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pyproject-
...
main
| Author | SHA1 | Date | |
|---|---|---|---|
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cd946742f7 | ||
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a5bc38ad1f | ||
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2a4e0d4629 | ||
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46a14153dd |
@@ -19,7 +19,7 @@ dependencies = [
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"anyio==4.11.0",
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"mlx==0.30.4; sys_platform == 'darwin'",
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"mlx[cpu]==0.30.4; sys_platform == 'linux'",
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"mlx-lm==0.30.5",
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"mlx-lm",
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"tiktoken>=0.12.0", # required for kimi k2 tokenizer
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"hypercorn>=0.18.0",
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"openai-harmony>=0.0.8",
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@@ -31,6 +31,8 @@ dependencies = [
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]
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[project.scripts]
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exo-master = "exo.master.main:main"
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exo-worker = "exo.worker.main:main"
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exo = "exo.main:main"
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# dependencies only required for development
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@@ -44,6 +46,12 @@ dev = [
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"ruff>=0.11.13",
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]
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# mlx[cuda] requires a newer version of mlx. the ideal on linux is: default to mlx[cpu] unless[cuda] specified.
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[project.optional-dependencies]
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# cuda = [
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# "mlx[cuda]==0.26.3",
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# ]
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###
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# workspace configuration
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###
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@@ -55,8 +63,8 @@ members = [
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[tool.uv.sources]
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exo_pyo3_bindings = { workspace = true }
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mlx-lm = { git = "https://github.com/ml-explore/mlx-lm", branch = "main" }
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# Uncomment to use local mlx/mlx-lm development versions:
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# mlx-lm = { git = "https://github.com/ml-explore/mlx-lm", branch = "main" }
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# mlx = { path = "/Users/Shared/mlx", editable=true }
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# mlx-lm = { path = "/Users/Shared/mlx-lm", editable=true }
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@@ -108,7 +116,7 @@ environments = [
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###
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[tool.ruff]
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extend-exclude = ["*mlx_typings/**", "rust/exo_pyo3_bindings/**"]
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extend-exclude = ["shared/protobufs/**", "*mlx_typings/**", "rust/exo_pyo3_bindings/**"]
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[tool.ruff.lint]
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extend-select = ["I", "N", "B", "A", "PIE", "SIM"]
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@@ -21,7 +21,7 @@ def exo_shard_downloader(max_parallel_downloads: int = 8) -> ShardDownloader:
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async def build_base_shard(model_id: ModelId) -> ShardMetadata:
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model_card = await ModelCard.from_hf(model_id)
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model_card = await ModelCard.load(model_id)
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return PipelineShardMetadata(
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model_card=model_card,
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device_rank=0,
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@@ -146,18 +146,6 @@ def chunk_to_response(
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)
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async def resolve_model_card(model_id: ModelId) -> ModelCard:
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if model_id in MODEL_CARDS:
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model_card = MODEL_CARDS[model_id]
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return model_card
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for card in MODEL_CARDS.values():
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if card.model_id == ModelId(model_id):
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return card
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return await ModelCard.from_hf(model_id)
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class API:
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def __init__(
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self,
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@@ -279,7 +267,7 @@ class API:
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async def place_instance(self, payload: PlaceInstanceParams):
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command = PlaceInstance(
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model_card=await resolve_model_card(payload.model_id),
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model_card=await ModelCard.load(payload.model_id),
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sharding=payload.sharding,
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instance_meta=payload.instance_meta,
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min_nodes=payload.min_nodes,
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@@ -296,7 +284,7 @@ class API:
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self, payload: CreateInstanceParams
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) -> CreateInstanceResponse:
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instance = payload.instance
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model_card = await resolve_model_card(instance.shard_assignments.model_id)
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model_card = await ModelCard.load(instance.shard_assignments.model_id)
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required_memory = model_card.storage_size
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available_memory = self._calculate_total_available_memory()
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@@ -324,7 +312,7 @@ class API:
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instance_meta: InstanceMeta = InstanceMeta.MlxRing,
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min_nodes: int = 1,
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) -> Instance:
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model_card = await resolve_model_card(model_id)
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model_card = await ModelCard.load(model_id)
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try:
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placements = get_instance_placements(
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@@ -565,7 +553,7 @@ class API:
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text_parts: list[str] = []
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tool_calls: list[ToolCall] = []
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model: str | None = None
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model: ModelId | None = None
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finish_reason: FinishReason | None = None
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usage: Usage | None = None
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@@ -624,7 +612,7 @@ class API:
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) -> BenchChatCompletionResponse:
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text_parts: list[str] = []
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tool_calls: list[ToolCall] = []
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model: str | None = None
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model: ModelId | None = None
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finish_reason: FinishReason | None = None
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stats: GenerationStats | None = None
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@@ -677,7 +665,7 @@ class API:
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)
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return resp
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async def _trigger_notify_user_to_download_model(self, model_id: str) -> None:
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async def _trigger_notify_user_to_download_model(self, model_id: ModelId) -> None:
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logger.warning(
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"TODO: we should send a notification to the user to download the model"
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)
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@@ -686,7 +674,7 @@ class API:
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self, payload: ChatCompletionTaskParams
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) -> ChatCompletionResponse | StreamingResponse:
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"""Handle chat completions, supporting both streaming and non-streaming responses."""
