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Author SHA1 Message Date
Alex Cheema 44845be117 fix instance type mismatch in /instance/previews endpoint
Derive instance_meta from the actual instance type returned by
place_instance() instead of using the requested instance_meta from
the loop variable. place_instance() overrides single-node placements
to MlxRing, but the preview response was still reporting the original
requested type (e.g., MlxJaccl), causing a mismatch.

Closes #1426

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-17 14:51:33 -08:00
636 changed files with 7919 additions and 34913 deletions
-20
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@@ -1,20 +0,0 @@
from enum import Enum
class HarmonyEncodingName(Enum):
HARMONY_GPT_OSS = ...
class HarmonyEncoding: ...
class HarmonyError(Exception): ...
class Role(Enum):
ASSISTANT = ...
class StreamableParser:
last_content_delta: str
current_channel: str | None
current_recipient: str | None
def __init__(self, encoding: HarmonyEncoding, role: Role = ...) -> None: ...
def process(self, token_id: int) -> None: ...
def load_harmony_encoding(name: HarmonyEncodingName) -> HarmonyEncoding: ...
-17
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@@ -1,17 +0,0 @@
class NvmlMemoryInfo:
used: int
total: int
free: int
class NvmlUtilizationRates:
gpu: int
memory: int
def nvmlInit() -> None: ...
def nvmlShutdown() -> None: ...
def nvmlDeviceGetCount() -> int: ...
def nvmlDeviceGetHandleByIndex(index: int) -> object: ...
def nvmlDeviceGetUtilizationRates(handle: object) -> NvmlUtilizationRates: ...
def nvmlDeviceGetTemperature(handle: object, sensor_type: int) -> int: ...
def nvmlDeviceGetPowerUsage(handle: object) -> int: ...
def nvmlDeviceGetMemoryInfo(handle: object) -> NvmlMemoryInfo: ...
-61
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@@ -1,61 +0,0 @@
from typing import Any, Sequence
from torch import backends as backends
from torch import cuda as cuda
from torch import distributed as distributed
__version__: str
class version:
cuda: str
class dtype: ...
bfloat16: dtype
float16: dtype
float32: dtype
int8: dtype
int32: dtype
int64: dtype
long: dtype
float8_e4m3fn: dtype
class Tensor:
shape: Sequence[int]
dtype: dtype
def __getitem__(self, key: Any) -> Tensor: ...
def __setitem__(self, key: Any, value: Any) -> None: ...
def to(self, *args: Any, **kwargs: Any) -> Tensor: ...
def cpu(self) -> Tensor: ...
def detach(self) -> Tensor: ...
def clone(self) -> Tensor: ...
def flatten(self, start_dim: int = 0, end_dim: int = -1) -> Tensor: ...
def view(self, *shape: Any) -> Tensor: ...
def squeeze(self, dim: int = ...) -> Tensor: ...
def unsqueeze(self, dim: int) -> Tensor: ...
def permute(self, *dims: int) -> Tensor: ...
def float(self) -> Tensor: ...
def numpy(self) -> Any: ...
def numel(self) -> int: ...
def nelement(self) -> int: ...
@property
def is_cuda(self) -> bool: ...
@property
def device(self) -> device: ...
def __len__(self) -> int: ...
def data_ptr(self) -> int: ...
def tolist(self) -> Any: ...
def abs(self) -> Tensor: ...
def max(self) -> Tensor: ...
def mean(self) -> Tensor: ...
def sum(self, dim: int = ...) -> Tensor: ...
def item(self) -> float: ...
def tensor(data: Any, dtype: dtype | None = None, device: Any = None) -> Tensor: ...
def zeros(*size: Any, dtype: dtype | None = None, device: Any = None) -> Tensor: ...
def empty(*size: Any, dtype: dtype | None = None, device: Any = None) -> Tensor: ...
def from_numpy(ndarray: Any) -> Tensor: ...
def inference_mode() -> Any: ...
class device:
def __init__(self, type: str, index: int = ...) -> None: ...
@@ -1 +0,0 @@
from torch.backends import cuda as cuda
@@ -1 +0,0 @@
def is_built() -> bool: ...
-10
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@@ -1,10 +0,0 @@
class _DeviceProperties:
total_memory: int
def is_available() -> bool: ...
def get_device_name(device: int) -> str: ...
def get_device_properties(device: int) -> _DeviceProperties: ...
def empty_cache() -> None: ...
def mem_get_info() -> tuple[int, int]: ...
def synchronize() -> None: ...
def max_memory_allocated() -> int: ...
@@ -1,2 +0,0 @@
def is_initialized() -> bool: ...
def destroy_process_group() -> None: ...
