class="p">[</span><span class="mi">0</span><span class="p">];</span>
 <span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">y</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">inputs</span><span class="p">[</span><span class="mi">1</span><span class="p">];</span>
+<span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">outputs</span><span class="p">[</span><span class="mi">0</span><span class="p">];</span>
 
 <span class="w">    </span><span class="c1">// Dispatch to the correct dtype</span>
 <span class="w">    </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">out</span><span class="p">.</span><span class="n">dtype</span><span class="p">()</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="n">float32</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
@@ -1088,29 +1078,27 @@ if we encounter an unexpected type.</p>
 <span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="n">axpby_impl</span><span class="o">&lt;</span><span class="n">complex64_t</span><span class="o">&gt;</span><span class="p">(</span><span class="n">x</span><span class="p">,</span><span class="w"> </span><span class="n">y</span><span class="p">,</span><span class="w"> </span><span class="n">out</span><span class="p">,</span><span class="w"> </span><span class="n">alpha_</span><span class="p">,</span><span class="w"> </span><span class="n">beta_</span><span class="p">);</span>
 <span class="w">    </span><span class="p">}</span><span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
 <span class="w">        </span><span class="k">throw</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">runtime_error</span><span class="p">(</span>
-<span class="w">            </span><span class="s">&quot;Axpby is only supported for floating point types.&quot;</span><span class="p">);</span>
+<span class="w">            </span><span class="s">&quot;[Axpby] Only supports floating point types.&quot;</span><span class="p">);</span>
 <span class="w">    </span><span class="p">}</span>
 <span class="p">}</span>
 </pre></div>
 </div>
-<p>We have a fallback implementation! Now, to do what we are really here to do.
-Remember we wanted to use the <code class="docutils literal notranslate"><span class="pre">axpby</span></code> routine provided by the <a class="reference external" href="https://developer.apple.com/documentation/accelerate/blas?language=objc">Accelerate</a>
-framework? Well, there are 3 complications to keep in mind:</p>
+<p>This is good as a fallback implementation. We can use the <code class="docutils literal notranslate"><span class="pre">axpby</span></code> routine
+provided by the <a class="reference external" href="https://developer.apple.com/documentation/accelerate/blas?language=objc">Accelerate</a> framework for a faster implementation in certain
+cases:</p>
 <ol class="arabic simple">
 <li><p>Accelerate does not provide implementations of <code class="docutils literal notranslate"><span class="pre">axpby</span></code> for half precision
-floats. We can only direct to it for <code class="docutils literal notranslate"><span class="pre">float32</span></code> types</p></li>
-<li><p>Accelerate assumes the inputs <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code> are contiguous and all elements
-have fixed strides between them. Possibly due to broadcasts and transposes,
-we aren’t guaranteed that the inputs fit this requirement. We can
-only direct to Accelerate if both <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code> are row contiguous or
-column contiguous.</p></li>
-<li><p>Accelerate performs the routine <code class="docutils literal notranslate"><span class="pre">Y</span> <span class="pre">=</span> <span class="pre">(alpha</span> <span class="pre">*</span> <span class="pre">X)</span> <span class="pre">+</span> <span class="pre">(beta</span> <span class="pre">*</span> <span class="pre">Y)</span></code> inplace.
-MLX expects to write out the answer to a new array. We must copy the elements
-of <code class="docutils literal notranslate"><span class="pre">y</span></code> into the output array and use that as an input to <code class="docutils literal notranslate"><span class="pre">axpby</span></code></p></li>
+floats. We can only use it for <code class="docutils literal notranslate"><span class="pre">float32</span></code> types.</p></li>
+<li><p>Accelerate assumes the inputs <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code> are contiguous and all
+elements have fixed strides between them. We only direct to Accelerate
+if both <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code> are row contiguous or column contiguous.</p></li>
+<li><p>Accelerate performs the routine <code class="docutils literal notranslate"><span class="pre">Y</span> <span class="pre">=</span> <span class="pre">(alpha</span> <span class="pre">*</span> <span class="pre">X)</span> <span class="pre">+</span> <span class="pre">(beta</span> <span class="pre">*</span> <span class="pre">Y)</span></code> in-place.
+MLX expects to write the output to a new array. We must copy the elements
+of <code class="docutils literal notranslate"><span class="pre">y</span></code> into the output and use that as an input to <code class="docutils literal notranslate"><span class="pre">axpby</span></code>.</p></li>
 </ol>
-<p>Let’s write out an implementation that uses Accelerate in the right conditions.
-It must simply allocate data for the output, copy elements of <code class="docutils literal notranslate"><span class="pre">y</span></code> into it,
-and then call the <code class="xref py py-meth docutils literal notranslate"><span class="pre">catlas_saxpby()</span></code> from accelerate.</p>
+<p>Let’s write an implementation that uses Accelerate in the right conditions.
+It allocates data for the output, copies <code class="docutils literal notranslate"><span class="pre">y</span></code> into it, and then calls the
+<code class="xref py py-func docutils literal notranslate"><span class="pre">catlas_saxpby()</span></code> from accelerate.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="k">template</span><span class="w"> </span><span class="o">&lt;</span><span class="k">typename</span><span class="w"> </span><span class="nc">T</span><span class="o">&gt;</span>
 <span class="kt">void</span><span class="w"> </span><span class="n">axpby_impl_accelerate</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">x</span><span class="p">,</span>
@@ -1121,17 +1109,7 @@ and then call the <code class="xref py py-meth docutils literal notranslate"><sp
 <span class="w">    </span><span class="c1">// Accelerate library provides catlas_saxpby which does</span>
 <span class="w">    </span><span class="c1">// Y = (alpha * X) + (beta * Y) in place</span>
 <span class="w">    </span><span class="c1">// To use it, we first copy the data in y over to the output array</span>
-
-<span class="w">    </span><span class="c1">// This specialization requires both x and y be contiguous in the same mode</span>
-<span class="w">    </span><span class="c1">// i.e: corresponding linear indices in both point to corresponding elements</span>
-<span class="w">    </span><span class="c1">// The data in the output array is allocated to match the strides in y</span>
-<span class="w">    </span><span class="c1">// such that x, y, and out are contiguous in the same mode and</span>
-<span class="w">    </span><span class="c1">// no transposition is needed</span>
-<span class="w">    </span><span class="n">out</span><span class="p">.</span><span class="n">set_data</span><span class="p">(</span>
-<span class="w">        </span><span class="n">allocator</span><span class="o">::</span><span class="n">malloc_or_wait</span><span class="p">(</span><span class="n">y</span><span class="p">.</span><span class="n">data_size</span><span class="p">()</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="n">out</span><span class="p">.</span><span class="n">itemsize</span><span class="p">()),</span>
-<span class="w">        </span><span class="n">y</span><span class="p">.</span><span class="n">data_size</span><span class="p">(),</span>
-<span class="w">        </span><span class="n">y</span><span class="p">.</span><span class="n">strides</span><span class="p">(),</span>
-<span class="w">        </span><span class="n">y</span><span class="p">.</span><span class="n">flags</span><span class="p">());</span>
+<span class="w">    </span><span class="n">out</span><span class="p">.</span><span class="n">set_data</span><span class="p">(</span><span class="n">allocator</span><span class="o">::</span><span class="n">malloc_or_wait</span><span class="p">(</span><span class="n">out</span><span class="p">.</span><span class="n">nbytes</span><span class="p">()));</span>
 
 <span class="w">    </span><span class="c1">// We then copy over the elements using the contiguous vector specialization</span>
 <span class="w">    </span><span class="n">copy_inplace</span><span class="p">(</span><span class="n">y</span><span class="p">,</span><span class="w"> </span><span class="n">out</span><span class="p">,</span><span class="w"> </span><span class="n">CopyType</span><span class="o">::</span><span class="n">Vector</span><span class="p">);</span>
@@ -1155,14 +1133,17 @@ and then call the <code class="xref py py-meth docutils literal notranslate"><sp
 <span class="p">}</span>
 </pre></div>
 </div>
-<p>Great! But what about the inputs that do not fit the criteria for accelerate?
-Luckily, we can always just direct back to <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval()</span></code>.</p>
-<p>With this in mind, lets finally implement our <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_cpu()</span></code>.</p>
+<p>For inputs that do not fit the criteria for accelerate, we fall back to
+<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval()</span></code>. With this in mind, let’s finish our
+<code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_cpu()</span></code>.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cm">/** Evaluate primitive on CPU using accelerate specializations */</span>
-<span class="kt">void</span><span class="w"> </span><span class="nf">Axpby::eval_cpu</span><span class="p">(</span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="kt">void</span><span class="w"> </span><span class="nf">Axpby::eval_cpu</span><span class="p">(</span>
+<span class="w">  </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span>
+<span class="w">  </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">outputs</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
 <span class="w">    </span><span class="n">assert</span><span class="p">(</span><span class="n">inputs</span><span class="p">.</span><span class="n">size</span><span class="p">()</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mi">2</span><span class="p">);</span>
 <span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">x</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">inputs</span><span class="p">[</span><span class="mi">0</span><span class="p">];</span>
 <span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">y</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">inputs</span><span class="p">[</span><span class="mi">1</span><span class="p">];</span>
+<span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">outputs</span><span class="p">[</span><span class="mi">0</span><span class="p">];</span>
 
 <span class="w">    </span><span class="c1">// Accelerate specialization for contiguous single precision float arrays</span>
 <span class="w">    </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">out</span><span class="p">.</span><span class="n">dtype</span><span class="p">()</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="n">float32</span><span class="w"> </span><span class="o">&amp;&amp;</span>
@@ -1172,33 +1153,32 @@ Luckily, we can always just direct back to <code class="xref py py-meth docutils
 <span class="w">        </span><span class="k">return</span><span class="p">;</span>
 <span class="w">    </span><span class="p">}</span>
 