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model_card = await resolve_model_card(ModelId(payload.model))
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model_card = await ModelCard.load(ModelId(payload.model))
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payload.model = model_card.model_id
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if not any(
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@@ -713,7 +701,7 @@ class API:
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async def bench_chat_completions(
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self, payload: BenchChatCompletionTaskParams
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) -> BenchChatCompletionResponse:
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model_card = await resolve_model_card(ModelId(payload.model))
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model_card = await ModelCard.load(ModelId(payload.model))
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payload.model = model_card.model_id
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if not any(
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@@ -733,12 +721,12 @@ class API:
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response = await self._collect_chat_completion_with_stats(command.command_id)
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return response
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async def _validate_image_model(self, model: str) -> ModelId:
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async def _validate_image_model(self, model: ModelId) -> ModelId:
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"""Validate model exists and return resolved model ID.
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Raises HTTPException 404 if no instance is found for the model.
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"""
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model_card = await resolve_model_card(ModelId(model))
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model_card = await ModelCard.load(model)
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resolved_model = model_card.model_id
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if not any(
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instance.shard_assignments.model_id == resolved_model
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@@ -784,7 +772,7 @@ class API:
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When stream=True and partial_images > 0, returns a StreamingResponse
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with SSE-formatted events for partial and final images.
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"""
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payload.model = await self._validate_image_model(payload.model)
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payload.model = await self._validate_image_model(ModelId(payload.model))
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command = ImageGeneration(
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request_params=payload,
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@@ -1029,7 +1017,7 @@ class API:
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async def bench_image_generations(
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self, request: Request, payload: BenchImageGenerationTaskParams
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) -> BenchImageGenerationResponse:
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payload.model = await self._validate_image_model(payload.model)
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payload.model = await self._validate_image_model(ModelId(payload.model))
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payload.stream = False
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payload.partial_images = 0
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@@ -1050,7 +1038,7 @@ class API:
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self,
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image: UploadFile,
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prompt: str,
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model: str,
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model: ModelId,
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n: int,
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size: str,
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response_format: Literal["url", "b64_json"],
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@@ -1145,7 +1133,7 @@ class API:
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command = await self._send_image_edits_command(
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image=image,
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prompt=prompt,
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model=model,
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model=ModelId(model),
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n=n,
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size=size,
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response_format=response_format,
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@@ -1201,7 +1189,7 @@ class API:
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command = await self._send_image_edits_command(
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image=image,
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prompt=prompt,
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model=model,
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model=ModelId(model),
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n=n,
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size=size,
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response_format=response_format,
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@@ -216,6 +216,8 @@ def get_node_id_keypair(
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Obtains the :class:`Keypair` associated with this node-ID.
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Obtain the :class:`PeerId` by from it.
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"""
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# TODO(evan): bring back node id persistence once we figure out how to deal with duplicates
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return Keypair.generate_ed25519()
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def lock_path(path: str | bytes | PathLike[str] | PathLike[bytes]) -> Path:
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return Path(str(path) + ".lock")
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@@ -8,7 +8,7 @@ from multiprocessing.synchronize import Event as EventT
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from multiprocessing.synchronize import Semaphore as SemaphoreT
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from loguru import logger
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from pytest import LogCaptureFixture
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from pytest import LogCaptureFixture, mark
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from exo.routing.router import get_node_id_keypair
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from exo.shared.constants import EXO_NODE_ID_KEYPAIR
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@@ -74,6 +74,7 @@ def _delete_if_exists(p: str | bytes | os.PathLike[str] | os.PathLike[bytes]):
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os.remove(p)
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@mark.skip(reason="this functionality is currently disabled but may return in future")
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def test_node_id_fetching(caplog: LogCaptureFixture):
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reps = 10
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@@ -3,6 +3,7 @@ from copy import deepcopy
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from typing import Any, cast
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import mlx.core as mx
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import psutil
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from mlx_lm.models.cache import (
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KVCache,
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QuantizedKVCache,
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@@ -12,25 +13,29 @@ from mlx_lm.models.cache import (
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from mlx_lm.models.gpt_oss import Model as GptOssModel
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from mlx_lm.tokenizer_utils import TokenizerWrapper
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from exo.shared.types.memory import Memory
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from exo.shared.types.mlx import KVCacheType
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from exo.worker.engines.mlx import Model
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from exo.worker.engines.mlx.constants import CACHE_GROUP_SIZE, KV_CACHE_BITS
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from exo.worker.runner.bootstrap import logger
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# Fraction of device memory above which LRU eviction kicks in
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_DEFAULT_MEMORY_THRESHOLD = 0.85
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_DEFAULT_MEMORY_THRESHOLD = 0.9
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_MEMORY_THRESHOLD = float(
|
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os.environ.get("EXO_MEMORY_THRESHOLD", _DEFAULT_MEMORY_THRESHOLD)
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)
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|
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|
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class KVPrefixCache:
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def __init__(self, tokenizer: TokenizerWrapper):
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def __init__(
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self, tokenizer: TokenizerWrapper, group: mx.distributed.Group | None = None
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):
|
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self.prompts: list[mx.array] = [] # mx array of tokens (ints)
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self.caches: list[KVCacheType] = []
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self._last_used: list[int] = [] # monotonic counter of last access per entry
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self._access_counter: int = 0
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self._tokenizer: TokenizerWrapper = tokenizer
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self._group = group
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def clear(self):
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"""Clear all cached prompts and caches."""
