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This commit is contained in:
Alex Cheema
2025-07-21 22:42:37 +01:00
committed by GitHub
parent cb101e3d24
commit 449fdac27a
19 changed files with 1404 additions and 24 deletions
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pyproject.toml
+4 -1
View File
@@ -5,8 +5,11 @@ description = "Exo"
readme = "README.md"
requires-python = ">=3.13"
dependencies = [
"aiofiles>=24.1.0",
"aiohttp>=3.12.14",
"exo-master",
"exo-worker",
"types-aiofiles>=24.1.0.20250708",
]
# dependencies only required for development
@@ -108,4 +111,4 @@ extend-select = ["I", "N", "B", "A", "PIE", "SIM"]
[tool.pytest.ini_options]
pythonpath = "."
asyncio_mode = "auto"
asyncio_mode = "auto"
shared/graphs.py
+41 -1
View File
@@ -1,8 +1,9 @@
from dataclasses import dataclass
from typing import Mapping, Set
from typing import Any, Callable, Mapping, Set
import rustworkx as rx
from pydantic import TypeAdapter
from pydantic_core import core_schema
from shared.types.graphs.common import (
Edge,
@@ -15,6 +16,7 @@ from shared.types.graphs.common import (
VertexIdT,
VertexTypeT,
)
from shared.types.graphs.pydantic import PydanticGraph
@dataclass(frozen=True)
@@ -52,6 +54,44 @@ class Graph(MutableGraphProtocol[EdgeTypeT, VertexTypeT, EdgeIdT, VertexIdT]):
self._vertex_id_to_index = {}
self._edge_id_to_endpoints = {}
# TODO: I'm not sure if this is the right thing, but we'll simplify the graph stuff anyway so fine for now.
@classmethod
def __get_pydantic_core_schema__(
cls,
_source: type[Any],
handler: Callable[[Any], core_schema.CoreSchema],
) -> core_schema.CoreSchema:
pydantic_graph_schema = handler(PydanticGraph)
def serializer(
instance: "Graph[EdgeTypeT, VertexTypeT, EdgeIdT, VertexIdT]",
) -> dict[str, Any]:
return {
"vertices": list(instance.get_vertex_data(instance.list_vertices())),
"edges": list(instance.get_edge_data(instance.list_edges())),
}
return core_schema.json_or_python_schema(
json_schema=pydantic_graph_schema,
python_schema=core_schema.no_info_plain_validator_function(cls.validate),
serialization=core_schema.plain_serializer_function_ser_schema(serializer),
)
@classmethod
def validate(
cls, value: Any # type: ignore
) -> "Graph[EdgeTypeT, VertexTypeT, EdgeIdT, VertexIdT]":
if isinstance(value, cls):
return value
if isinstance(value, dict):
raise NotImplementedError(
"Deserializing a Graph from a dictionary is not yet supported. "
"Please initialize the Graph object directly."
)
raise TypeError("Unsupported type for Graph validation")
###
# GraphProtocol methods
###
shared/types/graphs/pydantic.py
+8
View File
@@ -0,0 +1,8 @@
from typing import Any, List
from pydantic import BaseModel
class PydanticGraph(BaseModel):
vertices: List[Any]
edges: List[Any]
shared/types/state.py
+4 -4
View File
@@ -1,8 +1,8 @@
from collections.abc import Mapping, Sequence
from enum import Enum
from queue import Queue
from typing import List
from pydantic import BaseModel, TypeAdapter
from pydantic import BaseModel, Field, TypeAdapter
from shared.types.common import NodeId
from shared.types.graphs.topology import (
@@ -36,6 +36,6 @@ class State(BaseModel):
edge_base=TypeAdapter(TopologyEdge), vertex_base=TypeAdapter(TopologyNode)
)
history: Sequence[OrphanedPartOfTopology] = []
task_inbox: Queue[Task] = Queue()
task_outbox: Queue[Task] = Queue()
task_inbox: List[Task] = Field(default_factory=list)
task_outbox: List[Task] = Field(default_factory=list)
cache_policy: CachePolicy = CachePolicy.KeepAll
shared/types/worker/shards.py
+13 -2
View File
@@ -1,7 +1,7 @@
from enum import Enum
from typing import Annotated, Generic, Literal, TypeAlias, TypeVar
from pydantic import BaseModel, DirectoryPath, Field, TypeAdapter
from pydantic import BaseModel, Field, TypeAdapter
from shared.types.common import NodeId
from shared.types.models import ModelId
@@ -24,7 +24,6 @@ class BaseShardMetadata(BaseModel, Generic[PartitionStrategyT]):
device_rank: int
world_size: int
model_id: ModelId
model_path: DirectoryPath
class PipelineShardMetadata(BaseShardMetadata[Literal[PartitionStrategy.pipeline]]):
@@ -37,6 +36,18 @@ class PipelineShardMetadata(BaseShardMetadata[Literal[PartitionStrategy.pipeline
)
start_layer: Annotated[int, Field(ge=0)]
end_layer: Annotated[int, Field(ge=0)]
n_layers: Annotated[int, Field(ge=0)]
@property
def is_first_layer(self) -> bool:
return self.start_layer == 0
@property
def is_last_layer(self) -> bool:
return self.end_layer == self.n_layers - 1
def __hash__(self) -> int:
return hash((self.model_id, self.start_layer, self.end_layer, self.n_layers))
ShardMetadata = Annotated[
uv.lock
Generated
+245
View File
@@ -20,6 +20,68 @@ members = [
"exo-worker",
]
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[[package]]
name = "certifi"
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@@ -97,8 +168,11 @@ name = "exo"
version = "0.2.0"
source = { editable = "." }
dependencies = [
{ name = "aiofiles", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
{ name = "aiohttp", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
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{ name = "types-aiofiles", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
]
[package.optional-dependencies]
@@ -116,9 +190,12 @@ dev = [
[package.metadata]
requires-dist = [
{ name = "aiofiles", specifier = ">=24.1.0" },
{ name = "aiohttp", specifier = ">=3.12.14" },
{ name = "exo-master", editable = "master" },
{ name = "exo-worker", editable = "worker" },
{ name = "mlx", marker = "extra == 'darwin'" },
{ name = "types-aiofiles", specifier = ">=24.1.0.20250708" },
]
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worker/download/download_utils.py
+430
View File
@@ -0,0 +1,430 @@
import asyncio
import hashlib
import os
import shutil
import tempfile
import time
import traceback
from datetime import timedelta
from pathlib import Path
from typing import Annotated, Callable, Dict, List, Literal, Optional, Tuple, Union
from urllib.parse import urljoin
import aiofiles
import aiofiles.os as aios
import aiohttp
from pydantic import BaseModel, DirectoryPath, Field, TypeAdapter
from shared.constants import EXO_HOME
from shared.types.worker.shards import ShardMetadata
from worker.download.huggingface_utils import (
filter_repo_objects,
get_allow_patterns,
get_auth_headers,
get_hf_endpoint,
)
class ModelSafetensorsIndexMetadata(BaseModel):
total_size: Annotated[int, Field(ge=0)]
class ModelSafetensorsIndex(BaseModel):
metadata: Optional[ModelSafetensorsIndexMetadata]
weight_map: Dict[str, str]
class FileListEntry(BaseModel):
type: Literal["file", "directory"]
path: str
size: int | None = None
class RepoFileDownloadProgress(BaseModel):
"""Progress information for an individual file within a repository download."""
repo_id: str
repo_revision: str
file_path: str
downloaded: int
downloaded_this_session: int
total: int
speed: float # bytes per second
eta: timedelta
status: Literal["not_started", "in_progress", "complete"]
start_time: float
class Config:
frozen = True
class RepoDownloadProgress(BaseModel):
"""Aggregated download progress information for a repository/shard combination.