-<span class="w">    </span><span class="c1">// Fall back to common backend if specializations are not available</span>
-<span class="w">    </span><span class="n">eval</span><span class="p">(</span><span class="n">inputs</span><span class="p">,</span><span class="w"> </span><span class="n">out</span><span class="p">);</span>
+<span class="w">    </span><span class="c1">// Fall back to common back-end if specializations are not available</span>
+<span class="w">    </span><span class="n">eval</span><span class="p">(</span><span class="n">inputs</span><span class="p">,</span><span class="w"> </span><span class="n">outputs</span><span class="p">);</span>
 <span class="p">}</span>
 </pre></div>
 </div>
-<p>We have now hit a milestone! Just this much is enough to run the operation
-<code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby()</span></code> on a CPU stream!</p>
-<p>If you do not plan on running the operation on the GPU or using transforms on
+<p>Just this much is enough to run the operation <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby()</span></code> on a CPU stream! If
+you do not plan on running the operation on the GPU or using transforms on
 computation graphs that contain <code class="xref py py-class docutils literal notranslate"><span class="pre">Axpby</span></code>, you can stop implementing the
 primitive here and enjoy the speed-ups you get from the Accelerate library.</p>
 </section>
-<section id="implementing-the-gpu-backend">
-<h3>Implementing the GPU Backend<a class="headerlink" href="#implementing-the-gpu-backend" title="Link to this heading">#</a></h3>
+<section id="implementing-the-gpu-back-end">
+<h3>Implementing the GPU Back-end<a class="headerlink" href="#implementing-the-gpu-back-end" title="Link to this heading">#</a></h3>
 <p>Apple silicon devices address their GPUs using the <a class="reference external" href="https://developer.apple.com/documentation/metal?language=objc">Metal</a> shading language, and
-all GPU kernels in MLX are written using metal.</p>
+GPU kernels in MLX are written using Metal.</p>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>Here are some helpful resources if you are new to metal!</p>
+<p>Here are some helpful resources if you are new to Metal:</p>
 <ul class="simple">
 <li><p>A walkthrough of the metal compute pipeline: <a class="reference external" href="https://developer.apple.com/documentation/metal/performing_calculations_on_a_gpu?language=objc">Metal Example</a></p></li>
 <li><p>Documentation for metal shading language: <a class="reference external" href="https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf">Metal Specification</a></p></li>
 <li><p>Using metal from C++: <a class="reference external" href="https://developer.apple.com/metal/cpp/">Metal-cpp</a></p></li>
 </ul>
 </div>
-<p>Let’s keep the GPU algorithm simple. We will launch exactly as many threads
-as there are elements in the output. Each thread will pick the element it needs
-from <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code>, do the pointwise operation, and then update its assigned
+<p>Let’s keep the GPU kernel simple. We will launch exactly as many threads as
+there are elements in the output. Each thread will pick the element it needs
+from <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code>, do the point-wise operation, and update its assigned
 element in the output.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="k">template</span><span class="w"> </span><span class="o">&lt;</span><span class="k">typename</span><span class="w"> </span><span class="nc">T</span><span class="o">&gt;</span>
 <span class="p">[[</span><span class="n">kernel</span><span class="p">]]</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="n">axpby_general</span><span class="p">(</span>
@@ -1223,8 +1203,7 @@ element in the output.</p>
 </pre></div>
 </div>
 <p>We then need to instantiate this template for all floating point types and give
-each instantiation a unique host name so we can identify the right kernel for
-each data type.</p>
+each instantiation a unique host name so we can identify it.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cp">#define instantiate_axpby(type_name, type)              \</span>
 <span class="cp">    template [[host_name(&quot;axpby_general_&quot; #type_name)]] \</span>
 <span class="cp">    [[kernel]] void axpby_general&lt;type&gt;(                \</span>
@@ -1245,25 +1224,18 @@ each data type.</p>
 <span class="n">instantiate_axpby</span><span class="p">(</span><span class="n">complex64</span><span class="p">,</span><span class="w"> </span><span class="n">complex64_t</span><span class="p">);</span>
 </pre></div>
 </div>
-<p>This kernel will be compiled into a metal library <code class="docutils literal notranslate"><span class="pre">mlx_ext.metallib</span></code> as we
-will see later in <a class="reference internal" href="#building-with-cmake"><span class="std std-ref">Building with CMake</span></a>. In the following example, we
-assume that the library <code class="docutils literal notranslate"><span class="pre">mlx_ext.metallib</span></code> will always be co-located with
-the executable/ shared-library calling the <code class="xref py py-meth docutils literal notranslate"><span class="pre">register_library()</span></code> function.
-The <code class="xref py py-meth docutils literal notranslate"><span class="pre">register_library()</span></code> function takes the library’s name and potential
-path (or in this case, a function that can produce the path of the metal
-library) and tries to load that library if it hasn’t already been registered
-by the relevant static <code class="xref py py-class docutils literal notranslate"><span class="pre">mlx::core::metal::Device</span></code> object. This is why,
-it is important to package your C++ library with the metal library. We will
-go over this process in more detail later.</p>
-<p>The logic to determine the kernel, set the inputs, resolve the grid dimensions
-and dispatch it to the GPU are contained in <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_gpu()</span></code> as shown
+<p>The logic to determine the kernel, set the inputs, resolve the grid dimensions,
+and dispatch to the GPU are contained in <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::eval_gpu()</span></code> as shown
 below.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cm">/** Evaluate primitive on GPU */</span>
-<span class="kt">void</span><span class="w"> </span><span class="nf">Axpby::eval_gpu</span><span class="p">(</span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="kt">void</span><span class="w"> </span><span class="nf">Axpby::eval_gpu</span><span class="p">(</span>
+<span class="w">  </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span>
+<span class="w">  </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">outputs</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
 <span class="w">    </span><span class="c1">// Prepare inputs</span>
 <span class="w">    </span><span class="n">assert</span><span class="p">(</span><span class="n">inputs</span><span class="p">.</span><span class="n">size</span><span class="p">()</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mi">2</span><span class="p">);</span>
 <span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">x</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">inputs</span><span class="p">[</span><span class="mi">0</span><span class="p">];</span>
 <span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">y</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">inputs</span><span class="p">[</span><span class="mi">1</span><span class="p">];</span>
+<span class="w">    </span><span class="k">auto</span><span class="o">&amp;</span><span class="w"> </span><span class="n">out</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">outputs</span><span class="p">[</span><span class="mi">0</span><span class="p">];</span>
 
 <span class="w">    </span><span class="c1">// Each primitive carries the stream it should execute on</span>
 <span class="w">    </span><span class="c1">// and each stream carries its device identifiers</span>
@@ -1274,7 +1246,7 @@ below.</p>
 <span class="w">    </span><span class="c1">// Allocate output memory</span>
 <span class="w">    </span><span class="n">out</span><span class="p">.</span><span class="n">set_data</span><span class="p">(</span><span class="n">allocator</span><span class="o">::</span><span class="n">malloc_or_wait</span><span class="p">(</span><span class="n">out</span><span class="p">.</span><span class="n">nbytes</span><span class="p">()));</span>
 
-<span class="w">    </span><span class="c1">// Resolve name of kernel (corresponds to axpby.metal)</span>
+<span class="w">    </span><span class="c1">// Resolve name of kernel</span>
 <span class="w">    </span><span class="n">std</span><span class="o">::</span><span class="n">ostringstream</span><span class="w"> </span><span class="n">kname</span><span class="p">;</span>
 <span class="w">    </span><span class="n">kname</span><span class="w"> </span><span class="o">&lt;&lt;</span><span class="w"> </span><span class="s">&quot;axpby_&quot;</span><span class="w"> </span><span class="o">&lt;&lt;</span><span class="w"> </span><span class="s">&quot;general_&quot;</span><span class="w"> </span><span class="o">&lt;&lt;</span><span class="w"> </span><span class="n">type_to_name</span><span class="p">(</span><span class="n">out</span><span class="p">);</span>
 