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@@ -81,13 +86,13 @@ class KVPrefixCache:
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best_snapshot_index, best_snapshot_length = None, 0
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for i, cached_prompt in enumerate(self.prompts):
|
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length = _get_prefix_length(tokenized_prompt, cached_prompt)
|
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length = get_prefix_length(tokenized_prompt, cached_prompt)
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|
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if length == max_length:
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# Exact match - cached prompt starts with our entire prompt
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# Trim cache to prompt length - 1, return last token for stream_generate
|
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prompt_cache = deepcopy(self.caches[i])
|
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cached_length = _cache_length(self.caches[i])
|
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cached_length = cache_length(self.caches[i])
|
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tokens_to_trim = cached_length - (max_length - 1)
|
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if tokens_to_trim > 0:
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trim_prompt_cache(cast(list[Any], prompt_cache), tokens_to_trim)
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@@ -109,7 +114,7 @@ class KVPrefixCache:
|
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prompt_cache = deepcopy(self.caches[best_snapshot_index])
|
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|
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# Trim removes tokens from the end, so we trim (cached_length - prefix_length) to keep the prefix
|
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cached_length = _cache_length(self.caches[best_snapshot_index])
|
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cached_length = cache_length(self.caches[best_snapshot_index])
|
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tokens_to_trim = cached_length - best_snapshot_length
|
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if tokens_to_trim > 0:
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trim_prompt_cache(cast(list[Any], prompt_cache), tokens_to_trim)
|
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@@ -131,29 +136,37 @@ class KVPrefixCache:
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return prompt_cache, tokenized_prompt, None
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def _evict_if_needed(self):
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"""Evict least recently used entries while memory pressure is high."""
|
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"""Evict least recently used entries while memory usage is high."""
|
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if len(self.caches) == 0:
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return
|
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|
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active: int = mx.metal.get_active_memory()
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limit = int(mx.metal.device_info()["max_recommended_working_set_size"])
|
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if active < limit * _MEMORY_THRESHOLD:
|
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return
|
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|
||||
# Evict LRU entries until below threshold or only one entry left
|
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while len(self.caches) > 0:
|
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while (
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len(self.caches) > 1
|
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and self.get_memory_used_percentage() > _MEMORY_THRESHOLD
|
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):
|
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lru_index = self._last_used.index(min(self._last_used))
|
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evicted_tokens = len(self.prompts[lru_index])
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self.prompts.pop(lru_index)
|
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self.caches.pop(lru_index)
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self._last_used.pop(lru_index)
|
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logger.info(
|
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f"KV cache evicted LRU entry ({evicted_tokens} tokens) due to memory pressure"
|
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f"KV cache evicted LRU entry ({evicted_tokens} tokens) due to memory usage"
|
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)
|
||||
|
||||
active = mx.metal.get_active_memory()
|
||||
if active < limit * _MEMORY_THRESHOLD:
|
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break
|
||||
def get_memory_used_percentage(self) -> float:
|
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local_pressure: float = get_memory_used_percentage()
|
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|
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if self._group is None:
|
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return local_pressure
|
||||
|
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all_pressure = mx.distributed.all_gather(
|
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mx.array([local_pressure], dtype=mx.float32),
|
||||
group=self._group,
|
||||
)
|
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# .item() evals.