This structure captures the overall progress of downloading the files
required to materialise a particular *shard* of a model. It purposely
mirrors the key summary fields emitted by the `RepoProgressEvent` so that
the event payload can be cleanly projected onto the long-lived cluster
state.
"""
repo_id: str
repo_revision: str
shard: ShardMetadata
# progress totals
completed_files: int
total_files: int
downloaded_bytes: int
downloaded_bytes_this_session: int
total_bytes: int
# speed / eta
overall_speed: float # bytes per second
overall_eta: timedelta
# lifecycle status
status: Literal["not_started", "in_progress", "complete"]
# fine-grained file progress keyed by file_path
file_progress: Dict[str, RepoFileDownloadProgress] = Field(default_factory=dict)
class Config:
frozen = True # allow use as dict keys if desired
def build_model_path(model_id: str) -> DirectoryPath:
return EXO_HOME / "models" / model_id.replace("/", "--")
def exo_tmp() -> Path:
return Path(tempfile.gettempdir())/"exo"
async def resolve_model_path_for_repo(repo_id: str) -> Path:
return (await ensure_models_dir())/repo_id.replace("/", "--")
async def ensure_exo_home() -> Path:
await aios.makedirs(EXO_HOME, exist_ok=True)
return EXO_HOME
async def ensure_exo_tmp() -> Path:
await aios.makedirs(exo_tmp(), exist_ok=True)
return exo_tmp()
async def has_exo_home_read_access() -> bool:
try:
return await aios.access(EXO_HOME, os.R_OK)
except OSError:
return False
async def has_exo_home_write_access() -> bool:
try:
return await aios.access(EXO_HOME, os.W_OK)
except OSError:
return False
async def ensure_models_dir() -> Path:
models_dir = EXO_HOME/"models"
await aios.makedirs(models_dir, exist_ok=True)
return models_dir
async def delete_model(repo_id: str) -> bool:
model_dir = await ensure_models_dir()/repo_id.replace("/", "--")
if not await aios.path.exists(model_dir):
return False
await asyncio.to_thread(shutil.rmtree, model_dir, ignore_errors=False)
return True
async def seed_models(seed_dir: Union[str, Path]):
"""Move model in resources folder of app to .cache/huggingface/hub"""
source_dir = Path(seed_dir)
dest_dir = await ensure_models_dir()
for path in source_dir.iterdir():
if path.is_dir() and path.name.startswith("models--"):
dest_path = dest_dir/path.name
if await aios.path.exists(dest_path):
print('Skipping moving model to .cache directory')
else:
try:
await aios.rename(str(path), str(dest_path))
except Exception:
print(f"Error seeding model {path} to {dest_path}")
traceback.print_exc()
async def fetch_file_list_with_cache(repo_id: str, revision: str = "main", recursive: bool = False) -> List[FileListEntry]:
cache_file = (await ensure_exo_tmp())/f"{repo_id.replace('/', '--')}--{revision}--file_list.json"
if await aios.path.exists(cache_file):
async with aiofiles.open(cache_file, 'r') as f:
return TypeAdapter(List[FileListEntry]).validate_json(await f.read())
file_list = await fetch_file_list_with_retry(repo_id, revision, recursive=recursive)
await aios.makedirs(cache_file.parent, exist_ok=True)
async with aiofiles.open(cache_file, 'w') as f:
await f.write(TypeAdapter(List[FileListEntry]).dump_json(file_list).decode())
return file_list
async def fetch_file_list_with_retry(repo_id: str, revision: str = "main", path: str = "", recursive: bool = False) -> List[FileListEntry]:
n_attempts = 30
for attempt in range(n_attempts):
try:
return await _fetch_file_list(repo_id, revision, path, recursive)
except Exception as e:
if attempt == n_attempts - 1:
raise e
await asyncio.sleep(min(8, 0.1 * float(2.0 ** int(attempt))))
raise Exception(f"Failed to fetch file list for {repo_id=} {revision=} {path=} {recursive=}")
async def _fetch_file_list(repo_id: str, revision: str = "main", path: str = "", recursive: bool = False) -> List[FileListEntry]:
api_url = f"{get_hf_endpoint()}/api/models/{repo_id}/tree/{revision}"
url = f"{api_url}/{path}" if path else api_url
headers = await get_auth_headers()
async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=30, connect=10, sock_read=30, sock_connect=10)) as session, session.get(url, headers=headers) as response:
if response.status == 200:
data_json = await response.text()
data = TypeAdapter(list[FileListEntry]).validate_json(data_json)
files: list[FileListEntry] = []
for item in data:
if item.type == "file":
files.append(FileListEntry.model_validate(item))
elif item.type == "directory" and recursive:
subfiles = await _fetch_file_list(repo_id, revision, item.path, recursive)
files.extend(subfiles)
return files
else:
raise Exception(f"Failed to fetch file list: {response.status}")
async def calc_hash(path: Path, hash_type: Literal["sha1", "sha256"] = "sha1") -> str:
hasher = hashlib.sha1() if hash_type == "sha1" else hashlib.sha256()
if hash_type == "sha1":
header = f"blob {(await aios.stat(path)).st_size}\0".encode()
hasher.update(header)
async with aiofiles.open(path, 'rb') as f:
while chunk := await f.read(8 * 1024 * 1024):
hasher.update(chunk)
return hasher.hexdigest()
async def file_meta(repo_id: str, revision: str, path: str) -> Tuple[int, str]:
url = urljoin(f"{get_hf_endpoint()}/{repo_id}/resolve/{revision}/", path)
headers = await get_auth_headers()
async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=1800, connect=60, sock_read=1800, sock_connect=60)) as session, session.head(url, headers=headers) as r:
content_length = int(r.headers.get('x-linked-size') or r.headers.get('content-length') or 0)
etag = r.headers.get('X-Linked-ETag') or r.headers.get('ETag') or r.headers.get('Etag')
assert content_length > 0, f"No content length for {url}"
assert etag is not None, f"No remote hash for {url}"
if (etag[0] == '"' and etag[-1] == '"') or (etag[0] == "'" and etag[-1] == "'"):
etag = etag[1:-1]
return content_length, etag
async def download_file_with_retry(repo_id: str, revision: str, path: str, target_dir: Path, on_progress: Callable[[int, int], None] = lambda _, __: None) -> Path:
n_attempts = 30
for attempt in range(n_attempts):
try:
return await _download_file(repo_id, revision, path, target_dir, on_progress)
except Exception as e:
if isinstance(e, FileNotFoundError) or attempt == n_attempts - 1:
raise e
print(f"Download error on attempt {attempt}/{n_attempts} for {repo_id=} {revision=} {path=} {target_dir=}")
traceback.print_exc()
await asyncio.sleep(min(8, 0.1 * (2.0 ** attempt)))