@@ -1328,24 +1300,21 @@ below.</p>
 </pre></div>
 </div>
 <p>We can now call the <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby()</span></code> operation on both the CPU and the GPU!</p>
-<p>A few things to note about MLX and metal before moving on. MLX keeps track
-of the active <code class="docutils literal notranslate"><span class="pre">compute_encoder</span></code>. We rely on <code class="xref py py-meth docutils literal notranslate"><span class="pre">d.get_command_encoder()</span></code>
-to give us the active metal compute command encoder instead of building a
-new one and calling <code class="xref py py-meth docutils literal notranslate"><span class="pre">compute_encoder-&gt;end_encoding()</span></code> at the end.
-MLX keeps adding kernels (compute pipelines) to the active command encoder
-until some specified limit is hit or the compute encoder needs to be flushed
-for synchronization. MLX also handles enqueuing and committing the associated
-command buffers as needed. We suggest taking a deeper dive into
-<code class="xref py py-class docutils literal notranslate"><span class="pre">metal::Device</span></code> if you would like to study this routine further.</p>
+<p>A few things to note about MLX and Metal before moving on. MLX keeps track of
+the active <code class="docutils literal notranslate"><span class="pre">command_buffer</span></code> and the <code class="docutils literal notranslate"><span class="pre">MTLCommandBuffer</span></code> to which it is
+associated. We rely on <code class="xref py py-meth docutils literal notranslate"><span class="pre">d.get_command_encoder()</span></code> to give us the active
+metal compute command encoder instead of building a new one and calling
+<code class="xref py py-meth docutils literal notranslate"><span class="pre">compute_encoder-&gt;end_encoding()</span></code> at the end. MLX adds kernels (compute
+pipelines) to the active command buffer until some specified limit is hit or
+the command buffer needs to be flushed for synchronization.</p>
 </section>
 <section id="primitive-transforms">
 <h3>Primitive Transforms<a class="headerlink" href="#primitive-transforms" title="Link to this heading">#</a></h3>
-<p>Now that we have come this far, let’s also learn how to add implementations to
-transformations in a <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code>. These transformations can be built on
-top of our operations, including the one we just defined now. Which then gives
-us the following <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::jvp()</span></code> and <code class="xref py py-meth docutils literal notranslate"><span class="pre">Axpby::vjp()</span></code> implementations.</p>
+<p>Next, let’s add implementations for transformations in a <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code>.
+These transformations can be built on top of other operations, including the
+one we just defined:</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cm">/** The Jacobian-vector product. */</span>
-<span class="n">array</span><span class="w"> </span><span class="nf">Axpby::jvp</span><span class="p">(</span>
+<span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;</span><span class="w"> </span><span class="n">Axpby</span><span class="o">::</span><span class="n">jvp</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">primals</span><span class="p">,</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">tangents</span><span class="p">,</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">argnums</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
@@ -1360,12 +1329,12 @@ us the following <code class="xref py py-meth docutils literal notranslate"><spa
 <span class="w">    </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">argnums</span><span class="p">.</span><span class="n">size</span><span class="p">()</span><span class="w"> </span><span class="o">&gt;</span><span class="w"> </span><span class="mi">1</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
 <span class="w">        </span><span class="k">auto</span><span class="w"> </span><span class="n">scale</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">argnums</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mi">0</span><span class="w"> </span><span class="o">?</span><span class="w"> </span><span class="n">alpha_</span><span class="w"> </span><span class="o">:</span><span class="w"> </span><span class="n">beta_</span><span class="p">;</span>
 <span class="w">        </span><span class="k">auto</span><span class="w"> </span><span class="n">scale_arr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">array</span><span class="p">(</span><span class="n">scale</span><span class="p">,</span><span class="w"> </span><span class="n">tangents</span><span class="p">[</span><span class="mi">0</span><span class="p">].</span><span class="n">dtype</span><span class="p">());</span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="n">multiply</span><span class="p">(</span><span class="n">scale_arr</span><span class="p">,</span><span class="w"> </span><span class="n">tangents</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span><span class="w"> </span><span class="n">stream</span><span class="p">());</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="p">{</span><span class="n">multiply</span><span class="p">(</span><span class="n">scale_arr</span><span class="p">,</span><span class="w"> </span><span class="n">tangents</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span><span class="w"> </span><span class="n">stream</span><span class="p">())};</span>
 <span class="w">    </span><span class="p">}</span>
 <span class="w">    </span><span class="c1">// If, argnums = {0, 1}, we take contributions from both</span>
 <span class="w">    </span><span class="c1">// which gives us jvp = tangent_x * alpha + tangent_y * beta</span>
 <span class="w">    </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
-<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="n">axpby</span><span class="p">(</span><span class="n">tangents</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span><span class="w"> </span><span class="n">tangents</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="w"> </span><span class="n">alpha_</span><span class="p">,</span><span class="w"> </span><span class="n">beta_</span><span class="p">,</span><span class="w"> </span><span class="n">stream</span><span class="p">());</span>
+<span class="w">        </span><span class="k">return</span><span class="w"> </span><span class="p">{</span><span class="n">axpby</span><span class="p">(</span><span class="n">tangents</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span><span class="w"> </span><span class="n">tangents</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span><span class="w"> </span><span class="n">alpha_</span><span class="p">,</span><span class="w"> </span><span class="n">beta_</span><span class="p">,</span><span class="w"> </span><span class="n">stream</span><span class="p">())};</span>
 <span class="w">    </span><span class="p">}</span>
 <span class="p">}</span>
 </pre></div>
@@ -1373,26 +1342,27 @@ us the following <code class="xref py py-meth docutils literal notranslate"><spa
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cm">/** The vector-Jacobian product. */</span>
 <span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;</span><span class="w"> </span><span class="n">Axpby</span><span class="o">::</span><span class="n">vjp</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">primals</span><span class="p">,</span>
-<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">array</span><span class="o">&amp;</span><span class="w"> </span><span class="n">cotan</span><span class="p">,</span>
-<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">argnums</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">cotangents</span><span class="p">,</span>
+<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">argnums</span><span class="p">,</span>
+<span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="cm">/* unused */</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
 <span class="w">    </span><span class="c1">// Reverse mode diff</span>
 <span class="w">    </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;</span><span class="w"> </span><span class="n">vjps</span><span class="p">;</span>
 <span class="w">    </span><span class="k">for</span><span class="w"> </span><span class="p">(</span><span class="k">auto</span><span class="w"> </span><span class="n">arg</span><span class="w"> </span><span class="o">:</span><span class="w"> </span><span class="n">argnums</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
 <span class="w">        </span><span class="k">auto</span><span class="w"> </span><span class="n">scale</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">arg</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="mi">0</span><span class="w"> </span><span class="o">?</span><span class="w"> </span><span class="n">alpha_</span><span class="w"> </span><span class="o">:</span><span class="w"> </span><span class="n">beta_</span><span class="p">;</span>
-<span class="w">        </span><span class="k">auto</span><span class="w"> </span><span class="n">scale_arr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">array</span><span class="p">(</span><span class="n">scale</span><span class="p">,</span><span class="w"> </span><span class="n">cotan</span><span class="p">.</span><span class="n">dtype</span><span class="p">());</span>
-<span class="w">        </span><span class="n">vjps</span><span class="p">.</span><span class="n">push_back</span><span class="p">(</span><span class="n">multiply</span><span class="p">(</span><span class="n">scale_arr</span><span class="p">,</span><span class="w"> </span><span class="n">cotan</span><span class="p">,</span><span class="w"> </span><span class="n">stream</span><span class="p">()));</span>
+<span class="w">        </span><span class="k">auto</span><span class="w"> </span><span class="n">scale_arr</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">array</span><span class="p">(</span><span class="n">scale</span><span class="p">,</span><span class="w"> </span><span class="n">cotangents</span><span class="p">[</span><span class="mi">0</span><span class="p">].</span><span class="n">dtype</span><span class="p">());</span>
+<span class="w">        </span><span class="n">vjps</span><span class="p">.</span><span class="n">push_back</span><span class="p">(</span><span class="n">multiply</span><span class="p">(</span><span class="n">scale_arr</span><span class="p">,</span><span class="w"> </span><span class="n">cotangents</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span><span class="w"> </span><span class="n">stream</span><span class="p">()));</span>
 <span class="w">    </span><span class="p">}</span>
 <span class="w">    </span><span class="k">return</span><span class="w"> </span><span class="n">vjps</span><span class="p">;</span>
 <span class="p">}</span>
 </pre></div>
 </div>
-<p>Finally, you need not have a transformation fully defined to start using your
-own <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code>.</p>
+<p>Note, a transformation does not need to be fully defined to start using
+the <code class="xref py py-class docutils literal notranslate"><span class="pre">Primitive</span></code>.</p>
 <div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="cm">/** Vectorize primitive along given axis */</span>
-<span class="n">std</span><span class="o">::</span><span class="n">pair</span><span class="o">&lt;</span><span class="n">array</span><span class="p">,</span><span class="w"> </span><span class="kt">int</span><span class="o">&gt;</span><span class="w"> </span><span class="n">Axpby</span><span class="o">::</span><span class="n">vmap</span><span class="p">(</span>
+<span class="n">std</span><span class="o">::</span><span class="n">pair</span><span class="o">&lt;</span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;</span><span class="p">,</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&gt;</span><span class="w"> </span><span class="n">Axpby</span><span class="o">::</span><span class="n">vmap</span><span class="p">(</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="n">array</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">inputs</span><span class="p">,</span>
 <span class="w">        </span><span class="k">const</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">vector</span><span class="o">&lt;</span><span class="kt">int</span><span class="o">&gt;&amp;</span><span class="w"> </span><span class="n">axes</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
-<span class="w">    </span><span class="k">throw</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">runtime_error</span><span class="p">(</span><span class="s">&quot;Axpby has no vmap implementation.&quot;</span><span class="p">);</span>
+<span class="w">    </span><span class="k">throw</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">runtime_error</span><span class="p">(</span><span class="s">&quot;[Axpby] vmap not implemented.&quot;</span><span class="p">);</span>
 <span class="p">}</span>
 </pre></div>
 </div>
@@ -1416,64 +1386,63 @@ own <code class="xref py py-class docutils literal notranslate"><span class="pre
 <ul class="simple">
 <li><p><code class="docutils literal notranslate"><span class="pre">extensions/axpby/</span></code> defines the C++ extension library</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">extensions/mlx_sample_extensions</span></code> sets out the structure for the
-associated python package</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">extensions/bindings.cpp</span></code> provides python bindings for our operation</p></li>
+associated Python package</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">extensions/bindings.cpp</span></code> provides Python bindings for our operation</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">extensions/CMakeLists.txt</span></code> holds CMake rules to build the library and
-python bindings</p></li>
+Python bindings</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">extensions/setup.py</span></code> holds the <code class="docutils literal notranslate"><span class="pre">setuptools</span></code> rules to build and install
-the python package</p></li>
+the Python package</p></li>
 </ul>
 <section id="binding-to-python">
 <h3>Binding to Python<a class="headerlink" href="#binding-to-python" title="Link to this heading">#</a></h3>
-<p>We use <a class="reference external" href="https://pybind11.readthedocs.io/en/stable/">PyBind11</a> to build a Python API for the C++ library. Since bindings for
+<p>We use <a class="reference external" href="https://nanobind.readthedocs.io/en/latest/">nanobind</a> to build a Python API for the C++ library. Since bindings for
 components such as <a class="reference internal" href="../python/_autosummary/mlx.core.array.html#mlx.core.array" title="mlx.core.array"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.core.array</span></code></a>, <a class="reference internal" href="../python/_autosummary/mlx.core.stream.html#mlx.core.stream" title="mlx.core.stream"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.core.stream</span></code></a>, etc. are
-already provided, adding our <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby()</span></code> is simple!</p>
-<div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="n">PYBIND11_MODULE</span><span class="p">(</span><span class="n">mlx_sample_extensions</span><span class="p">,</span><span class="w"> </span><span class="n">m</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
-<span class="w">    </span><span class="n">m</span><span class="p">.</span><span class="n">doc</span><span class="p">()</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s">&quot;Sample C++ and metal extensions for MLX&quot;</span><span class="p">;</span>
+already provided, adding our <code class="xref py py-meth docutils literal notranslate"><span class="pre">axpby()</span></code> is simple.</p>
+<div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="n">NB_MODULE</span><span class="p">(</span><span class="n">_ext</span><span class="p">,</span><span class="w"> </span><span class="n">m</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
+<span class="w">     </span><span class="n">m</span><span class="p">.</span><span class="n">doc</span><span class="p">()</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s">&quot;Sample extension for MLX&quot;</span><span class="p">;</span>
 