|
||||
max_pressure = float(mx.max(all_pressure).item())
|
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return max_pressure
|
||||
|
||||
|
||||
def encode_prompt(tokenizer: TokenizerWrapper, prompt: str) -> mx.array:
|
||||
@@ -168,13 +181,13 @@ def encode_prompt(tokenizer: TokenizerWrapper, prompt: str) -> mx.array:
|
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return mx.array(tokenized_prompt)
|
||||
|
||||
|
||||
def _cache_length(cache: KVCacheType) -> int:
|
||||
def cache_length(cache: KVCacheType) -> int:
|
||||
"""Get the number of tokens in a KV cache."""
|
||||
# Use .offset attribute which all cache types have (len() not implemented in older QuantizedKVCache)
|
||||
return max(c.offset for c in cache) # type: ignore
|
||||
|
||||
|
||||
def _get_prefix_length(prompt: mx.array, cached_prompt: mx.array) -> int:
|
||||
def get_prefix_length(prompt: mx.array, cached_prompt: mx.array) -> int:
|
||||
"""Find the length of the common prefix between two token arrays."""
|
||||
n = min(int(prompt.shape[0]), int(cached_prompt.shape[0]))
|
||||
if n == 0:
|
||||
@@ -185,6 +198,17 @@ def _get_prefix_length(prompt: mx.array, cached_prompt: mx.array) -> int:
|
||||
return int(mx.sum(prefix_mask).item())
|
||||
|
||||
|
||||
def get_available_memory() -> Memory:
|
||||
mem: int = psutil.virtual_memory().available
|
||||
return Memory.from_bytes(mem)
|
||||
|
||||
|
||||
def get_memory_used_percentage() -> float:
|
||||
mem = psutil.virtual_memory()
|
||||
# percent is 0-100
|
||||
return float(mem.percent / 100)
|
||||
|
||||
|
||||
def make_kv_cache(
|
||||
model: Model, max_kv_size: int | None = None, keep: int = 0
|
||||
) -> KVCacheType:
|
||||
|
||||
@@ -37,6 +37,7 @@ from exo.shared.types.tasks import (
|
||||
Shutdown,
|
||||
StartWarmup,
|
||||
Task,
|
||||
TaskId,
|
||||
TaskStatus,
|
||||
)
|
||||
from exo.shared.types.worker.instances import BoundInstance
|
||||
@@ -111,8 +112,12 @@ def main(
|
||||
event_sender.send(
|
||||
RunnerStatusUpdated(runner_id=runner_id, runner_status=current_status)
|
||||
)
|
||||
seen = set[TaskId]()
|
||||
with task_receiver as tasks:
|
||||
for task in tasks:
|
||||
if task.task_id in seen:
|
||||
logger.warning("repeat task - potential error")
|
||||
seen.add(task.task_id)
|
||||
event_sender.send(
|
||||
TaskStatusUpdated(task_id=task.task_id, task_status=TaskStatus.Running)
|
||||
)
|
||||
@@ -163,7 +168,7 @@ def main(
|
||||
logger.info(
|
||||
f"model has_tool_calling={tokenizer.has_tool_calling}"
|
||||
)
|
||||
kv_prefix_cache = KVPrefixCache(tokenizer)
|
||||
kv_prefix_cache = KVPrefixCache(tokenizer, group)
|
||||
|
||||
elif (
|
||||
ModelTask.TextToImage in shard_metadata.model_card.tasks
|
||||
|
||||
@@ -127,20 +127,25 @@ class RunnerSupervisor:
|
||||
self._tg.cancel_scope.cancel()
|
||||
|
||||
async def start_task(self, task: Task):
|
||||
if task.task_id in self.pending:
|
||||
logger.warning(
|
||||
f"Skipping invalid task {task} as it has already been submitted"
|
||||
)
|
||||
return
|
||||
if task.task_id in self.completed:
|
||||
logger.info(
|
||||
logger.warning(
|
||||
f"Skipping invalid task {task} as it has already been completed"
|
||||
)
|
||||
return
|
||||
logger.info(f"Starting task {task}")
|
||||
event = anyio.Event()
|
||||
self.pending[task.task_id] = event
|
||||
try:
|
||||
self._task_sender.send(task)
|
||||
await self._task_sender.send_async(task)
|
||||
except ClosedResourceError:
|
||||
logger.warning(f"Task {task} dropped, runner closed communication.")