raise Exception(f"Failed to download file {repo_id=} {revision=} {path=} {target_dir=}")
async def _download_file(repo_id: str, revision: str, path: str, target_dir: Path, on_progress: Callable[[int, int], None] = lambda _, __: None) -> Path:
if await aios.path.exists(target_dir/path):
return target_dir/path
await aios.makedirs((target_dir/path).parent, exist_ok=True)
length, etag = await file_meta(repo_id, revision, path)
remote_hash = etag[:-5] if etag.endswith("-gzip") else etag
partial_path = target_dir/f"{path}.partial"
resume_byte_pos = (await aios.stat(partial_path)).st_size if (await aios.path.exists(partial_path)) else None
if resume_byte_pos != length:
url = urljoin(f"{get_hf_endpoint()}/{repo_id}/resolve/{revision}/", path)
headers = await get_auth_headers()
if resume_byte_pos:
headers['Range'] = f'bytes={resume_byte_pos}-'
n_read = resume_byte_pos or 0
async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=1800, connect=60, sock_read=1800, sock_connect=60)) as session, session.get(url, headers=headers, timeout=aiohttp.ClientTimeout(total=1800, connect=60, sock_read=1800, sock_connect=60)) as r:
if r.status == 404:
raise FileNotFoundError(f"File not found: {url}")
assert r.status in [200, 206], f"Failed to download {path} from {url}: {r.status}"
async with aiofiles.open(partial_path, 'ab' if resume_byte_pos else 'wb') as f:
while chunk := await r.content.read(8 * 1024 * 1024):
on_progress(n_read := n_read + await f.write(chunk), length)
final_hash = await calc_hash(partial_path, hash_type="sha256" if len(remote_hash) == 64 else "sha1")
integrity = final_hash == remote_hash
if not integrity:
try:
await aios.remove(partial_path)
except Exception as e:
print(f"Error removing partial file {partial_path}: {e}")
raise Exception(f"Downloaded file {target_dir/path} has hash {final_hash} but remote hash is {remote_hash}")
await aios.rename(partial_path, target_dir/path)
return target_dir/path
def calculate_repo_progress(shard: ShardMetadata, repo_id: str, revision: str, file_progress: Dict[str, RepoFileDownloadProgress], all_start_time: float) -> RepoDownloadProgress:
all_total_bytes = sum(p.total for p in file_progress.values())
all_downloaded_bytes = sum(p.downloaded for p in file_progress.values())
all_downloaded_bytes_this_session = sum(p.downloaded_this_session for p in file_progress.values())
elapsed_time = time.time() - all_start_time
all_speed = all_downloaded_bytes_this_session / elapsed_time if elapsed_time > 0 else 0
all_eta = timedelta(seconds=(all_total_bytes - all_downloaded_bytes) / all_speed) if all_speed > 0 else timedelta(seconds=0)
status = (
"complete"
if all(p.status == "complete" for p in file_progress.values())
else "in_progress" if any(p.status == "in_progress" for p in file_progress.values()) else "not_started"
)
return RepoDownloadProgress(
repo_id=repo_id,
repo_revision=revision,
shard=shard,
completed_files=len([p for p in file_progress.values() if p.downloaded == p.total]),
total_files=len(file_progress),
downloaded_bytes=all_downloaded_bytes,
downloaded_bytes_this_session=all_downloaded_bytes_this_session,
total_bytes=all_total_bytes,
overall_speed=all_speed,
overall_eta=all_eta,
status=status,
file_progress=file_progress,
)
async def get_weight_map(repo_id: str, revision: str = "main") -> Dict[str, str]:
target_dir = (await ensure_exo_tmp())/repo_id.replace("/", "--")
index_file = await download_file_with_retry(repo_id, revision, "model.safetensors.index.json", target_dir)
async with aiofiles.open(index_file, 'r') as f:
index_data = ModelSafetensorsIndex.model_validate_json(await f.read())
return index_data.weight_map
async def resolve_allow_patterns(shard: ShardMetadata) -> List[str]:
try:
weight_map = await get_weight_map(str(shard.model_id))
return get_allow_patterns(weight_map, shard)
except Exception:
print(f"Error getting weight map for {shard.model_id=}")
traceback.print_exc()
return ["*"]
async def get_downloaded_size(path: Path) -> int:
partial_path = path.with_suffix(path.suffix + ".partial")
if await aios.path.exists(path):
return (await aios.stat(path)).st_size
if await aios.path.exists(partial_path):
return (await aios.stat(partial_path)).st_size
return 0
async def download_progress_for_local_path(repo_id: str, shard: ShardMetadata, local_path: Path) -> RepoDownloadProgress:
# Scan local files for accurate progress reporting
file_progress: Dict[str, RepoFileDownloadProgress] = {}
total_files = 0
total_bytes = 0
if await aios.path.isdir(local_path):
# Recursively count files and sizes
for root, _, files in os.walk(local_path):
for f in files:
if f.endswith(('.safetensors', '.bin', '.pt', '.gguf', '.json')):
file_path = Path(root) / f
size = (await aios.stat(file_path)).st_size
rel_path = str(file_path.relative_to(local_path))
file_progress[rel_path] = RepoFileDownloadProgress(
repo_id=repo_id,
repo_revision="local",
file_path=rel_path,
downloaded=size,
downloaded_this_session=0,
total=size,
speed=0,
eta=timedelta(0),
status="complete",
start_time=time.time()
)
total_files += 1
total_bytes += size
else:
raise ValueError(f"Local path {local_path} is not a directory")
return RepoDownloadProgress(
repo_id=repo_id,
repo_revision="local",
shard=shard,
completed_files=total_files,
total_files=total_files,
downloaded_bytes=total_bytes,
downloaded_bytes_this_session=0,
total_bytes=total_bytes,
overall_speed=0,
overall_eta=timedelta(0),
status="complete",
file_progress=file_progress,
)
async def download_shard(shard: ShardMetadata,
on_progress: Callable[[ShardMetadata, RepoDownloadProgress], None],
max_parallel_downloads: int = 8,
skip_download: bool = False,
allow_patterns: List[str] | None = None) -> tuple[Path, RepoDownloadProgress]:
if not skip_download:
print(f"Downloading {shard.model_id=}")
# Handle local paths
if await aios.path.exists(str(shard.model_id)):
print(f"Using local model path {shard.model_id}")
local_path = Path(str(shard.model_id))
return local_path, await download_progress_for_local_path(str(shard.model_id), shard, local_path)
revision = "main"
target_dir = await ensure_models_dir()/str(shard.model_id).replace("/", "--")
if not skip_download:
await aios.makedirs(target_dir, exist_ok=True)
if not allow_patterns:
allow_patterns = await resolve_allow_patterns(shard)
print(f"Downloading {shard.model_id=} with {allow_patterns=}")
all_start_time = time.time()