-<span class="w">    </span><span class="n">m</span><span class="p">.</span><span class="n">def</span><span class="p">(</span>
-<span class="w">        </span><span class="s">&quot;axpby&quot;</span><span class="p">,</span>
-<span class="w">        </span><span class="o">&amp;</span><span class="n">axpby</span><span class="p">,</span>
-<span class="w">        </span><span class="s">&quot;x&quot;</span><span class="n">_a</span><span class="p">,</span>
-<span class="w">        </span><span class="s">&quot;y&quot;</span><span class="n">_a</span><span class="p">,</span>
-<span class="w">        </span><span class="n">py</span><span class="o">::</span><span class="n">pos_only</span><span class="p">(),</span>
-<span class="w">        </span><span class="s">&quot;alpha&quot;</span><span class="n">_a</span><span class="p">,</span>
-<span class="w">        </span><span class="s">&quot;beta&quot;</span><span class="n">_a</span><span class="p">,</span>
-<span class="w">        </span><span class="n">py</span><span class="o">::</span><span class="n">kw_only</span><span class="p">(),</span>
-<span class="w">        </span><span class="s">&quot;stream&quot;</span><span class="n">_a</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">py</span><span class="o">::</span><span class="n">none</span><span class="p">(),</span>
-<span class="w">        </span><span class="sa">R</span><span class="s">&quot;</span><span class="dl">pbdoc(</span>
-<span class="s">            Scale and sum two vectors element-wise</span>
-<span class="s">            ``z = alpha * x + beta * y``</span>
+<span class="w">     </span><span class="n">m</span><span class="p">.</span><span class="n">def</span><span class="p">(</span>
+<span class="w">         </span><span class="s">&quot;axpby&quot;</span><span class="p">,</span>
+<span class="w">         </span><span class="o">&amp;</span><span class="n">axpby</span><span class="p">,</span>
+<span class="w">         </span><span class="s">&quot;x&quot;</span><span class="n">_a</span><span class="p">,</span>
+<span class="w">         </span><span class="s">&quot;y&quot;</span><span class="n">_a</span><span class="p">,</span>
+<span class="w">         </span><span class="s">&quot;alpha&quot;</span><span class="n">_a</span><span class="p">,</span>
+<span class="w">         </span><span class="s">&quot;beta&quot;</span><span class="n">_a</span><span class="p">,</span>
+<span class="w">         </span><span class="n">nb</span><span class="o">::</span><span class="n">kw_only</span><span class="p">(),</span>
+<span class="w">         </span><span class="s">&quot;stream&quot;</span><span class="n">_a</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">nb</span><span class="o">::</span><span class="n">none</span><span class="p">(),</span>
+<span class="w">         </span><span class="sa">R</span><span class="s">&quot;</span><span class="dl">(</span>
+<span class="s">             Scale and sum two vectors element-wise</span>
+<span class="s">             ``z = alpha * x + beta * y``</span>
 
-<span class="s">            Follows numpy style broadcasting between ``x`` and ``y``</span>
-<span class="s">            Inputs are upcasted to floats if needed</span>
+<span class="s">             Follows numpy style broadcasting between ``x`` and ``y``</span>
+<span class="s">             Inputs are upcasted to floats if needed</span>
 
-<span class="s">            Args:</span>
-<span class="s">                x (array): Input array.</span>
-<span class="s">                y (array): Input array.</span>
-<span class="s">                alpha (float): Scaling factor for ``x``.</span>
-<span class="s">                beta (float): Scaling factor for ``y``.</span>
+<span class="s">             Args:</span>
+<span class="s">                 x (array): Input array.</span>
+<span class="s">                 y (array): Input array.</span>
+<span class="s">                 alpha (float): Scaling factor for ``x``.</span>
+<span class="s">                 beta (float): Scaling factor for ``y``.</span>
 
-<span class="s">            Returns:</span>
-<span class="s">                array: ``alpha * x + beta * y``</span>
-<span class="s">        </span><span class="dl">)pbdoc</span><span class="s">&quot;</span><span class="p">);</span>
-<span class="p">}</span>
+<span class="s">             Returns:</span>
+<span class="s">                 array: ``alpha * x + beta * y``</span>
+<span class="s">         </span><span class="dl">)</span><span class="s">&quot;</span><span class="p">);</span>
+<span class="w"> </span><span class="p">}</span>
 </pre></div>
 </div>
 <p>Most of the complexity in the above example comes from additional bells and
 whistles such as the literal names and doc-strings.</p>
 <div class="admonition warning">
 <p class="admonition-title">Warning</p>
-<p><code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.core</span></code> needs to be imported before importing
-<code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx_sample_extensions</span></code> as defined by the pybind11 module above to
+<p><code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.core</span></code> must be imported before importing
+<code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx_sample_extensions</span></code> as defined by the nanobind module above to
 ensure that the casters for <code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.core</span></code> components like
 <a class="reference internal" href="../python/_autosummary/mlx.core.array.html#mlx.core.array" title="mlx.core.array"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.core.array</span></code></a> are available.</p>
 </div>
 </section>
 <section id="building-with-cmake">
 <span id="id1"></span><h3>Building with CMake<a class="headerlink" href="#building-with-cmake" title="Link to this heading">#</a></h3>
-<p>Building the C++ extension library itself is simple, it only requires that you
-<code class="docutils literal notranslate"><span class="pre">find_package(MLX</span> <span class="pre">CONFIG)</span></code> and then link it to your library.</p>
+<p>Building the C++ extension library only requires that you <code class="docutils literal notranslate"><span class="pre">find_package(MLX</span>
+<span class="pre">CONFIG)</span></code> and then link it to your library.</p>
 <div class="highlight-cmake notranslate"><div class="highlight"><pre><span></span><span class="c"># Add library</span>
 <span class="nb">add_library</span><span class="p">(</span><span class="s">mlx_ext</span><span class="p">)</span>
 
@@ -1493,11 +1462,11 @@ ensure that the casters for <code class="xref py py-mod docutils literal notrans
 <span class="nb">target_link_libraries</span><span class="p">(</span><span class="s">mlx_ext</span><span class="w"> </span><span class="s">PUBLIC</span><span class="w"> </span><span class="s">mlx</span><span class="p">)</span>
 </pre></div>
 </div>
-<p>We also need to build the attached metal library. For convenience, we provide a
+<p>We also need to build the attached Metal library. For convenience, we provide a
 <code class="xref py py-meth docutils literal notranslate"><span class="pre">mlx_build_metallib()</span></code> function that builds a <code class="docutils literal notranslate"><span class="pre">.metallib</span></code> target given
 sources, headers, destinations, etc. (defined in <code class="docutils literal notranslate"><span class="pre">cmake/extension.cmake</span></code> and
 automatically imported with MLX package).</p>
-<p>Here is what that looks like in practice!</p>
+<p>Here is what that looks like in practice:</p>
 <div class="highlight-cmake notranslate"><div class="highlight"><pre><span></span><span class="c"># Build metallib</span>
 <span class="nb">if</span><span class="p">(</span><span class="s">MLX_BUILD_METAL</span><span class="p">)</span>
 
@@ -1517,15 +1486,17 @@ automatically imported with MLX package).</p>
 <span class="nb">endif</span><span class="p">()</span>
 </pre></div>
 </div>
-<p>Finally, we build the <a class="reference external" href="https://pybind11.readthedocs.io/en/stable/">Pybind11</a> bindings</p>
-<div class="highlight-cmake notranslate"><div class="highlight"><pre><span></span><span class="nb">pybind11_add_module</span><span class="p">(</span>
-<span class="w">    </span><span class="s">mlx_sample_extensions</span>
-<span class="w">    </span><span class="o">${</span><span class="nv">CMAKE_CURRENT_LIST_DIR</span><span class="o">}</span><span class="s">/bindings.cpp</span>
+<p>Finally, we build the <a class="reference external" href="https://nanobind.readthedocs.io/en/latest/">nanobind</a> bindings</p>
+<div class="highlight-cmake notranslate"><div class="highlight"><pre><span></span><span class="nb">nanobind_add_module</span><span class="p">(</span>
+<span class="w">  </span><span class="s">_ext</span>
+<span class="w">  </span><span class="s">NB_STATIC</span><span class="w"> </span><span class="s">STABLE_ABI</span><span class="w"> </span><span class="s">LTO</span><span class="w"> </span><span class="s">NOMINSIZE</span>
+<span class="w">  </span><span class="s">NB_DOMAIN</span><span class="w"> </span><span class="s">mlx</span>
+<span class="w">  </span><span class="o">${</span><span class="nv">CMAKE_CURRENT_LIST_DIR</span><span class="o">}</span><span class="s">/bindings.cpp</span>
 <span class="p">)</span>
-<span class="nb">target_link_libraries</span><span class="p">(</span><span class="s">mlx_sample_extensions</span><span class="w"> </span><span class="s">PRIVATE</span><span class="w"> </span><span class="s">mlx_ext</span><span class="p">)</span>
+<span class="nb">target_link_libraries</span><span class="p">(</span><span class="s">_ext</span><span class="w"> </span><span class="s">PRIVATE</span><span class="w"> </span><span class="s">mlx_ext</span><span class="p">)</span>
 