-1
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@@ -1 +0,0 @@
__version__: str
-2
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@@ -1,2 +0,0 @@
class ModelConfig:
max_model_len: int
-18
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@@ -1,18 +0,0 @@
from dataclasses import dataclass
@dataclass
class EngineArgs:
model: str = ...
served_model_name: str | list[str] | None = ...
tokenizer: str | None = ...
trust_remote_code: bool = ...
dtype: str = ...
seed: int = ...
max_model_len: int | None = ...
gpu_memory_utilization: float = ...
enforce_eager: bool = ...
tensor_parallel_size: int = ...
pipeline_parallel_size: int = ...
quantization: str | None = ...
load_format: str = ...
enable_sleep_mode: bool = ...
-17
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@@ -1,17 +0,0 @@
class CompletionOutput:
index: int
text: str
token_ids: list[int]
cumulative_logprob: float | None
logprobs: object | None
finish_reason: str | None
stop_reason: int | str | None
def finished(self) -> bool: ...
class RequestOutput:
request_id: str
prompt: str | None
prompt_token_ids: list[int] | None
outputs: list[CompletionOutput]
finished: bool
-11
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@@ -1,11 +0,0 @@
class SamplingParams:
n: int
temperature: float
top_p: float
top_k: int
min_p: float
seed: int | None
stop: str | list[str] | None
max_tokens: int | None
logprobs: int | None
repetition_penalty: float
@@ -1,3 +0,0 @@
from vllm.tokenizers.protocol import TokenizerLike
__all__ = ["TokenizerLike"]
@@ -1,15 +0,0 @@
from typing import Protocol
class TokenizerLike(Protocol):
@property
def eos_token_id(self) -> int: ...
@property
def vocab_size(self) -> int: ...
def encode(self, text: str, add_special_tokens: bool = ...) -> list[int]: ...
def decode(self, ids: list[int] | int, skip_special_tokens: bool = ...) -> str: ...
def apply_chat_template(
self,
messages: list[dict[str, str]],
tools: list[dict[str, object]] | None = ...,
**kwargs: object,
) -> str | list[int]: ...
-1
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@@ -1 +0,0 @@
-1
View File
@@ -1 +0,0 @@
@@ -1,24 +0,0 @@
from collections.abc import Sequence
from vllm.v1.core.kv_cache_utils import BlockPool, KVCacheBlock
from vllm.v1.kv_cache_interface import KVCacheConfig
class KVCacheBlocks:
blocks: tuple[Sequence[KVCacheBlock], ...]
def __init__(self, blocks: tuple[Sequence[KVCacheBlock], ...]) -> None: ...
def get_block_ids(self) -> tuple[list[int], ...]: ...
class KVCacheManager:
block_pool: BlockPool
kv_cache_config: KVCacheConfig
enable_caching: bool
num_kv_cache_groups: int
coordinator: object
def __init__(self, *args: object, **kwargs: object) -> None: ...
def allocate_slots(
self, request: object, num_new_tokens: int, *args: object, **kwargs: object
) -> KVCacheBlocks | None: ...
def get_computed_blocks(self, request: object) -> tuple[KVCacheBlocks, int]: ...
def create_kv_cache_blocks(
self, blocks: tuple[list[KVCacheBlock], ...]
) -> KVCacheBlocks: ...
@@ -1,16 +0,0 @@
class KVCacheBlock:
block_id: int
ref_cnt: int
def __init__(self, block_id: int) -> None: ...
class FreeKVCacheBlockQueue:
def append_n(self, blocks: list[KVCacheBlock]) -> None: ...
def popleft_n(self, n: int) -> list[KVCacheBlock]: ...
class BlockPool:
blocks: list[KVCacheBlock]
free_block_queue: FreeKVCacheBlockQueue
num_gpu_blocks: int
enable_caching: bool
def get_num_free_blocks(self) -> int: ...
def get_new_blocks(self, num_blocks: int) -> list[KVCacheBlock]: ...
@@ -1,22 +0,0 @@
from vllm.config import ModelConfig
from vllm.engine.arg_utils import EngineArgs
from vllm.outputs import RequestOutput
from vllm.sampling_params import SamplingParams
from vllm.tokenizers import TokenizerLike
class LLMEngine:
tokenizer: TokenizerLike | None
model_config: ModelConfig
@classmethod
def from_engine_args(cls, engine_args: EngineArgs) -> LLMEngine: ...
def add_request(
self,
request_id: str,
prompt: str,
params: SamplingParams,
arrival_time: float | None = ...,
) -> None: ...
def step(self) -> list[RequestOutput]: ...
def has_unfinished_requests(self) -> bool: ...
def get_tokenizer(self) -> TokenizerLike: ...