|
||||
return
|
||||
await event.wait()
|
||||
logger.info(f"Finished task {task}")
|
||||
|
||||
async def _forward_events(self):
|
||||
with self._ev_recv as events:
|
||||
|
||||
@@ -14,9 +14,9 @@ from exo.shared.types.tasks import ChatCompletionTaskParams
|
||||
from exo.worker.engines.mlx import Model
|
||||
from exo.worker.engines.mlx.cache import (
|
||||
KVPrefixCache,
|
||||
_cache_length,
|
||||
_get_prefix_length,
|
||||
cache_length,
|
||||
encode_prompt,
|
||||
get_prefix_length,
|
||||
make_kv_cache,
|
||||
)
|
||||
from exo.worker.engines.mlx.generator.generate import mlx_generate, prefill
|
||||
@@ -35,47 +35,47 @@ class TestGetPrefixLength:
|
||||
def test_identical_arrays(self):
|
||||
a = mx.array([1, 2, 3, 4, 5])
|
||||
b = mx.array([1, 2, 3, 4, 5])
|
||||
assert _get_prefix_length(a, b) == 5
|
||||
assert get_prefix_length(a, b) == 5
|
||||
|
||||
def test_no_common_prefix(self):
|
||||
a = mx.array([1, 2, 3])
|
||||
b = mx.array([4, 5, 6])
|
||||
assert _get_prefix_length(a, b) == 0
|
||||
assert get_prefix_length(a, b) == 0
|
||||
|
||||
def test_partial_prefix(self):
|
||||
a = mx.array([1, 2, 3, 4, 5])
|
||||
b = mx.array([1, 2, 3, 7, 8])
|
||||
assert _get_prefix_length(a, b) == 3
|
||||
assert get_prefix_length(a, b) == 3
|
||||
|
||||
def test_prompt_longer_than_cached(self):
|
||||
a = mx.array([1, 2, 3, 4, 5])
|
||||
b = mx.array([1, 2, 3])
|
||||
assert _get_prefix_length(a, b) == 3
|
||||
assert get_prefix_length(a, b) == 3
|
||||
|
||||
def test_cached_longer_than_prompt(self):
|
||||
a = mx.array([1, 2, 3])
|
||||
b = mx.array([1, 2, 3, 4, 5])
|
||||
assert _get_prefix_length(a, b) == 3
|
||||
assert get_prefix_length(a, b) == 3
|
||||
|
||||
def test_single_token_match(self):
|
||||
a = mx.array([1, 2, 3])
|
||||
b = mx.array([1, 5, 6])
|
||||
assert _get_prefix_length(a, b) == 1
|
||||
assert get_prefix_length(a, b) == 1
|
||||
|
||||
def test_empty_prompt(self):
|
||||
a = mx.array([]).astype(mx.int32)
|
||||
b = mx.array([1, 2, 3])
|
||||
assert _get_prefix_length(a, b) == 0
|
||||
assert get_prefix_length(a, b) == 0
|
||||
|
||||
def test_empty_cached(self):
|
||||
a = mx.array([1, 2, 3])
|
||||
b = mx.array([]).astype(mx.int32)
|
||||
assert _get_prefix_length(a, b) == 0
|
||||
assert get_prefix_length(a, b) == 0
|
||||
|
||||
def test_both_empty(self):
|
||||
a = mx.array([]).astype(mx.int32)
|
||||
b = mx.array([]).astype(mx.int32)
|
||||
assert _get_prefix_length(a, b) == 0
|
||||
assert get_prefix_length(a, b) == 0
|
||||
|
||||
|
||||
class TestKVPrefix:
|
||||
@@ -146,7 +146,7 @@ class TestKVPrefixCacheWithModel:
|
||||
prefill(model, tokenizer, make_sampler(0.0), tokens, cache)
|
||||
|
||||
# Cache should now hold the prompt tokens
|
||||
assert _cache_length(cache) == len(tokens)
|
||||
assert cache_length(cache) == len(tokens)
|
||||
|
||||
def test_add_and_get_exact_match(self, model_and_tokenizer):
|
||||
model, tokenizer = model_and_tokenizer
|
||||
@@ -166,7 +166,7 @@ class TestKVPrefixCacheWithModel:
|
||||
kv_prefix_cache.add_kv_cache(prompt, cache)
|
||||
|
||||
assert len(kv_prefix_cache.prompts) == 1
|
||||
stored_length = _cache_length(kv_prefix_cache.caches[0])
|
||||
stored_length = cache_length(kv_prefix_cache.caches[0])
|
||||
assert stored_length > 0
|
||||
|
||||
# Retrieve with same prompt: exact match
|
||||
@@ -209,7 +209,7 @@ class TestKVPrefixCacheWithModel:
|
||||
long_tokens = encode_prompt(tokenizer, long_prompt)
|
||||
|
||||
# The prompts share a prefix (chat template preamble + "Hi")
|
||||
expected_prefix = _get_prefix_length(long_tokens, short_tokens)
|
||||
expected_prefix = get_prefix_length(long_tokens, short_tokens)
|
||||
assert expected_prefix > 0, (
|
||||
"Prompts should share a prefix from the chat template"
|
||||
)
|
||||
@@ -243,7 +243,7 @@ class TestKVPrefixCacheWithModel:
|
||||
kv_prefix_cache = KVPrefixCache(tokenizer)
|
||||
kv_prefix_cache.add_kv_cache(prompt, cache)
|
||||
|
||||
stored_length = _cache_length(kv_prefix_cache.caches[0])
|
||||
stored_length = cache_length(kv_prefix_cache.caches[0])
|
||||
|
||||
# Get cache and mutate it (simulating what generation does)
|