# TODO: currently not recursive. Some models might require subdirectories - thus this will need to be changed.
file_list = await fetch_file_list_with_cache(str(shard.model_id), revision, recursive=False)
filtered_file_list = list(filter_repo_objects(file_list, allow_patterns=allow_patterns, key=lambda x: x.path))
file_progress: Dict[str, RepoFileDownloadProgress] = {}
def on_progress_wrapper(file: FileListEntry, curr_bytes: int, total_bytes: int):
start_time = file_progress[file.path].start_time if file.path in file_progress else time.time()
downloaded_this_session = file_progress[file.path].downloaded_this_session + (curr_bytes - file_progress[file.path].downloaded) if file.path in file_progress else curr_bytes
speed = downloaded_this_session / (time.time() - start_time) if time.time() - start_time > 0 else 0
eta = timedelta(seconds=(total_bytes - curr_bytes) / speed) if speed > 0 else timedelta(seconds=0)
file_progress[file.path] = RepoFileDownloadProgress(
repo_id=str(shard.model_id),
repo_revision=revision,
file_path=file.path,
downloaded=curr_bytes,
downloaded_this_session=downloaded_this_session,
total=total_bytes,
speed=speed,
eta=eta,
status="complete" if curr_bytes == total_bytes else "in_progress",
start_time=start_time,
)
on_progress(shard, calculate_repo_progress(shard, str(shard.model_id), revision, file_progress, all_start_time))
for file in filtered_file_list:
downloaded_bytes = await get_downloaded_size(target_dir/file.path)
file_progress[file.path] = RepoFileDownloadProgress(
repo_id=str(shard.model_id),
repo_revision=revision,
file_path=file.path,
downloaded=downloaded_bytes,
downloaded_this_session=0,
total=file.size or 0,
speed=0,
eta=timedelta(0),
status="complete" if downloaded_bytes == file.size else "not_started",
start_time=time.time(),
)
semaphore = asyncio.Semaphore(max_parallel_downloads)
async def download_with_semaphore(file: FileListEntry):
async with semaphore:
await download_file_with_retry(str(shard.model_id), revision, file.path, target_dir, lambda curr_bytes, total_bytes: on_progress_wrapper(file, curr_bytes, total_bytes))
if not skip_download:
await asyncio.gather(*[download_with_semaphore(file) for file in filtered_file_list])
final_repo_progress = calculate_repo_progress(shard, str(shard.model_id), revision, file_progress, all_start_time)
on_progress(shard, final_repo_progress)
if gguf := next((f for f in filtered_file_list if f.path.endswith(".gguf")), None):
return target_dir/gguf.path, final_repo_progress
else:
return target_dir, final_repo_progress
worker/download/huggingface_utils.py
+97
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import os
from fnmatch import fnmatch
from pathlib import Path
from typing import Callable, Dict, Generator, Iterable, List, Optional, TypeVar, Union
import aiofiles
import aiofiles.os as aios
from shared.types.worker.shards import ShardMetadata
T = TypeVar("T")
def filter_repo_objects(
items: Iterable[T],
*,
allow_patterns: Optional[Union[List[str], str]] = None,
ignore_patterns: Optional[Union[List[str], str]] = None,
key: Optional[Callable[[T], str]] = None,
) -> Generator[T, None, None]:
if isinstance(allow_patterns, str):
allow_patterns = [allow_patterns]
if isinstance(ignore_patterns, str):
ignore_patterns = [ignore_patterns]
if allow_patterns is not None:
allow_patterns = [_add_wildcard_to_directories(p) for p in allow_patterns]
if ignore_patterns is not None:
ignore_patterns = [_add_wildcard_to_directories(p) for p in ignore_patterns]
if key is None:
def _identity(item: T) -> str:
if isinstance(item, str):
return item
if isinstance(item, Path):
return str(item)
raise ValueError(f"Please provide `key` argument in `filter_repo_objects`: `{item}` is not a string.")
key = _identity
for item in items:
path = key(item)
if allow_patterns is not None and not any(fnmatch(path, r) for r in allow_patterns):
continue
if ignore_patterns is not None and any(fnmatch(path, r) for r in ignore_patterns):
continue
yield item
def _add_wildcard_to_directories(pattern: str) -> str:
if pattern[-1] == "/":
return pattern + "*"
return pattern
def get_hf_endpoint() -> str:
return os.environ.get('HF_ENDPOINT', "https://huggingface.co")
def get_hf_home() -> Path:
"""Get the Hugging Face home directory."""
return Path(os.environ.get("HF_HOME", Path.home()/".cache"/"huggingface"))
async def get_hf_token() -> Optional[str]:
"""Retrieve the Hugging Face token from the user's HF_HOME directory."""
token_path = get_hf_home()/"token"
if await aios.path.exists(token_path):
async with aiofiles.open(token_path, 'r') as f:
return (await f.read()).strip()
return None
async def get_auth_headers() -> dict[str, str]:
"""Get authentication headers if a token is available."""
token = await get_hf_token()
if token:
return {"Authorization": f"Bearer {token}"}
return {}
def extract_layer_num(tensor_name: str) -> Optional[int]:
# This is a simple example and might need to be adjusted based on the actual naming convention
parts = tensor_name.split('.')
for part in parts:
if part.isdigit():
return int(part)
return None
def get_allow_patterns(weight_map: Dict[str, str], shard: ShardMetadata) -> List[str]:
default_patterns = set(["*.json", "*.py", "tokenizer.model", "*.tiktoken", "*.txt"])
shard_specific_patterns: set[str] = set()
if weight_map:
for tensor_name, filename in weight_map.items():
layer_num = extract_layer_num(tensor_name)
if layer_num is not None and shard.start_layer <= layer_num <= shard.end_layer:
shard_specific_patterns.add(filename)
sorted_file_names = sorted(weight_map.values())
if shard.is_first_layer:
shard_specific_patterns.add(sorted_file_names[0])
elif shard.is_last_layer:
shard_specific_patterns.add(sorted_file_names[-1])
else:
shard_specific_patterns = set(["*.safetensors"])
print(f"get_allow_patterns {shard=} {shard_specific_patterns=}")
return list(default_patterns | shard_specific_patterns)
worker/download/impl_shard_downloader.py
+128
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@@ -0,0 +1,128 @@
import asyncio
from pathlib import Path
from typing import AsyncIterator, Callable, Dict, List, Optional
from shared.types.worker.shards import (
PartitionStrategy,
PipelineShardMetadata,
ShardMetadata,
)
from worker.download.download_utils import RepoDownloadProgress, download_shard
from worker.download.model_cards import MODEL_CARDS
from worker.download.model_meta import get_model_meta
from worker.download.shard_downloader import ShardDownloader
def exo_shard_downloader(max_parallel_downloads: int = 8) -> ShardDownloader:
return SingletonShardDownloader(CachedShardDownloader(ResumableShardDownloader(max_parallel_downloads)))
async def build_base_shard(model_id: str) -> Optional[ShardMetadata]:
model_meta = await get_model_meta(model_id)
# print(f"build_base_shard {model_id=} {model_meta=}")
return PipelineShardMetadata(
model_id=model_id,
partition_strategy=PartitionStrategy.pipeline,
device_rank=0,
world_size=1,
start_layer=0,
end_layer=model_meta.n_layers - 1,
n_layers=model_meta.n_layers,
)
async def build_full_shard(model_id: str) -> Optional[PipelineShardMetadata]:
base_shard = await build_base_shard(model_id)
if base_shard is None:
return None
return PipelineShardMetadata(
model_id=base_shard.model_id,