@@ -1,23 +0,0 @@
from dataclasses import dataclass
@dataclass
class KVCacheSpec:
block_size: int
num_kv_heads: int
head_size: int
@dataclass
class KVCacheGroupSpec:
layer_names: list[str]
kv_cache_spec: KVCacheSpec
@dataclass
class KVCacheTensorSpec:
shared_by: list[str]
size: int
@dataclass
class KVCacheConfig:
num_blocks: int
kv_cache_groups: list[KVCacheGroupSpec]
kv_cache_tensors: list[KVCacheTensorSpec]
-6
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@@ -1,6 +0,0 @@
class Request:
request_id: str
prompt_token_ids: list[int] | None
num_prompt_tokens: int
num_computed_tokens: int
num_tokens: int
@@ -1 +0,0 @@
@@ -1,24 +0,0 @@
import torch
class _CompilationConfig:
static_forward_context: dict[str, object]
class _ModelConfig:
hf_config: object
class GPUModelRunner:
kv_caches: list[torch.Tensor]
compilation_config: _CompilationConfig
model_config: _ModelConfig | None
def _allocate_kv_cache_tensors(
self, kv_cache_config: object
) -> dict[str, torch.Tensor]: ...
def initialize_kv_cache_tensors(
self, kv_cache_config: object, kernel_block_sizes: list[int]
) -> dict[str, torch.Tensor]: ...
def _reshape_kv_cache_tensors(
self,
kv_cache_config: object,
raw_tensors: dict[str, torch.Tensor],
kernel_block_sizes: list[int],
) -> dict[str, torch.Tensor]: ...
@@ -1,6 +0,0 @@
from vllm.v1.worker.gpu_model_runner import GPUModelRunner
class Worker:
model_runner: GPUModelRunner
def determine_available_memory(self) -> int: ...
def initialize_from_config(self, kv_cache_config: object) -> None: ...
-1
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@@ -1 +0,0 @@
def extract_layer_index(layer_name: str, num_attn_module: int) -> int: ...
@@ -2,11 +2,10 @@
This type stub file was generated by pyright.
"""
from typing import Protocol
import mlx.core as mx
import PIL.Image
import tqdm
from typing import Protocol
from mflux.models.common.config.config import Config
class BeforeLoopCallback(Protocol):
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
from mflux.callbacks.callback import (
AfterLoopCallback,
BeforeLoopCallback,
@@ -2,11 +2,10 @@
This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
import mlx.core as mx
import PIL.Image
import tqdm
from typing import TYPE_CHECKING
from mflux.callbacks.callback_registry import CallbackRegistry
from mflux.models.common.config.config import Config
@@ -2,12 +2,11 @@
This type stub file was generated by pyright.
"""
import mlx.core as mx
from pathlib import Path
from typing import Any
import mlx.core as mx
from mflux.models.common.config.model_config import ModelConfig
from tqdm import tqdm
from mflux.models.common.config.model_config import ModelConfig
logger = ...
@@ -2,11 +2,10 @@
This type stub file was generated by pyright.
"""
import mlx.core as mx
from functools import lru_cache
from typing import Literal
import mlx.core as mx
class ModelConfig:
precision: mx.Dtype = ...
def __init__(
@@ -2,10 +2,10 @@
This type stub file was generated by pyright.
"""
import mlx.core as mx
from pathlib import Path
from typing import TYPE_CHECKING, TypeAlias
import mlx.core as mx
from mlx import nn
from mflux.models.common.vae.tiling_config import TilingConfig
from mflux.models.fibo.latent_creator.fibo_latent_creator import FiboLatentCreator
from mflux.models.flux.latent_creator.flux_latent_creator import FluxLatentCreator
@@ -13,7 +13,6 @@ from mflux.models.qwen.latent_creator.qwen_latent_creator import QwenLatentCreat
from mflux.models.z_image.latent_creator.z_image_latent_creator import (
ZImageLatentCreator,
)
from mlx import nn
if TYPE_CHECKING:
LatentCreatorType: TypeAlias = type[
@@ -2,8 +2,8 @@
This type stub file was generated by pyright.
"""
from mflux.models.common.lora.layer.linear_lora_layer import LoRALinear
from mlx import nn
from mflux.models.common.lora.layer.linear_lora_layer import LoRALinear
class FusedLoRALinear(nn.Module):
def __init__(
@@ -2,11 +2,10 @@
This type stub file was generated by pyright.
"""
from collections.abc import Callable
from dataclasses import dataclass
import mlx.core as mx
import mlx.nn as nn
from collections.abc import Callable
from dataclasses import dataclass
from mflux.models.common.lora.mapping.lora_mapping import LoRATarget
@dataclass
@@ -2,12 +2,11 @@
This type stub file was generated by pyright.
"""
import mlx.core as mx
from collections.abc import Callable
from dataclasses import dataclass
from typing import List, Protocol
import mlx.core as mx
@dataclass
class LoRATarget:
model_path: str
@@ -36,3 +36,4 @@ class Rule(NamedTuple):
name: str
check: str
action: QuantizationAction | PathAction | LoraAction | ConfigAction
...