||||
result_cache, _, matched_index = kv_prefix_cache.get_kv_cache(model, prompt)
|
||||
@@ -259,7 +259,7 @@ class TestKVPrefixCacheWithModel:
|
||||
mx.eval([c.keys for c in result_cache])
|
||||
|
||||
# Stored cache must be unchanged
|
||||
assert _cache_length(kv_prefix_cache.caches[0]) == stored_length
|
||||
assert cache_length(kv_prefix_cache.caches[0]) == stored_length
|
||||
|
||||
def test_stored_cache_survives_repeated_get_mutate_cycles(
|
||||
self, model_and_tokenizer
|
||||
@@ -281,7 +281,7 @@ class TestKVPrefixCacheWithModel:
|
||||
kv_prefix_cache = KVPrefixCache(tokenizer)
|
||||
kv_prefix_cache.add_kv_cache(prompt, cache)
|
||||
|
||||
stored_length = _cache_length(kv_prefix_cache.caches[0])
|
||||
stored_length = cache_length(kv_prefix_cache.caches[0])
|
||||
|
||||
for i in range(3):
|
||||
result_cache, _, _ = kv_prefix_cache.get_kv_cache(model, prompt)
|
||||
@@ -293,7 +293,7 @@ class TestKVPrefixCacheWithModel:
|
||||
layer_cache.update_and_fetch(extra, extra)
|
||||
mx.eval([c.keys for c in result_cache])
|
||||
|
||||
assert _cache_length(kv_prefix_cache.caches[0]) == stored_length, (
|
||||
assert cache_length(kv_prefix_cache.caches[0]) == stored_length, (
|
||||
f"Failed on loop {i}"
|
||||
)
|
||||
|
||||
@@ -325,7 +325,7 @@ class TestKVPrefixCacheWithModel:
|
||||
assert len(kv_prefix_cache.caches) == 1
|
||||
# Cache should contain prompt + generated tokens
|
||||
expected_length = len(prompt_tokens) + generated_tokens
|
||||
assert _cache_length(kv_prefix_cache.caches[0]) == expected_length
|
||||
assert cache_length(kv_prefix_cache.caches[0]) == expected_length
|
||||
|
||||
def test_mlx_generate_second_call_gets_prefix_hit(self, model_and_tokenizer):
|
||||
"""Second mlx_generate call with same prompt should get a prefix hit from stored cache."""
|
||||
@@ -400,7 +400,7 @@ class TestKVPrefixCacheWithModel:
|
||||
first_gen_time = time.perf_counter() - t0
|
||||
|
||||
assert len(kv_prefix_cache.prompts) == 1
|
||||
first_cache_length = _cache_length(kv_prefix_cache.caches[0])
|
||||
first_cache_length = cache_length(kv_prefix_cache.caches[0])
|
||||
|
||||
# Second generation: same long prompt + extra content (simulating multi-turn)
|
||||
task2 = ChatCompletionTaskParams(
|
||||
@@ -416,7 +416,7 @@ class TestKVPrefixCacheWithModel:
|
||||
prompt2_tokens = encode_prompt(tokenizer, prompt2)
|
||||
|
||||
# Verify the prompts share a long prefix
|
||||
prefix_len = _get_prefix_length(prompt2_tokens, prompt1_tokens)
|
||||
prefix_len = get_prefix_length(prompt2_tokens, prompt1_tokens)
|
||||
assert prefix_len > 1000, "Prompts must share > 1000 token prefix"
|
||||
|
||||
# Second generation should reuse the cached prefix (only prefill new tokens)
|
||||
@@ -440,7 +440,7 @@ class TestKVPrefixCacheWithModel:
|
||||
# With prefix_hit > 1000, should update in-place (not add a second entry)
|
||||
assert len(kv_prefix_cache.prompts) == 1
|
||||
# Updated cache should be longer (prompt2 + generated > prompt1 + generated)
|
||||
updated_cache_length = _cache_length(kv_prefix_cache.caches[0])
|
||||
updated_cache_length = cache_length(kv_prefix_cache.caches[0])
|
||||
assert updated_cache_length > first_cache_length
|
||||
|
||||
def test_mlx_generate_stored_cache_not_mutated(self, model_and_tokenizer):
|
||||
@@ -465,7 +465,7 @@ class TestKVPrefixCacheWithModel:
|
||||
):
|
||||
pass
|
||||
|
||||
first_cache_length = _cache_length(kv_prefix_cache.caches[0])
|
||||
firstcache_length = cache_length(kv_prefix_cache.caches[0])
|
||||
|
||||
# Second generation gets the cache and mutates it during generation
|
||||
for _response in mlx_generate(
|
||||
@@ -478,7 +478,7 @@ class TestKVPrefixCacheWithModel:
|
||||
pass
|
||||
|
||||
# The first stored cache must not have been mutated by the second generation
|
||||
assert _cache_length(kv_prefix_cache.caches[0]) == first_cache_length
|
||||
assert cache_length(kv_prefix_cache.caches[0]) == firstcache_length
|
||||
|
||||
def test_evicts_lru_entry_under_memory_pressure(self, model_and_tokenizer):
|
||||
"""Under memory pressure, adding a new cache entry evicts the least recently used one."""