partition_strategy=base_shard.partition_strategy,
device_rank=base_shard.device_rank,
world_size=base_shard.world_size,
start_layer=base_shard.start_layer,
end_layer=base_shard.n_layers - 1,
n_layers=base_shard.n_layers,
)
class SingletonShardDownloader(ShardDownloader):
def __init__(self, shard_downloader: ShardDownloader):
self.shard_downloader = shard_downloader
self.active_downloads: Dict[ShardMetadata, asyncio.Task[Path]] = {}
def on_progress(self, callback: Callable[[ShardMetadata, RepoDownloadProgress], None]) -> None:
self.shard_downloader.on_progress(callback)
async def ensure_shard(self, shard: ShardMetadata, config_only: bool = False) -> Path:
if shard not in self.active_downloads:
self.active_downloads[shard] = asyncio.create_task(self.shard_downloader.ensure_shard(shard, config_only))
try:
return await self.active_downloads[shard]
finally:
if shard in self.active_downloads and self.active_downloads[shard].done():
del self.active_downloads[shard]
async def get_shard_download_status(self) -> AsyncIterator[tuple[Path, RepoDownloadProgress]]:
async for path, status in self.shard_downloader.get_shard_download_status():
yield path, status
class CachedShardDownloader(ShardDownloader):
def __init__(self, shard_downloader: ShardDownloader):
self.shard_downloader = shard_downloader
self.cache: Dict[tuple[str, ShardMetadata], Path] = {}
def on_progress(self, callback: Callable[[ShardMetadata, RepoDownloadProgress], None]) -> None:
self.shard_downloader.on_progress(callback)
async def ensure_shard(self, shard: ShardMetadata, config_only: bool = False) -> Path:
if (shard.model_id, shard) in self.cache:
# print(f"ensure_shard cache hit {shard=}")
return self.cache[(shard.model_id, shard)]
# print(f"ensure_shard cache miss {shard=}")
target_dir = await self.shard_downloader.ensure_shard(shard, config_only)
self.cache[(shard.model_id, shard)] = target_dir
return target_dir
async def get_shard_download_status(self) -> AsyncIterator[tuple[Path, RepoDownloadProgress]]:
async for path, status in self.shard_downloader.get_shard_download_status():
yield path, status
class ResumableShardDownloader(ShardDownloader):
def __init__(self, max_parallel_downloads: int = 8):
self.max_parallel_downloads = max_parallel_downloads
self.on_progress_callbacks: List[Callable[[ShardMetadata, RepoDownloadProgress], None]] = []
def on_progress_wrapper(self, shard: ShardMetadata, progress: RepoDownloadProgress) -> None:
for callback in self.on_progress_callbacks:
callback(shard, progress)
def on_progress(self, callback: Callable[[ShardMetadata, RepoDownloadProgress], None]) -> None:
self.on_progress_callbacks.append(callback)
async def ensure_shard(self, shard: ShardMetadata, config_only: bool = False) -> Path:
allow_patterns = ["config.json"] if config_only else None
# print(f"ensure_shard {shard=} {config_only=} {allow_patterns=}")
target_dir, _ = await download_shard(shard, self.on_progress_wrapper, max_parallel_downloads=self.max_parallel_downloads, allow_patterns=allow_patterns)
return target_dir
async def get_shard_download_status(self) -> AsyncIterator[tuple[Path, RepoDownloadProgress]]:
# print("get_shard_download_status")
async def _status_for_model(model_id: str) -> Optional[tuple[Path, RepoDownloadProgress]]:
"""Helper coroutine that builds the shard for a model and gets its download status."""
shard = await build_full_shard(model_id)
if shard is None:
return None
return await download_shard(shard, self.on_progress_wrapper, skip_download=True)
# Kick off download status coroutines concurrently
tasks = [asyncio.create_task(_status_for_model(model_id)) for model_id in MODEL_CARDS]
for task in asyncio.as_completed(tasks):
try:
result = await task
if result is None:
continue
path, progress = result
yield (path, progress)
except Exception as e:
print("Error downloading shard:", e)
worker/download/model_cards.py
+133
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@@ -0,0 +1,133 @@
from typing import List
from pydantic import BaseModel
class ModelCard(BaseModel):
id: str
repo_id: str
name: str
description: str
tags: List[str]
MODEL_CARDS = {
"llama-3.3": ModelCard(
id="llama-3.3",
repo_id="mlx-community/Llama-3.3-70B-Instruct-4bit",
name="Llama 3.3 70B",
description="The Meta Llama 3.3 multilingual large language model (LLM) is an instruction tuned generative model in 70B (text in/text out)",
tags=[]),
"llama-3.3:70b": ModelCard(
id="llama-3.3:70b",
repo_id="mlx-community/Llama-3.3-70B-Instruct-4bit",
name="Llama 3.3 70B",
description="The Meta Llama 3.3 multilingual large language model (LLM) is an instruction tuned generative model in 70B (text in/text out)",
tags=[]),
"llama-3.2": ModelCard(
id="llama-3.2",
repo_id="mlx-community/Llama-3.2-1B-Instruct-4bit",
name="Llama 3.2 1B",
description="Llama 3.2 is a large language model trained on the Llama 3.2 dataset.",
tags=[]),
"llama-3.2:1b": ModelCard(
id="llama-3.2:1b",
repo_id="mlx-community/Llama-3.2-1B-Instruct-4bit",
name="Llama 3.2 1B",
description="Llama 3.2 is a large language model trained on the Llama 3.2 dataset.",
tags=[]),
"llama-3.2:3b": ModelCard(
id="llama-3.2:3b",
repo_id="mlx-community/Llama-3.2-3B-Instruct-4bit",
name="Llama 3.2 3B",
description="Llama 3.2 is a large language model trained on the Llama 3.2 dataset.",
tags=[]),
"llama-3.1:8b": ModelCard(
id="llama-3.1:8b",
repo_id="mlx-community/Meta-Llama-3.1-8B-Instruct-4bit",
name="Llama 3.1 8B",
description="Llama 3.1 is a large language model trained on the Llama 3.1 dataset.",
tags=[]),
"llama-3.1-70b": ModelCard(
id="llama-3.1-70b",
repo_id="mlx-community/Meta-Llama-3.1-70B-Instruct-4bit",
name="Llama 3.1 70B",
description="Llama 3.1 is a large language model trained on the Llama 3.1 dataset.",
tags=[]),
"deepseek-r1": ModelCard(
id="deepseek-r1",
repo_id="mlx-community/DeepSeek-R1-4bit",
name="DeepSeek R1 671B (4-bit)",
description="DeepSeek R1 is a large language model trained on the DeepSeek R1 dataset.",
tags=[]),
"deepseek-r1:671b": ModelCard(
id="deepseek-r1:671b", # TODO: make sure model_id matches up for identical models
repo_id="mlx-community/DeepSeek-R1-4bit",
name="DeepSeek R1 671B",
description="DeepSeek R1 is a large language model trained on the DeepSeek R1 dataset.",
tags=[]),
"deepseek-v3": ModelCard(
id="deepseek-v3",
repo_id="mlx-community/DeepSeek-V3-0324-4bit",
name="DeepSeek V3 4B",
description="DeepSeek V3 is a large language model trained on the DeepSeek V3 dataset.",
tags=[]),
"deepseek-v3:671b": ModelCard(
id="deepseek-v3:671b",
repo_id="mlx-community/DeepSeek-V3-0324-4bit",
name="DeepSeek V3 671B",
description="DeepSeek V3 is a large language model trained on the DeepSeek V3 dataset.",
tags=[]),
"phi-3-mini": ModelCard(
id="phi-3-mini",
repo_id="mlx-community/Phi-3-mini-128k-instruct-4bit",
name="Phi 3 Mini 128k",
description="Phi 3 Mini is a large language model trained on the Phi 3 Mini dataset.",
tags=[]),
"phi-3-mini:128k": ModelCard(
id="phi-3-mini:128k",
repo_id="mlx-community/Phi-3-mini-128k-instruct-4bit",
name="Phi 3 Mini 128k",
description="Phi 3 Mini is a large language model trained on the Phi 3 Mini dataset.",
tags=[]),
"qwen3-0.6b": ModelCard(
id="qwen3-0.6b",
repo_id="mlx-community/Qwen3-0.6B-4bit",
name="Qwen3 0.6B",