 <span class="nb">if</span><span class="p">(</span><span class="s">BUILD_SHARED_LIBS</span><span class="p">)</span>
-<span class="w">    </span><span class="nb">target_link_options</span><span class="p">(</span><span class="s">mlx_sample_extensions</span><span class="w"> </span><span class="s">PRIVATE</span><span class="w"> </span><span class="s">-Wl,-rpath,@loader_path</span><span class="p">)</span>
+<span class="w">  </span><span class="nb">target_link_options</span><span class="p">(</span><span class="s">_ext</span><span class="w"> </span><span class="s">PRIVATE</span><span class="w"> </span><span class="s">-Wl,-rpath,@loader_path</span><span class="p">)</span>
 <span class="nb">endif</span><span class="p">()</span>
 </pre></div>
 </div>
@@ -1533,7 +1504,7 @@ automatically imported with MLX package).</p>
 <section id="building-with-setuptools">
 <h3>Building with <code class="docutils literal notranslate"><span class="pre">setuptools</span></code><a class="headerlink" href="#building-with-setuptools" title="Link to this heading">#</a></h3>
 <p>Once we have set out the CMake build rules as described above, we can use the
-build utilities defined in <code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.extension</span></code> for a simple build process.</p>
+build utilities defined in <code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.extension</span></code>:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">mlx</span> <span class="kn">import</span> <span class="n">extension</span>
 <span class="kn">from</span> <span class="nn">setuptools</span> <span class="kn">import</span> <span class="n">setup</span>
 
@@ -1542,13 +1513,13 @@ build utilities defined in <code class="xref py py-mod docutils literal notransl
         <span class="n">name</span><span class="o">=</span><span class="s2">&quot;mlx_sample_extensions&quot;</span><span class="p">,</span>
         <span class="n">version</span><span class="o">=</span><span class="s2">&quot;0.0.0&quot;</span><span class="p">,</span>
         <span class="n">description</span><span class="o">=</span><span class="s2">&quot;Sample C++ and Metal extensions for MLX primitives.&quot;</span><span class="p">,</span>
-        <span class="n">ext_modules</span><span class="o">=</span><span class="p">[</span><span class="n">extension</span><span class="o">.</span><span class="n">CMakeExtension</span><span class="p">(</span><span class="s2">&quot;mlx_sample_extensions&quot;</span><span class="p">)],</span>
+        <span class="n">ext_modules</span><span class="o">=</span><span class="p">[</span><span class="n">extension</span><span class="o">.</span><span class="n">CMakeExtension</span><span class="p">(</span><span class="s2">&quot;mlx_sample_extensions._ext&quot;</span><span class="p">)],</span>
         <span class="n">cmdclass</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;build_ext&quot;</span><span class="p">:</span> <span class="n">extension</span><span class="o">.</span><span class="n">CMakeBuild</span><span class="p">},</span>
-        <span class="n">packages</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;mlx_sample_extensions&quot;</span><span class="p">],</span>
-        <span class="n">package_dir</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;&quot;</span><span class="p">:</span> <span class="s2">&quot;mlx_sample_extensions&quot;</span><span class="p">},</span>
-        <span class="n">package_data</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;mlx_sample_extensions&quot;</span> <span class="p">:</span> <span class="p">[</span><span class="s2">&quot;*.so&quot;</span><span class="p">,</span> <span class="s2">&quot;*.dylib&quot;</span><span class="p">,</span> <span class="s2">&quot;*.metallib&quot;</span><span class="p">]},</span>
+        <span class="n">packages</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;mlx_sample_extensions&quot;</span><span class="p">],</span>
+        <span class="n">package_data</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;mlx_sample_extensions&quot;</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;*.so&quot;</span><span class="p">,</span> <span class="s2">&quot;*.dylib&quot;</span><span class="p">,</span> <span class="s2">&quot;*.metallib&quot;</span><span class="p">]},</span>
+        <span class="n">extras_require</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;dev&quot;</span><span class="p">:[]},</span>
         <span class="n">zip_safe</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
-        <span class="n">python_requires</span><span class="o">=</span><span class="s2">&quot;&gt;=3.7&quot;</span><span class="p">,</span>
+        <span class="n">python_requires</span><span class="o">=</span><span class="s2">&quot;&gt;=3.8&quot;</span><span class="p">,</span>
     <span class="p">)</span>
 </pre></div>
 </div>
@@ -1557,34 +1528,36 @@ build utilities defined in <code class="xref py py-mod docutils literal notransl
 <p>We treat <code class="docutils literal notranslate"><span class="pre">extensions/mlx_sample_extensions</span></code> as the package directory
 even though it only contains a <code class="docutils literal notranslate"><span class="pre">__init__.py</span></code> to ensure the following:</p>
 <ul class="simple">
-<li><p><code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.core</span></code> is always imported before importing  <code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx_sample_extensions</span></code></p></li>
+<li><p><code class="xref py py-mod docutils literal notranslate"><span class="pre">mlx.core</span></code> must be imported before importing <code class="xref py py-mod docutils literal notranslate"><span class="pre">_ext</span></code></p></li>
 <li><p>The C++ extension library and the metal library are co-located with the python
 bindings and copied together if the package is installed</p></li>
 </ul>
 </div>
-<p>You can build inplace for development using
+<p>To build the package, first install the build dependencies with <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span>
+<span class="pre">-r</span> <span class="pre">requirements.txt</span></code>.  You can then build inplace for development using
 <code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">setup.py</span> <span class="pre">build_ext</span> <span class="pre">-j8</span> <span class="pre">--inplace</span></code> (in <code class="docutils literal notranslate"><span class="pre">extensions/</span></code>)</p>
-<p>This will result in a directory structure as follows:</p>
+<p>This results in the directory structure:</p>
 <div class="line-block">
 <div class="line">extensions</div>
 <div class="line">├── mlx_sample_extensions</div>
 <div class="line">│   ├── __init__.py</div>
 <div class="line">│   ├── libmlx_ext.dylib # C++ extension library</div>
 <div class="line">│   ├── mlx_ext.metallib # Metal library</div>
-<div class="line">│   └── mlx_sample_extensions.cpython-3x-darwin.so # Python Binding</div>
+<div class="line">│   └── _ext.cpython-3x-darwin.so # Python Binding</div>
 <div class="line">…</div>
 </div>
-<p>When you try to install using the command <code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">-m</span> <span class="pre">pip</span> <span class="pre">install</span> <span class="pre">.</span></code>
-(in <code class="docutils literal notranslate"><span class="pre">extensions/</span></code>), the package will be installed with the same structure as
-<code class="docutils literal notranslate"><span class="pre">extensions/mlx_sample_extensions</span></code> and the C++ and metal library will be
-copied along with the python binding since they are specified as <code class="docutils literal notranslate"><span class="pre">package_data</span></code>.</p>
+<p>When you try to install using the command <code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">-m</span> <span class="pre">pip</span> <span class="pre">install</span> <span class="pre">.</span></code> (in
+<code class="docutils literal notranslate"><span class="pre">extensions/</span></code>), the package will be installed with the same structure as
+<code class="docutils literal notranslate"><span class="pre">extensions/mlx_sample_extensions</span></code> and the C++ and Metal library will be
+copied along with the Python binding since they are specified as
+<code class="docutils literal notranslate"><span class="pre">package_data</span></code>.</p>
 </section>
 </section>
 <section id="usage">
 <h2>Usage<a class="headerlink" href="#usage" title="Link to this heading">#</a></h2>
 <p>After installing the extension as described above, you should be able to simply
-import the python package and play with it as you would any other MLX operation!</p>
-<p>Let’s looks at a simple script and it’s results!</p>
+import the Python package and play with it as you would any other MLX operation.</p>
+<p>Let’s look at a simple script and its results:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">mlx.core</span> <span class="k">as</span> <span class="nn">mx</span>
 <span class="kn">from</span> <span class="nn">mlx_sample_extensions</span> <span class="kn">import</span> <span class="n">axpby</span>
 
@@ -1606,7 +1579,7 @@ import the python package and play with it as you would any other MLX operation!
 <section id="results">
 <h3>Results<a class="headerlink" href="#results" title="Link to this heading">#</a></h3>
 <p>Let’s run a quick benchmark and see how our new <code class="docutils literal notranslate"><span class="pre">axpby</span></code> operation compares
-with the naive <code class="xref py py-meth docutils literal notranslate"><span class="pre">simple_axpby()</span></code> we defined at first on the CPU.</p>
+with the naive <code class="xref py py-meth docutils literal notranslate"><span class="pre">simple_axpby()</span></code> we first defined on the CPU.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">mlx.core</span> <span class="k">as</span> <span class="nn">mx</span>
 <span class="kn">from</span> <span class="nn">mlx_sample_extensions</span> <span class="kn">import</span> <span class="n">axpby</span>
 <span class="kn">import</span> <span class="nn">time</span>
@@ -1624,7 +1597,7 @@ with the naive <code class="xref py py-meth docutils literal notranslate"><span
 <span class="n">alpha</span> <span class="o">=</span> <span class="mf">4.0</span>
 <span class="n">beta</span> <span class="o">=</span> <span class="mf">2.0</span>
 