|
||||
@@ -540,6 +540,6 @@ class TestKVPrefixCacheWithModel:
|
||||
assert len(kv_prefix_cache.prompts) == 1
|
||||
# The surviving entry should be the newly added one
|
||||
new_tokens = encode_prompt(tokenizer, prompt)
|
||||
assert _get_prefix_length(kv_prefix_cache.prompts[0], new_tokens) == len(
|
||||
assert get_prefix_length(kv_prefix_cache.prompts[0], new_tokens) == len(
|
||||
new_tokens
|
||||
)
|
||||
|
||||
@@ -109,8 +109,8 @@ def assert_events_equal(test_events: Iterable[Event], true_events: Iterable[Even
|
||||
|
||||
@pytest.fixture
|
||||
def patch_out_mlx(monkeypatch: pytest.MonkeyPatch):
|
||||
# initialize_mlx returns a "group" equal to 1
|
||||
monkeypatch.setattr(mlx_runner, "initialize_mlx", make_nothin(1))
|
||||
# initialize_mlx returns a mock group
|
||||
monkeypatch.setattr(mlx_runner, "initialize_mlx", make_nothin(MockGroup()))
|
||||
monkeypatch.setattr(mlx_runner, "load_mlx_items", make_nothin((1, MockTokenizer)))
|
||||
monkeypatch.setattr(mlx_runner, "warmup_inference", make_nothin(1))
|
||||
monkeypatch.setattr(mlx_runner, "_check_for_debug_prompts", nothin)
|
||||
@@ -147,6 +147,14 @@ class MockTokenizer:
|
||||
has_tool_calling = False
|
||||
|
||||
|
||||
class MockGroup:
|
||||
def rank(self) -> int:
|
||||
return 0
|
||||
|
||||
def size(self) -> int:
|
||||
return 1
|
||||
|
||||
|
||||
def _run(tasks: Iterable[Task]):
|
||||
bound_instance = get_bound_mlx_ring_instance(
|
||||
instance_id=INSTANCE_1_ID,
|
||||
|
||||
30
uv.lock
generated
30
uv.lock
generated
@@ -192,14 +192,20 @@ sdist = { url = "https://files.pythonhosted.org/packages/eb/56/b1ba7935a17738ae8
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/b0/1e/d22cc63332bd59b06481ceaac49d6c507598642e2230f201649058a7e704/cffi-2.0.0-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:07b271772c100085dd28b74fa0cd81c8fb1a3ba18b21e03d7c27f3436a10606b", size = 212446 },
|
||||
{ url = "https://files.pythonhosted.org/packages/a9/f5/a2c23eb03b61a0b8747f211eb716446c826ad66818ddc7810cc2cc19b3f2/cffi-2.0.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d48a880098c96020b02d5a1f7d9251308510ce8858940e6fa99ece33f610838b", size = 220101 },
|
||||
{ url = "https://files.pythonhosted.org/packages/f2/7f/e6647792fc5850d634695bc0e6ab4111ae88e89981d35ac269956605feba/cffi-2.0.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:f93fd8e5c8c0a4aa1f424d6173f14a892044054871c771f8566e4008eaa359d2", size = 207948 },
|
||||
{ url = "https://files.pythonhosted.org/packages/cb/1e/a5a1bd6f1fb30f22573f76533de12a00bf274abcdc55c8edab639078abb6/cffi-2.0.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:dd4f05f54a52fb558f1ba9f528228066954fee3ebe629fc1660d874d040ae5a3", size = 206422 },
|
||||
{ url = "https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c8d3b5532fc71b7a77c09192b4a5a200ea992702734a2e9279a37f2478236f26", size = 219499 },
|
||||
{ url = "https://files.pythonhosted.org/packages/50/e1/a969e687fcf9ea58e6e2a928ad5e2dd88cc12f6f0ab477e9971f2309b57c/cffi-2.0.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:d9b29c1f0ae438d5ee9acb31cadee00a58c46cc9c0b2f9038c6b0b3470877a8c", size = 222928 },
|
||||
{ url = "https://files.pythonhosted.org/packages/36/54/0362578dd2c9e557a28ac77698ed67323ed5b9775ca9d3fe73fe191bb5d8/cffi-2.0.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6d50360be4546678fc1b79ffe7a66265e28667840010348dd69a314145807a1b", size = 221302 },
|
||||
{ url = "https://files.pythonhosted.org/packages/d6/43/0e822876f87ea8a4ef95442c3d766a06a51fc5298823f884ef87aaad168c/cffi-2.0.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:24b6f81f1983e6df8db3adc38562c83f7d4a0c36162885ec7f7b77c7dcbec97b", size = 220049 },