description="Qwen3 0.6B is a large language model trained on the Qwen3 0.6B dataset.",
tags=[]),
"qwen3-30b": ModelCard(
id="qwen3-30b",
repo_id="mlx-community/Qwen3-30B-A3B-4bit",
name="Qwen3 30B (Active 3B)",
description="Qwen3 30B is a large language model trained on the Qwen3 30B dataset.",
tags=[]),
"granite-3.3-2b": ModelCard(
id="granite-3.3-2b",
repo_id="mlx-community/granite-3.3-2b-instruct-fp16",
name="Granite 3.3 2B",
description="Granite-3.3-2B-Instruct is a 2-billion parameter 128K context length language model fine-tuned for improved reasoning and instruction-following capabilities.",
tags=[]),
"granite-3.3-8b": ModelCard(
id="granite-3.3-8b",
repo_id="mlx-community/granite-3.3-8b-instruct-fp16",
name="Granite 3.3 8B",
description="Granite-3.3-8B-Instruct is a 8-billion parameter 128K context length language model fine-tuned for improved reasoning and instruction-following capabilities.",
tags=[]),
"smol-lm-135m": ModelCard(
id="smol-lm-135m",
repo_id="mlx-community/SmolLM-135M-4bit",
name="Smol LM 135M",
description="SmolLM is a series of state-of-the-art small language models available in three sizes: 135M, 360M, and 1.7B parameters. ",
tags=[]),
}
def get_huggingface_id(model: str) -> str:
if "mlx-community/" in model:
return model
if model not in MODEL_CARDS:
raise ValueError(f"Model {model} not found")
return MODEL_CARDS[model].repo_id
if __name__ == "__main__":
for model in MODEL_CARDS:
print(f"{model} -> {get_huggingface_id(model)}")
worker/download/model_meta.py
+124
View File
@@ -0,0 +1,124 @@
import json
from typing import Annotated, Dict, Optional
import aiofiles
from huggingface_hub import model_info
from huggingface_hub.errors import EntryNotFoundError, HfHubHTTPError
from pydantic import BaseModel, Field
from shared.types.models import ModelMetadata
from worker.download.download_utils import (
ModelSafetensorsIndex,
download_file_with_retry,
ensure_exo_tmp,
)
from worker.download.model_cards import MODEL_CARDS
class ConfigData(BaseModel):
num_hidden_layers: Optional[Annotated[int, Field(ge=0)]]
num_layers: Optional[Annotated[int, Field(ge=0)]]
n_layer: Optional[Annotated[int, Field(ge=0)]]
async def get_config_data(model_id: str) -> Optional[ConfigData]:
"""Downloads and parses config.json for a model."""
try:
model_card = MODEL_CARDS[model_id]
target_dir = (await ensure_exo_tmp())/model_card.repo_id.replace("/", "--")
config_path = await download_file_with_retry(model_card.repo_id, "main", "config.json", target_dir, lambda curr_bytes, total_bytes: print(f"Downloading config.json for {model_id}: {curr_bytes}/{total_bytes}"))
async with aiofiles.open(config_path, 'r') as f:
return ConfigData.model_validate_json(await f.read())
except EntryNotFoundError:
print(f"Warning: config.json not found for {model_id}. Layers/type from config unavailable.")
except json.JSONDecodeError:
print(f"Error: Failed to parse config.json for {model_id}.")
except Exception as e:
print(f"Error: Error processing config.json for {model_id}: {e}")
return None
def get_num_layers(config_data: Optional[ConfigData], model_id: str) -> Optional[int]:
"""Extracts number of layers from config data."""
if not config_data:
return None
if config_data.num_hidden_layers is not None:
return config_data.num_hidden_layers
if config_data.num_layers is not None:
return config_data.num_layers
if config_data.n_layer is not None:
return config_data.n_layer
print(f"Warning: No known layer key or valid number in config.json for {model_id}. Config: {config_data.model_dump_json()}")
return None
async def get_safetensors_size(model_id: str) -> Optional[int]:
"""Gets model size from safetensors index or falls back to HF API."""
try:
model_card = MODEL_CARDS[model_id]
target_dir = (await ensure_exo_tmp())/model_card.repo_id.replace("/", "--")
index_path = await download_file_with_retry(model_card.repo_id, "main", "model.safetensors.index.json", target_dir, lambda curr_bytes, total_bytes: print(f"Downloading model.safetensors.index.json for {model_id}: {curr_bytes}/{total_bytes}"))
async with aiofiles.open(index_path, 'r') as f:
index_data = ModelSafetensorsIndex.model_validate_json(await f.read())
metadata = index_data.metadata
if metadata is not None:
return metadata.total_size
print(f"Warning: Could not extract total_size from safetensors index metadata for {model_id}. Metadata: {index_data.model_dump_json()}")
except EntryNotFoundError:
print(f"Warning: model.safetensors.index.json not found for {model_id}.")
except json.JSONDecodeError:
print(f"Error: Failed to parse model.safetensors.index.json for {model_id}.")
except Exception as e:
print(f"Error: Error processing model.safetensors.index.json for {model_id}: {e}")
print(f"Warning: Could not determine safetensors total size from index for {model_id}. Falling back to model_info API call.")
try:
info = model_info(model_id)
if info.safetensors is not None:
return info.safetensors.total
print(f"Warning: Could not get safetensors total size from model_info API for {model_id}. Safetensors info: {info}")
except HfHubHTTPError as e:
print(f"Error: HTTP Error while fetching model info from API for {model_id}: {e}")
except Exception as e:
print(f"Error: Error getting total size from huggingface info API for {model_id}: {e}")
return None
_model_meta_cache: Dict[str, ModelMetadata] = {}
async def get_model_meta(model_id: str) -> ModelMetadata:
if model_id in _model_meta_cache:
return _model_meta_cache[model_id]
model_meta = await _get_model_meta(model_id)
_model_meta_cache[model_id] = model_meta
return model_meta
async def _get_model_meta(model_id: str) -> ModelMetadata:
"""Fetches storage size and number of layers for a Hugging Face model, returns Pydantic ModelMeta."""
model_card = MODEL_CARDS[model_id]
num_layers_val: Optional[int] = None
mem_size_bytes_val: Optional[int] = None
try:
config_data = await get_config_data(model_id)
# get_num_layers is synchronous
num_layers_val = get_num_layers(config_data, model_id)
mem_size_bytes_val = await get_safetensors_size(model_id)
except HfHubHTTPError as e:
print(f"Error: HTTP Error encountered for '{model_id}': {e}")
except Exception as e:
print(f"Error: Unexpected error during metadata fetching for '{model_id}': {e}")
# Fallbacks for missing metadata
if mem_size_bytes_val is None:
print(f"Warning: Could not determine model size for {model_id}. Defaulting to 0 bytes.")
mem_size_bytes_val = 0
if num_layers_val is None:
print(f"Warning: Could not determine number of layers for {model_id}. Defaulting to 0 layers.")
num_layers_val = 0
return ModelMetadata(
model_id=model_id,
pretty_name=model_card.name,
storage_size_kilobytes=mem_size_bytes_val // 1024,
n_layers=num_layers_val,
)
worker/download/shard_downloader.py
+96
View File
@@ -0,0 +1,96 @@
from abc import ABC, abstractmethod
from datetime import timedelta
from pathlib import Path
from typing import AsyncIterator, Callable
from shared.types.worker.shards import (
PartitionStrategy,
PipelineShardMetadata,
ShardMetadata,
)
from worker.download.download_utils import RepoDownloadProgress
class ShardDownloader(ABC):
@abstractmethod
async def ensure_shard(self, shard: ShardMetadata, config_only: bool = False) -> Path:
"""
Ensures that the shard is downloaded.