-<span class="n">mx</span><span class="o">.</span><span class="n">eval</span><span class="p">((</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">))</span>
+<span class="n">mx</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
 
 <span class="k">def</span> <span class="nf">bench</span><span class="p">(</span><span class="n">f</span><span class="p">):</span>
     <span class="c1"># Warm up</span>
@@ -1646,21 +1619,18 @@ with the naive <code class="xref py py-meth docutils literal notranslate"><span
 <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Simple axpby: </span><span class="si">{</span><span class="n">simple_time</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> s | Custom axpby: </span><span class="si">{</span><span class="n">custom_time</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> s&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
-<p>Results:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">Simple</span> <span class="n">axpby</span><span class="p">:</span> <span class="mf">0.114</span> <span class="n">s</span> <span class="o">|</span> <span class="n">Custom</span> <span class="n">axpby</span><span class="p">:</span> <span class="mf">0.109</span> <span class="n">s</span>
-</pre></div>
-</div>
-<p>We see some modest improvements right away!</p>
+<p>The results are <code class="docutils literal notranslate"><span class="pre">Simple</span> <span class="pre">axpby:</span> <span class="pre">0.114</span> <span class="pre">s</span> <span class="pre">|</span> <span class="pre">Custom</span> <span class="pre">axpby:</span> <span class="pre">0.109</span> <span class="pre">s</span></code>. We see
+modest improvements right away!</p>
 <p>This operation is now good to be used to build other operations, in
 <a class="reference internal" href="../python/nn/module.html#mlx.nn.Module" title="mlx.nn.Module"><code class="xref py py-class docutils literal notranslate"><span class="pre">mlx.nn.Module</span></code></a> calls, and also as a part of graph transformations like
-<code class="xref py py-meth docutils literal notranslate"><span class="pre">grad()</span></code>!</p>
+<code class="xref py py-meth docutils literal notranslate"><span class="pre">grad()</span></code>.</p>
 </section>
 </section>
 <section id="scripts">
 <h2>Scripts<a class="headerlink" href="#scripts" title="Link to this heading">#</a></h2>
 <div class="admonition-download-the-code admonition">
 <p class="admonition-title">Download the code</p>
-<p>The full example code is available in <a class="reference external" href="code">mlx</a>.</p>
+<p>The full example code is available in <a class="reference external" href="https://github.com/ml-explore/mlx/tree/main/examples/extensions/">mlx</a>.</p>
 </div>
 </section>
 </section>
@@ -1713,12 +1683,12 @@ with the naive <code class="xref py py-meth docutils literal notranslate"><span
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#operations-and-primitives">Operations and Primitives</a><ul class="visible nav section-nav flex-column">
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#operations">Operations</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#primitives">Primitives</a></li>
-<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#using-the-primitives">Using the Primitives</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#using-the-primitive">Using the Primitive</a></li>
 </ul>
 </li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-primitive">Implementing the Primitive</a><ul class="visible nav section-nav flex-column">
-<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-cpu-backend">Implementing the CPU Backend</a></li>
-<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-gpu-backend">Implementing the GPU Backend</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-cpu-back-end">Implementing the CPU Back-end</a></li>
+<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#implementing-the-gpu-back-end">Implementing the GPU Back-end</a></li>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#primitive-transforms">Primitive Transforms</a></li>
 </ul>
 </li>

docs/build/html/dev/metal_debugger.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Metal Debugger &#8212; MLX 0.9.0 documentation</title>
+    <title>Metal Debugger &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../_static/documentation_options.js?v=cb265169"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -130,8 +130,8 @@
       
     
     
-    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -285,6 +285,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -317,6 +318,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.max.html">mlx.core.max</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -351,6 +353,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.square.html">mlx.core.square</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.subtract.html">mlx.core.subtract</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.sum.html">mlx.core.sum</a></li>
@@ -378,6 +381,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.gumbel.html">mlx.core.random.gumbel</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.key.html">mlx.core.random.key</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.seed.html">mlx.core.random.seed</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -431,6 +435,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>
@@ -773,25 +779,39 @@ document.write(`
   <section id="metal-debugger">
 <h1>Metal Debugger<a class="headerlink" href="#metal-debugger" title="Link to this heading">#</a></h1>
 <p>Profiling is a key step for performance optimization. You can build MLX with
-the <code class="docutils literal notranslate"><span class="pre">MLX_METAL_DEBUG</span></code> option to improve the Metal debugging and optimization
-workflow. The <code class="docutils literal notranslate"><span class="pre">MLX_METAL_DEBUG</span></code> debug option:</p>
+the <code class="docutils literal notranslate"><span class="pre">MLX_METAL_DEBUG</span></code> option to improve the Metal debugging and
+optimization workflow. The <code class="docutils literal notranslate"><span class="pre">MLX_METAL_DEBUG</span></code> debug option:</p>
 <ul class="simple">
 <li><p>Records source during Metal compilation, for later inspection while
 debugging.</p></li>
 <li><p>Labels Metal objects such as command queues, improving capture readability.</p></li>
 </ul>
-<p>The <code class="docutils literal notranslate"><span class="pre">metal::start_capture</span></code> function initiates a capture of all MLX GPU work.</p>
-<div class="highlight-C++ notranslate"><div class="highlight"><pre><span></span><span class="kt">int</span><span class="w"> </span><span class="nf">main</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
-<span class="w">    </span><span class="n">metal</span><span class="o">::</span><span class="n">start_capture</span><span class="p">(</span><span class="s">&quot;/Users/Jane/Developer/MLX.gputrace&quot;</span><span class="p">);</span>
+<p>To build with debugging enabled in Python prepend
+<code class="docutils literal notranslate"><span class="pre">CMAKE_ARGS=&quot;-DMLX_METAL_DEBUG=ON&quot;</span></code> to the build call.</p>
+<p>The <a class="reference internal" href="../python/_autosummary/mlx.core.metal.start_capture.html#mlx.core.metal.start_capture" title="mlx.core.metal.start_capture"><code class="xref py py-func docutils literal notranslate"><span class="pre">metal.start_capture()</span></code></a> function initiates a capture of all MLX GPU
+work.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>To capture a GPU trace you must run the application with
+<code class="docutils literal notranslate"><span class="pre">MTL_CAPTURE_ENABLED=1</span></code>.</p>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">mlx.core</span> <span class="k">as</span> <span class="nn">mx</span>
 
-<span class="w">    </span><span class="k">auto</span><span class="w"> </span><span class="n">a</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">arange</span><span class="p">(</span><span class="mf">10.f</span><span class="p">,</span><span class="w"> </span><span class="mf">20.f</span><span class="p">,</span><span class="w"> </span><span class="mf">1.f</span><span class="p">,</span><span class="w"> </span><span class="n">float32</span><span class="p">);</span>
-<span class="w">    </span><span class="k">auto</span><span class="w"> </span><span class="n">b</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">arange</span><span class="p">(</span><span class="mf">30.f</span><span class="p">,</span><span class="w"> </span><span class="mf">40.f</span><span class="p">,</span><span class="w"> </span><span class="mf">1.f</span><span class="p">,</span><span class="w"> </span><span class="n">float32</span><span class="p">);</span>
-<span class="w">    </span><span class="k">auto</span><span class="w"> </span><span class="n">c</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">add</span><span class="p">(</span><span class="n">a</span><span class="p">,</span><span class="w"> </span><span class="n">b</span><span class="p">);</span>
+<span class="n">a</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="mi">512</span><span class="p">))</span>
+<span class="n">b</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">512</span><span class="p">,</span> <span class="mi">512</span><span class="p">))</span>
+<span class="n">mx</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
 
-<span class="w">    </span><span class="n">eval</span><span class="p">(</span><span class="n">c</span><span class="p">);</span>
+<span class="n">trace_file</span> <span class="o">=</span> <span class="s2">&quot;mlx_trace.gputrace&quot;</span>
 
-<span class="w">    </span><span class="n">metal</span><span class="o">::</span><span class="n">stop_capture</span><span class="p">();</span>
-<span class="p">}</span>
+<span class="k">if</span> <span class="ow">not</span> <span class="n">mx</span><span class="o">.</span><span class="n">metal</span><span class="o">.</span><span class="n">start_capture</span><span class="p">(</span><span class="n">trace_file</span><span class="p">):</span>
+  <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Make sure to run with MTL_CAPTURE_ENABLED=1 and &quot;</span>
+        <span class="sa">f</span><span class="s2">&quot;that the path </span><span class="si">{</span><span class="n">trace_file</span><span class="si">}</span><span class="s2"> does not already exist.&quot;</span><span class="p">)</span>
+  <span class="n">exit</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
+
+<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">10</span><span class="p">):</span>
+  <span class="n">mx</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">))</span>
+
+<span class="n">mx</span><span class="o">.</span><span class="n">metal</span><span class="o">.</span><span class="n">stop_capture</span><span class="p">()</span>
 </pre></div>
 </div>
 <p>You can open and replay the GPU trace in Xcode. The <code class="docutils literal notranslate"><span class="pre">Dependencies</span></code> view
@@ -800,8 +820,8 @@ documentation</a> for more information.</p>
 <img alt="../_images/capture.png" class="dark-light" src="../_images/capture.png" />
 <section id="xcode-workflow">
 <h2>Xcode Workflow<a class="headerlink" href="#xcode-workflow" title="Link to this heading">#</a></h2>
-<p>You can skip saving to a path by running within Xcode. First, generate an Xcode
-project using CMake.</p>
+<p>You can skip saving to a path by running within Xcode. First, generate an
+Xcode project using CMake.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">mkdir</span> <span class="n">build</span> <span class="o">&amp;&amp;</span> <span class="n">cd</span> <span class="n">build</span>
 <span class="n">cmake</span> <span class="o">..</span> <span class="o">-</span><span class="n">DMLX_METAL_DEBUG</span><span class="o">=</span><span class="n">ON</span> <span class="o">-</span><span class="n">G</span> <span class="n">Xcode</span>
 <span class="nb">open</span> <span class="n">mlx</span><span class="o">.</span><span class="n">xcodeproj</span>

docs/build/html/examples/linear_regression.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Linear Regression &#8212; MLX 0.9.0 documentation</title>
+    <title>Linear Regression &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../_static/documentation_options.js?v=cb265169"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -131,8 +131,8 @@
       