|
||||
{ url = "https://files.pythonhosted.org/packages/b4/89/76799151d9c2d2d1ead63c2429da9ea9d7aac304603de0c6e8764e6e8e70/cffi-2.0.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:12873ca6cb9b0f0d3a0da705d6086fe911591737a59f28b7936bdfed27c0d47c", size = 207793 },
|
||||
{ url = "https://files.pythonhosted.org/packages/bb/dd/3465b14bb9e24ee24cb88c9e3730f6de63111fffe513492bf8c808a3547e/cffi-2.0.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:d9b97165e8aed9272a6bb17c01e3cc5871a594a446ebedc996e2397a1c1ea8ef", size = 206300 },
|
||||
{ url = "https://files.pythonhosted.org/packages/47/d9/d83e293854571c877a92da46fdec39158f8d7e68da75bf73581225d28e90/cffi-2.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:afb8db5439b81cf9c9d0c80404b60c3cc9c3add93e114dcae767f1477cb53775", size = 219244 },
|
||||
{ url = "https://files.pythonhosted.org/packages/2b/0f/1f177e3683aead2bb00f7679a16451d302c436b5cbf2505f0ea8146ef59e/cffi-2.0.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:737fe7d37e1a1bffe70bd5754ea763a62a066dc5913ca57e957824b72a85e205", size = 222828 },
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||||
{ url = "https://files.pythonhosted.org/packages/c6/0f/cafacebd4b040e3119dcb32fed8bdef8dfe94da653155f9d0b9dc660166e/cffi-2.0.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:38100abb9d1b1435bc4cc340bb4489635dc2f0da7456590877030c9b3d40b0c1", size = 220926 },
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||||
{ url = "https://files.pythonhosted.org/packages/be/b4/c56878d0d1755cf9caa54ba71e5d049479c52f9e4afc230f06822162ab2f/cffi-2.0.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:7cc09976e8b56f8cebd752f7113ad07752461f48a58cbba644139015ac24954c", size = 221593 },
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||||
{ url = "https://files.pythonhosted.org/packages/e0/0d/eb704606dfe8033e7128df5e90fee946bbcb64a04fcdaa97321309004000/cffi-2.0.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:92b68146a71df78564e4ef48af17551a5ddd142e5190cdf2c5624d0c3ff5b2e8", size = 209354 },
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||||
{ url = "https://files.pythonhosted.org/packages/d8/19/3c435d727b368ca475fb8742ab97c9cb13a0de600ce86f62eab7fa3eea60/cffi-2.0.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:b1e74d11748e7e98e2f426ab176d4ed720a64412b6a15054378afdb71e0f37dc", size = 208480 },
|
||||
{ url = "https://files.pythonhosted.org/packages/d0/44/681604464ed9541673e486521497406fadcc15b5217c3e326b061696899a/cffi-2.0.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:28a3a209b96630bca57cce802da70c266eb08c6e97e5afd61a75611ee6c64592", size = 221584 },
|
||||
{ url = "https://files.pythonhosted.org/packages/25/8e/342a504ff018a2825d395d44d63a767dd8ebc927ebda557fecdaca3ac33a/cffi-2.0.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:7553fb2090d71822f02c629afe6042c299edf91ba1bf94951165613553984512", size = 224443 },
|
||||
{ url = "https://files.pythonhosted.org/packages/e1/5e/b666bacbbc60fbf415ba9988324a132c9a7a0448a9a8f125074671c0f2c3/cffi-2.0.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:6c6c373cfc5c83a975506110d17457138c8c63016b563cc9ed6e056a82f13ce4", size = 223437 },
|
||||
@@ -305,8 +311,10 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/5c/49/498c86566a1d80e978b42f0d702795f69887005548c041636df6ae1ca64c/cryptography-46.0.3-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:01ca9ff2885f3acc98c29f1860552e37f6d7c7d013d7334ff2a9de43a449315d", size = 4450807 },
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Reference in New Issue
Block a user