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
from mflux.models.common.config.model_config import ModelConfig
if TYPE_CHECKING: ...
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from abc import ABC, abstractmethod
import mlx.core as mx
from abc import ABC, abstractmethod
class BaseScheduler(ABC):
@property
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
import mlx.core as mx
from typing import TYPE_CHECKING
from mflux.models.common.config.config import Config
from mflux.models.common.schedulers.base_scheduler import BaseScheduler
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
import mlx.core as mx
from typing import TYPE_CHECKING
from mflux.models.common.config.config import Config
from mflux.models.common.schedulers.base_scheduler import BaseScheduler
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
import mlx.core as mx
from typing import TYPE_CHECKING
from mflux.models.common.config.config import Config
from mflux.models.common.schedulers.base_scheduler import BaseScheduler
@@ -4,10 +4,9 @@ This type stub file was generated by pyright.
from abc import ABC, abstractmethod
from typing import Protocol, runtime_checkable
from mflux.models.common.tokenizer.tokenizer_output import TokenizerOutput
from PIL import Image
from transformers import PreTrainedTokenizer
from mflux.models.common.tokenizer.tokenizer_output import TokenizerOutput
"""
This type stub file was generated by pyright.
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
from mflux.models.common.tokenizer.tokenizer import BaseTokenizer
from mflux.models.common.weights.loading.weight_definition import TokenizerDefinition
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from dataclasses import dataclass
import mlx.core as mx
from dataclasses import dataclass
"""
This type stub file was generated by pyright.
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from typing import Callable
import mlx.core as mx
from typing import Callable
class VAETiler:
@staticmethod
@@ -3,8 +3,8 @@ This type stub file was generated by pyright.
"""
import mlx.core as mx
from mflux.models.common.vae.tiling_config import TilingConfig
from mlx import nn
from mflux.models.common.vae.tiling_config import TilingConfig
class VAEUtil:
@staticmethod
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
import mlx.nn as nn
from typing import TYPE_CHECKING
from mflux.models.common.weights.loading.loaded_weights import LoadedWeights
from mflux.models.common.weights.loading.weight_definition import (
ComponentDefinition,
@@ -2,12 +2,11 @@
This type stub file was generated by pyright.
"""
from dataclasses import dataclass
from typing import TYPE_CHECKING, Callable, List, TypeAlias
import mlx.core as mx
from mflux.models.common.tokenizer.tokenizer import BaseTokenizer
from dataclasses import dataclass
from typing import Callable, List, TYPE_CHECKING, TypeAlias
from mflux.models.common.weights.mapping.weight_mapping import WeightTarget
from mflux.models.common.tokenizer.tokenizer import BaseTokenizer
from mflux.models.depth_pro.weights.depth_pro_weight_definition import (
DepthProWeightDefinition,
)
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING
from mflux.models.common.weights.loading.loaded_weights import LoadedWeights
from mflux.models.common.weights.loading.weight_definition import (
ComponentDefinition,
@@ -2,9 +2,8 @@
This type stub file was generated by pyright.
"""
from typing import Dict, List, Optional
import mlx.core as mx
from typing import Dict, List, Optional
from mflux.models.common.weights.mapping.weight_mapping import WeightTarget
class WeightMapper:
@@ -2,11 +2,10 @@
This type stub file was generated by pyright.
"""
import mlx.core as mx
from dataclasses import dataclass
from typing import Callable, List, Optional, Protocol
import mlx.core as mx
"""
This type stub file was generated by pyright.
"""
@@ -2,8 +2,7 @@
This type stub file was generated by pyright.
"""
from typing import TYPE_CHECKING, Any
from typing import Any, TYPE_CHECKING
from mflux.models.common.weights.loading.weight_definition import WeightDefinitionType
if TYPE_CHECKING: ...
@@ -2,10 +2,9 @@
This type stub file was generated by pyright.
"""
import mlx.core as mx
from dataclasses import dataclass
from pathlib import Path
import mlx.core as mx
from PIL import Image
@dataclass
@@ -14,6 +13,7 @@ class DepthResult:
depth_array: mx.array
min_depth: float
max_depth: float
...
class DepthPro:
def __init__(self, quantize: int | None = ...) -> None: ...
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import List
from mflux.models.common.weights.loading.weight_definition import (
ComponentDefinition,
TokenizerDefinition,
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import List
from mflux.models.common.weights.mapping.weight_mapping import (
WeightMapping,
WeightTarget,
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import List
from mflux.models.common.weights.loading.weight_definition import (
ComponentDefinition,
TokenizerDefinition,
@@ -3,7 +3,6 @@ This type stub file was generated by pyright.
"""
from typing import List
from mflux.models.common.weights.mapping.weight_mapping import (
WeightMapping,
WeightTarget,

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