     
     
-    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.max.html">mlx.core.max</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -352,6 +354,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.square.html">mlx.core.square</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.subtract.html">mlx.core.subtract</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.sum.html">mlx.core.sum</a></li>
@@ -379,6 +382,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.gumbel.html">mlx.core.random.gumbel</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.key.html">mlx.core.random.key</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.seed.html">mlx.core.random.seed</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -432,6 +436,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>

docs/build/html/examples/llama-inference.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>LLM inference &#8212; MLX 0.9.0 documentation</title>
+    <title>LLM inference &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../_static/documentation_options.js?v=cb265169"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -131,8 +131,8 @@
       
     
     
-    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.max.html">mlx.core.max</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -352,6 +354,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.square.html">mlx.core.square</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.subtract.html">mlx.core.subtract</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.sum.html">mlx.core.sum</a></li>
@@ -379,6 +382,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.gumbel.html">mlx.core.random.gumbel</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.key.html">mlx.core.random.key</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.seed.html">mlx.core.random.seed</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -432,6 +436,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>

docs/build/html/examples/mlp.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Multi-Layer Perceptron &#8212; MLX 0.9.0 documentation</title>
+    <title>Multi-Layer Perceptron &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
 <link rel="preload" as="script" href="../_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="../_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../_static/documentation_options.js?v=cb265169"></script>
     <script src="../_static/doctools.js?v=888ff710"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -131,8 +131,8 @@
       
     
     
-    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.max.html">mlx.core.max</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -352,6 +354,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.square.html">mlx.core.square</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.subtract.html">mlx.core.subtract</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.sum.html">mlx.core.sum</a></li>
@@ -379,6 +382,7 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.gumbel.html">mlx.core.random.gumbel</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.key.html">mlx.core.random.key</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.seed.html">mlx.core.random.seed</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -432,6 +436,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>

docs/build/html/genindex.html

@@ -7,7 +7,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Index &#8212; MLX 0.9.0 documentation</title>
+    <title>Index &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -35,7 +35,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="_static/documentation_options.js?v=cb265169"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -128,8 +128,8 @@
       
     
     
-    <img src="_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -283,6 +283,7 @@
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -315,6 +316,7 @@
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.max.html">mlx.core.max</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -349,6 +351,7 @@
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.square.html">mlx.core.square</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.subtract.html">mlx.core.subtract</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.sum.html">mlx.core.sum</a></li>
@@ -376,6 +379,7 @@
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.gumbel.html">mlx.core.random.gumbel</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.key.html">mlx.core.random.key</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.seed.html">mlx.core.random.seed</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -429,6 +433,8 @@
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>
@@ -1006,14 +1012,14 @@ document.write(`
 </li>
       <li><a href="python/_autosummary/mlx.core.erfinv.html#mlx.core.erfinv">erfinv() (in module mlx.core)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="python/_autosummary/mlx.core.eval.html#mlx.core.eval">eval() (in module mlx.core)</a>
 
       <ul>
         <li><a href="python/nn/_autosummary/mlx.nn.Module.eval.html#mlx.nn.Module.eval">(Module method)</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="python/_autosummary/mlx.core.array.exp.html#mlx.core.array.exp">exp() (array method)</a>
 
       <ul>
@@ -1021,6 +1027,8 @@ document.write(`
 </li>
       </ul></li>
       <li><a href="python/_autosummary/mlx.core.expand_dims.html#mlx.core.expand_dims">expand_dims() (in module mlx.core)</a>
+</li>
+      <li><a href="python/_autosummary/mlx.core.expm1.html#mlx.core.expm1">expm1() (in module mlx.core)</a>
 </li>
       <li><a href="python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html#mlx.optimizers.exponential_decay">exponential_decay() (in module mlx.optimizers)</a>
 </li>
@@ -1298,6 +1306,8 @@ document.write(`
         <li><a href="python/_autosummary/mlx.core.mean.html#mlx.core.mean">(in module mlx.core)</a>
 </li>
       </ul></li>
+      <li><a href="python/_autosummary/mlx.core.meshgrid.html#mlx.core.meshgrid">meshgrid() (in module mlx.core)</a>
+</li>
       <li><a href="python/_autosummary/mlx.core.array.min.html#mlx.core.array.min">min() (array method)</a>
 
       <ul>
@@ -1327,6 +1337,8 @@ document.write(`
       <li><a href="python/nn/_autosummary/mlx.nn.MultiHeadAttention.html#mlx.nn.MultiHeadAttention">MultiHeadAttention (class in mlx.nn)</a>
 </li>
       <li><a href="python/_autosummary/mlx.core.multiply.html#mlx.core.multiply">multiply() (in module mlx.core)</a>
+</li>
+      <li><a href="python/_autosummary/mlx.core.random.multivariate_normal.html#mlx.core.random.multivariate_normal">multivariate_normal() (in module mlx.core.random)</a>
 </li>
   </ul></td>
 </tr></table>
@@ -1540,14 +1552,14 @@ document.write(`
 </li>
       <li><a href="python/nn/_autosummary_functions/mlx.nn.losses.smooth_l1_loss.html#mlx.nn.losses.smooth_l1_loss">smooth_l1_loss() (in module mlx.nn.losses)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="python/_autosummary/mlx.core.softmax.html#mlx.core.softmax">softmax() (in module mlx.core)</a>
 
       <ul>
         <li><a href="python/nn/_autosummary_functions/mlx.nn.softmax.html#mlx.nn.softmax">(in module mlx.nn)</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="python/nn/_autosummary_functions/mlx.nn.softplus.html#mlx.nn.softplus">softplus() (in module mlx.nn)</a>
 </li>
       <li><a href="python/nn/_autosummary/mlx.nn.Softshrink.html#mlx.nn.Softshrink">Softshrink (class in mlx.nn)</a>
@@ -1583,6 +1595,8 @@ document.write(`
 </li>
       </ul></li>
       <li><a href="python/_autosummary/mlx.core.stack.html#mlx.core.stack">stack() (in module mlx.core)</a>
+</li>
+      <li><a href="python/_autosummary/mlx.core.metal.start_capture.html#mlx.core.metal.start_capture">start_capture() (in module mlx.core.metal)</a>
 </li>
       <li><a href="python/nn/_autosummary/mlx.nn.Module.state.html#mlx.nn.Module.state">state (Module property)</a>
 
@@ -1590,11 +1604,15 @@ document.write(`
         <li><a href="python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html#mlx.optimizers.Optimizer.state">(Optimizer property)</a>
 </li>
       </ul></li>
+      <li><a href="python/_autosummary/mlx.core.std.html#mlx.core.std">std() (in module mlx.core)</a>
+</li>
       <li><a href="python/nn/_autosummary/mlx.nn.Step.html#mlx.nn.Step">Step (class in mlx.nn)</a>
 </li>
       <li><a href="python/nn/_autosummary_functions/mlx.nn.step.html#mlx.nn.step">step() (in module mlx.nn)</a>
 </li>
       <li><a href="python/optimizers/_autosummary/mlx.optimizers.step_decay.html#mlx.optimizers.step_decay">step_decay() (in module mlx.optimizers)</a>
+</li>
+      <li><a href="python/_autosummary/mlx.core.metal.stop_capture.html#mlx.core.metal.stop_capture">stop_capture() (in module mlx.core.metal)</a>
 </li>
       <li><a href="python/_autosummary/mlx.core.stop_gradient.html#mlx.core.stop_gradient">stop_gradient() (in module mlx.core)</a>
 </li>

docs/build/html/index.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>MLX &#8212; MLX 0.9.0 documentation</title>
+    <title>MLX &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
 <link rel="preload" as="script" href="_static/scripts/pydata-sphinx-theme.js?digest=5b4479735964841361fd" />
   <script src="_static/vendor/fontawesome/6.1.2/js/all.min.js?digest=5b4479735964841361fd"></script>
 
-    <script src="_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="_static/documentation_options.js?v=cb265169"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/scripts/sphinx-book-theme.js?v=efea14e4"></script>
@@ -130,8 +130,8 @@
       
     
     
-    <img src="_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -285,6 +285,7 @@
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.erf.html">mlx.core.erf</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -317,6 +318,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.minimum.html">mlx.core.minimum</a></li>
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@@ -351,6 +353,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
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@@ -378,6 +381,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.randint.html">mlx.core.random.randint</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -431,6 +435,8 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="python/nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>

docs/build/html/install.html

@@ -8,7 +8,7 @@
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     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>Build and Install &#8212; MLX 0.9.0 documentation</title>
+    <title>Build and Install &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="_static/documentation_options.js?v=cb265169"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
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@@ -131,8 +131,8 @@
       
     
     
-    <img src="_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.min.html">mlx.core.min</a></li>
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@@ -352,6 +354,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
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@@ -379,6 +382,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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@@ -432,6 +436,8 @@
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 <li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="python/_autosummary/mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.Device.html

@@ -8,7 +8,7 @@
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     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>mlx.core.Device &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.Device &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
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@@ -131,8 +131,8 @@
       
     
     