Does not allow multiple overlapping downloads at once.
If you try to download a Shard which overlaps a Shard that is already being downloaded,
the download will be cancelled and a new download will start.
Args:
shard (Shard): The shard to download.
inference_engine_name (str): The inference engine used on the node hosting the shard
"""
@abstractmethod
def on_progress(self, callback: Callable[[ShardMetadata, RepoDownloadProgress], None]) -> None:
pass
@abstractmethod
async def get_shard_download_status(self) -> AsyncIterator[tuple[Path, RepoDownloadProgress]]:
"""Get the download status of shards.
Yields:
tuple[Path, RepoDownloadProgress]: The path and progress of a shard download.
"""
yield (
Path("/tmp/noop_shard"),
RepoDownloadProgress(
repo_id="noop",
repo_revision="noop",
shard=PipelineShardMetadata(
model_id="noop",
partition_strategy=PartitionStrategy.pipeline,
device_rank=0,
world_size=1,
start_layer=0,
end_layer=0,
n_layers=1,
),
completed_files=0,
total_files=0,
downloaded_bytes=0,
downloaded_bytes_this_session=0,
total_bytes=0,
overall_speed=0,
overall_eta=timedelta(seconds=0),
status="complete",
)
)
class NoopShardDownloader(ShardDownloader):
async def ensure_shard(self, shard: ShardMetadata, config_only: bool = False) -> Path:
return Path("/tmp/noop_shard")
def on_progress(self, callback: Callable[[ShardMetadata, RepoDownloadProgress], None]) -> None:
pass
async def get_shard_download_status(self) -> AsyncIterator[tuple[Path, RepoDownloadProgress]]:
yield (
Path("/tmp/noop_shard"),
RepoDownloadProgress(
repo_id="noop",
repo_revision="noop",
shard=PipelineShardMetadata(
model_id="noop",
partition_strategy=PartitionStrategy.pipeline,
device_rank=0,
world_size=1,
start_layer=0,
end_layer=0,
n_layers=1,
),
completed_files=0,
total_files=0,
downloaded_bytes=0,
downloaded_bytes_this_session=0,
total_bytes=0,
overall_speed=0,
overall_eta=timedelta(seconds=0),
status="complete",
)
)
worker/download/test_download.py
+54
View File
@@ -0,0 +1,54 @@
import time
import pytest
from shared.types.models import ModelId
from shared.types.worker.shards import PartitionStrategy, PipelineShardMetadata
from worker.download.impl_shard_downloader import exo_shard_downloader
from worker.download.shard_downloader import ShardDownloader
@pytest.mark.asyncio
async def test_shard_downloader():
shard_downloader: ShardDownloader = exo_shard_downloader()
shard_downloader.on_progress(
lambda shard, progress: print(f"Download progress: {progress}")
)
shard_metadata = PipelineShardMetadata(
model_id=ModelId("mlx-community/Llama-3.2-1B-Instruct-4bit"),
partition_strategy=PartitionStrategy.pipeline,
device_rank=0,
world_size=1,
start_layer=0,
end_layer=100,
n_layers=100,
)
path = await shard_downloader.ensure_shard(shard_metadata)
assert path.exists()
downloaded_model_path = path.parent / "mlx-community--Llama-3.2-1B-Instruct-4bit"
assert (downloaded_model_path / "config.json").exists()
assert (downloaded_model_path / "model.safetensors").exists()
assert (downloaded_model_path / "model.safetensors.index.json").exists()
assert (downloaded_model_path / "special_tokens_map.json").exists()
assert (downloaded_model_path / "tokenizer.json").exists()
assert (downloaded_model_path / "tokenizer_config.json").exists()
expected_files_and_sizes = [
("config.json", 1121),
("model.safetensors", 695283921),
("model.safetensors.index.json", 26159),
("special_tokens_map.json", 296),
("tokenizer.json", 17209920),
("tokenizer_config.json", 54558),
]
for filename, expected_size in expected_files_and_sizes:
file_path = downloaded_model_path / filename
assert file_path.stat().st_size == expected_size, f"{filename} size mismatch"
start_time = time.monotonic()
path_again = await shard_downloader.ensure_shard(shard_metadata)
duration = time.monotonic() - start_time
assert path_again == path
assert duration < 5, f"Second call to ensure_shard took too long: {duration:.2f}s"
worker/main.py
+6 -3
View File
@@ -1,6 +1,6 @@
import asyncio
import os
from asyncio.queues import Queue
from asyncio import Queue
from functools import partial
from logging import Logger
from typing import AsyncGenerator, Optional
@@ -39,6 +39,7 @@ from shared.types.worker.runners import (
RunningRunnerStatus,
)
from shared.types.worker.shards import ShardMetadata
from worker.download.download_utils import build_model_path
from worker.runner.runner_supervisor import RunnerSupervisor
@@ -56,7 +57,7 @@ class AssignedRunner(BaseModel):
@property
def is_downloaded(self) -> bool:
# TODO: Do this properly with huggingface validating each of the files.
return os.path.exists(self.shard_metadata.model_path)
return os.path.exists(build_model_path(self.shard_metadata.model_id))
def status_update_event(self) -> RunnerStatusUpdated:
return RunnerStatusUpdated(
@@ -334,7 +335,9 @@ class Worker:
# Handle state updates
async def _loop(self):
while True:
state_copy = self.state.model_copy(deep=True)
state_copy = self.state.model_copy(deep=False)
state_copy.task_inbox = []
state_copy.task_outbox = []
op: RunnerOp | None = self.plan(state_copy)
worker/tests/conftest.py
+2 -4
View File
@@ -30,7 +30,7 @@ from worker.main import Worker
@pytest.fixture
def pipeline_shard_meta():
def pipeline_shard_meta(tmp_path: Path):
def _pipeline_shard_meta(
num_nodes: int = 1, device_rank: int = 0
) -> PipelineShardMetadata:
@@ -46,9 +46,7 @@ def pipeline_shard_meta():
return PipelineShardMetadata(
device_rank=device_rank,
model_id=ModelId(uuid.uuid4()),
model_path=Path(
"~/.exo/models/mlx-community--Llama-3.2-1B-Instruct-4bit/"
).expanduser(),
n_layers=total_layers,
start_layer=start_layer,
end_layer=end_layer,
world_size=num_nodes,
worker/tests/test_serdes.py
+2
View File
@@ -1,3 +1,4 @@
from pathlib import Path
from typing import Callable, TypeVar
from pydantic import BaseModel, TypeAdapter
@@ -26,6 +27,7 @@ def assert_equal_serdes(obj: T, typeadapter: TypeAdapter[T]):
def test_supervisor_setup_message_serdes(
pipeline_shard_meta: Callable[..., PipelineShardMetadata],
hosts: Callable[..., list[Host]],
tmp_path: Path,
):
setup_message = SetupMessage(
model_shard_meta=pipeline_shard_meta(1, 0),
worker/tests/test_supervisor.py
+6
View File
@@ -1,4 +1,5 @@
import asyncio
from pathlib import Path
from typing import Callable
import pytest
@@ -26,6 +27,7 @@ async def test_supervisor_single_node_response(
pipeline_shard_meta: Callable[..., PipelineShardMetadata],
hosts: Callable[..., list[Host]],
chat_task: Task,
tmp_path: Path,
):
"""Test that asking for the capital of France returns 'Paris' in the response"""
model_shard_meta = pipeline_shard_meta(1, 0)
@@ -62,6 +64,7 @@ async def test_supervisor_two_node_response(
pipeline_shard_meta: Callable[..., PipelineShardMetadata],
hosts: Callable[..., list[Host]],
chat_task: Task,
tmp_path: Path,
):
"""Test that asking for the capital of France returns 'Paris' in the response"""
supervisor_0 = await RunnerSupervisor.create(
@@ -116,6 +119,7 @@ async def test_supervisor_early_stopping(
pipeline_shard_meta: Callable[..., PipelineShardMetadata],
hosts: Callable[..., list[Host]],
chat_task: Task,
tmp_path: Path,
):
"""Test that asking for the capital of France returns 'Paris' in the response"""
model_shard_meta = pipeline_shard_meta(1, 0)
@@ -166,6 +170,7 @@ async def test_supervisor_handles_terminated_runner(
pipeline_shard_meta: Callable[..., PipelineShardMetadata],
hosts: Callable[..., list[Host]],
chat_task: Task,
tmp_path: Path,
):
"""Test that the supervisor handles a terminated runner"""
model_shard_meta = pipeline_shard_meta(1, 0)
@@ -190,6 +195,7 @@ async def test_supervisor_handles_killed_runner(
pipeline_shard_meta: Callable[..., PipelineShardMetadata],
hosts: Callable[..., list[Host]],
chat_task: Task,
tmp_path: Path,
):
"""Test that the supervisor handles a killed runner"""
model_shard_meta = pipeline_shard_meta(1, 0)
worker/tests/test_worker_handlers.py
+8 -7
View File
@@ -1,6 +1,7 @@
## Tests for worker state handlers
import asyncio
from pathlib import Path
from typing import Callable
import pytest
@@ -35,7 +36,7 @@ def user_message():
return "What, according to Douglas Adams, is the meaning of life, the universe and everything?"
@pytest.mark.asyncio
async def test_assign_op(worker: Worker, instance: Callable[[NodeId], Instance]):
async def test_assign_op(worker: Worker, instance: Callable[[NodeId], Instance], tmp_path: Path):
await worker.start()
await asyncio.sleep(0.01)
@@ -67,7 +68,7 @@ async def test_assign_op(worker: Worker, instance: Callable[[NodeId], Instance])
assert isinstance(worker.assigned_runners[runner_id].status, ReadyRunnerStatus)
@pytest.mark.asyncio
async def test_unassign_op(worker_with_assigned_runner: tuple[Worker, RunnerId, Instance]):
async def test_unassign_op(worker_with_assigned_runner: tuple[Worker, RunnerId, Instance], tmp_path: Path):
worker, runner_id, _ = worker_with_assigned_runner
unassign_op = UnassignRunnerOp(
@@ -84,7 +85,7 @@ async def test_unassign_op(worker_with_assigned_runner: tuple[Worker, RunnerId,
assert len(events) == 0
@pytest.mark.asyncio
async def test_runner_up_op(worker_with_assigned_runner: tuple[Worker, RunnerId, Instance], chat_task: Task):
async def test_runner_up_op(worker_with_assigned_runner: tuple[Worker, RunnerId, Instance], chat_task: Task, tmp_path: Path):
worker, runner_id, _ = worker_with_assigned_runner
runner_up_op = RunnerUpOp(runner_id=runner_id)
@@ -117,7 +118,7 @@ async def test_runner_up_op(worker_with_assigned_runner: tuple[Worker, RunnerId,
await runner.astop() # Neat cleanup.
@pytest.mark.asyncio
async def test_runner_down_op(worker_with_running_runner: tuple[Worker, RunnerId, Instance]):
async def test_runner_down_op(worker_with_running_runner: tuple[Worker, RunnerId, Instance], tmp_path: Path):
worker, runner_id, _ = worker_with_running_runner
runner_down_op = RunnerDownOp(runner_id=runner_id)
@@ -130,7 +131,7 @@ async def test_runner_down_op(worker_with_running_runner: tuple[Worker, RunnerId
assert isinstance(events[0].runner_status, ReadyRunnerStatus)
@pytest.mark.asyncio
async def test_download_op(worker_with_assigned_runner: tuple[Worker, RunnerId, Instance]):
async def test_download_op(worker_with_assigned_runner: tuple[Worker, RunnerId, Instance], tmp_path: Path):
worker, runner_id, instance_obj = worker_with_assigned_runner
print(f'{worker.assigned_runners=}')
@@ -153,7 +154,7 @@ async def test_download_op(worker_with_assigned_runner: tuple[Worker, RunnerId,
@pytest.mark.asyncio
async def test_execute_task_op(
worker_with_running_runner: tuple[Worker, RunnerId, Instance],
chat_task: Task):
chat_task: Task, tmp_path: Path):
worker, runner_id, _ = worker_with_running_runner
execute_task_op = ExecuteTaskOp(
@@ -187,7 +188,7 @@ async def test_execute_task_op(
@pytest.mark.asyncio
async def test_execute_task_fails(
worker_with_running_runner: tuple[Worker, RunnerId, Instance],
chat_task: Task):
chat_task: Task, tmp_path: Path):
worker, runner_id, _ = worker_with_running_runner
messages = chat_task.task_params.messages
worker/tests/test_worker_plan.py
+3 -2
View File
@@ -23,6 +23,7 @@ from shared.types.worker.runners import (
ShardAssignments,
)
from shared.types.worker.shards import PipelineShardMetadata
from worker.download.download_utils import build_model_path
from worker.main import AssignedRunner, Worker
@@ -148,9 +149,9 @@ def _build_worker_state(
device_rank=0,
world_size=1,
model_id=model_id,
model_path=model_subdir,
start_layer=0,
end_layer=0,
n_layers=1,
)
shard_assignments = ShardAssignments(
@@ -233,7 +234,7 @@ def test_worker_plan(case: PlanTestCase, tmp_path: Path, monkeypatch: pytest.Mon
)
worker.assigned_runners[ctx.runner_id] = assigned_runner
path_downloaded_map[str(ctx.shard_metadata.model_path)] = runner_case.downloaded
path_downloaded_map[str(build_model_path(ctx.shard_metadata.model_id))] = runner_case.downloaded
# Stub filesystem existence check ------------------------------------------------------
from worker import main as worker_main # local import for module-scoped os