-    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.erfinv.html">mlx.core.erfinv</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.maximum.html">mlx.core.maximum</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.min.html">mlx.core.min</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.moveaxis.html">mlx.core.moveaxis</a></li>
@@ -352,6 +354,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.squeeze.html">mlx.core.squeeze</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.sum.html">mlx.core.sum</a></li>
@@ -379,6 +382,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.random.randint.html">mlx.core.random.randint</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.random.split.html">mlx.core.random.split</a></li>
@@ -432,6 +436,8 @@
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.get_cache_memory.html">mlx.core.metal.get_cache_memory</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_memory_limit.html">mlx.core.metal.set_memory_limit</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
 </ul>
 </li>
 <li class="toctree-l1 has-children"><a class="reference internal" href="../nn.html">Neural Networks</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-11"><i class="fa-solid fa-chevron-down"></i></label><ul>

docs/build/html/python/_autosummary/mlx.core.Dtype.html

@@ -8,7 +8,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
-    <title>mlx.core.Dtype &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.Dtype &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
     <script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
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@@ -131,8 +131,8 @@
       
     
     
-    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.9.0 documentation - Home"/>
-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.eye.html">mlx.core.eye</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.flatten.html">mlx.core.flatten</a></li>
@@ -318,6 +319,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.mean.html">mlx.core.mean</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.min.html">mlx.core.min</a></li>
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@@ -352,6 +354,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html

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-    <title>mlx.core.DtypeCategory &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.DtypeCategory &#8212; MLX 0.10.0 documentation</title>
   
   
   
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.Stream.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.stream &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.stream &#8212; MLX 0.10.0 documentation</title>
   
   
   
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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@@ -432,6 +436,8 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.abs.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.abs &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.abs &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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@@ -131,8 +131,8 @@
       
     
     
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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@@ -432,6 +436,8 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.add.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.add &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.add &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
 </a></div>
@@ -286,6 +286,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
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@@ -318,6 +319,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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@@ -432,6 +436,8 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.all.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.all &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.all &#8212; MLX 0.10.0 documentation</title>
   
   
   
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
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@@ -318,6 +319,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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@@ -432,6 +436,8 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.allclose.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.allclose &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.allclose &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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@@ -131,8 +131,8 @@
       
     
     
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.exp.html">mlx.core.exp</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
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@@ -318,6 +319,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.stop_gradient.html">mlx.core.stop_gradient</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.random.normal.html">mlx.core.random.normal</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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@@ -432,6 +436,8 @@
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.set_cache_limit.html">mlx.core.metal.set_cache_limit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.stop_capture.html">mlx.core.metal.stop_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.any.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.any &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.any &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
     <script src="../../_static/doctools.js?v=888ff710"></script>
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@@ -131,8 +131,8 @@
       
     
     
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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@@ -286,6 +286,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="mlx.core.stack.html">mlx.core.stack</a></li>
+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.arange.html

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-    <title>mlx.core.arange &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.arange &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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docs/build/html/python/_autosummary/mlx.core.arccos.html

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-    <title>mlx.core.arccos &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.arccos &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.arccosh.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.arccosh &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.arccosh &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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@@ -131,8 +131,8 @@
       
     
     
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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docs/build/html/python/_autosummary/mlx.core.arcsin.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.arcsin &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.arcsin &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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@@ -286,6 +286,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.meshgrid.html">mlx.core.meshgrid</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.arcsinh.html

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-    <title>mlx.core.arcsinh &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.arcsinh &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
 <li class="toctree-l2"><a class="reference internal" href="mlx.core.expand_dims.html">mlx.core.expand_dims</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.arctan.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.arctan &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.arctan &#8212; MLX 0.10.0 documentation</title>
   
   
   
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.random.multivariate_normal.html">mlx.core.random.multivariate_normal</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.arctanh.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.arctanh &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.arctanh &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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@@ -131,8 +131,8 @@
       
     
     
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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@@ -286,6 +286,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.argmax.html

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-    <title>mlx.core.argmax &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.argmax &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.argmin.html

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-    <title>mlx.core.argmin &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.argmin &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.argpartition.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.argpartition &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.argpartition &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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docs/build/html/python/_autosummary/mlx.core.argsort.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.argsort &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.argsort &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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-    <script src="../../_static/documentation_options.js?v=2a76c96f"></script>
+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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@@ -131,8 +131,8 @@
       
     
     
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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docs/build/html/python/_autosummary/mlx.core.array.T.html

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docs/build/html/python/_autosummary/mlx.core.array.abs.html

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docs/build/html/python/_autosummary/mlx.core.array.all.html

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docs/build/html/python/_autosummary/mlx.core.array.any.html

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docs/build/html/python/_autosummary/mlx.core.array.argmax.html

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-    <title>mlx.core.array.argmax &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.argmin.html

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-    <title>mlx.core.array.argmin &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.astype.html

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-    <title>mlx.core.array.astype &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.at.html

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docs/build/html/python/_autosummary/mlx.core.array.cos.html

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-    <title>mlx.core.array.cos &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.cummax.html

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-    <title>mlx.core.array.cummax &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.cummin.html

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docs/build/html/python/_autosummary/mlx.core.array.cumprod.html

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docs/build/html/python/_autosummary/mlx.core.array.cumsum.html

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docs/build/html/python/_autosummary/mlx.core.array.diag.html

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docs/build/html/python/_autosummary/mlx.core.array.diagonal.html

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docs/build/html/python/_autosummary/mlx.core.array.dtype.html

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-    <title>mlx.core.array.dtype &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.exp.html

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-    <title>mlx.core.array.exp &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.flatten.html

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docs/build/html/python/_autosummary/mlx.core.array.html

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-    <title>mlx.core.array &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.item.html

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-    <title>mlx.core.array.item &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.itemsize.html

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-    <title>mlx.core.array.itemsize &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.log.html

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docs/build/html/python/_autosummary/mlx.core.array.log10.html

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docs/build/html/python/_autosummary/mlx.core.array.log1p.html

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-    <title>mlx.core.array.log1p &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.log2.html

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docs/build/html/python/_autosummary/mlx.core.array.logsumexp.html

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docs/build/html/python/_autosummary/mlx.core.array.max.html

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docs/build/html/python/_autosummary/mlx.core.array.mean.html

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-    <title>mlx.core.array.mean &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.moveaxis.html

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-    <title>mlx.core.array.moveaxis &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.nbytes.html

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-    <title>mlx.core.array.nbytes &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.ndim.html

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-    <title>mlx.core.array.ndim &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.round.html

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docs/build/html/python/_autosummary/mlx.core.array.rsqrt.html

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-    <title>mlx.core.array.rsqrt &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.shape.html

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-    <title>mlx.core.array.shape &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.sin.html

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-    <title>mlx.core.array.sin &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.size.html

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docs/build/html/python/_autosummary/mlx.core.array.split.html

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-    <title>mlx.core.array.split &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.sqrt.html

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-    <title>mlx.core.array.sqrt &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.square.html

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-    <title>mlx.core.array.square &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.array.square &#8212; MLX 0.10.0 documentation</title>
   
   
   
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docs/build/html/python/_autosummary/mlx.core.array.squeeze.html

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-    <title>mlx.core.array.squeeze &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.sum.html

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-    <title>mlx.core.array.sum &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.array.sum &#8212; MLX 0.10.0 documentation</title>
   
   
   
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docs/build/html/python/_autosummary/mlx.core.array.swapaxes.html

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-    <title>mlx.core.array.swapaxes &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.array.swapaxes &#8212; MLX 0.10.0 documentation</title>
   
   
   
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docs/build/html/python/_autosummary/mlx.core.array.tolist.html

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docs/build/html/python/_autosummary/mlx.core.array.transpose.html

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-    <title>mlx.core.array.transpose &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array.var.html

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-    <title>mlx.core.array.var &#8212; MLX 0.9.0 documentation</title>
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docs/build/html/python/_autosummary/mlx.core.array_equal.html

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-    <title>mlx.core.array_equal &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.array_equal &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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docs/build/html/python/_autosummary/mlx.core.atleast_1d.html

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-    <title>mlx.core.atleast_1d &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.atleast_1d &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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docs/build/html/python/_autosummary/mlx.core.atleast_2d.html

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-    <title>mlx.core.atleast_2d &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.atleast_2d &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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docs/build/html/python/_autosummary/mlx.core.atleast_3d.html

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-    <title>mlx.core.atleast_3d &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.atleast_3d &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.std.html">mlx.core.std</a></li>
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docs/build/html/python/_autosummary/mlx.core.broadcast_to.html

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-    <title>mlx.core.broadcast_to &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.broadcast_to &#8212; MLX 0.10.0 documentation</title>
   
   
   
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+    <script src="../../_static/documentation_options.js?v=cb265169"></script>
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+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.expm1.html">mlx.core.expm1</a></li>
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docs/build/html/python/_autosummary/mlx.core.ceil.html

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-    <title>mlx.core.ceil &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.ceil &#8212; MLX 0.10.0 documentation</title>
   
   
   
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-    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.9.0 documentation - Home"/>`);</script>
+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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+<li class="toctree-l2"><a class="reference internal" href="mlx.core.metal.start_capture.html">mlx.core.metal.start_capture</a></li>
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docs/build/html/python/_autosummary/mlx.core.clip.html

@@ -8,7 +8,7 @@
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-    <title>mlx.core.clip &#8212; MLX 0.9.0 documentation</title>
+    <title>mlx.core.clip &#8212; MLX 0.10.0 documentation</title>
   
   
   
@@ -36,7 +36,7 @@
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+    <img src="../../_static/mlx_logo.png" class="logo__image only-light" alt="MLX 0.10.0 documentation - Home"/>
+    <script>document.write(`<img src="../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.10.0 documentation - Home"/>`);</script>
   
   
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