tzhouamandClaude Fable 5.1
4e3e8a1ebc
Verbatim copy of the edge/omni-edge working tree (tracked diffs + untracked edge/local, tests/edge/local, docs/edge, pipeline files). Taken so that vLLM-Omni v0.29.0rc1 can be merged on a branch without touching the user's working tree. logs_edge/ and benchmark .npy outputs excluded. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
51 lines
2.1 KiB
Python
51 lines
2.1 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
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"""Pipelines for text models vLLM implements and Omni does not own.
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A model being in vLLM's registry does not make it reachable through
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``Omni(model=...)``: the orchestrator resolves a pipeline by ``model_type``
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before any weight is read, so a ``model_type`` with no entry fails early and
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opaquely. Spark-X2.5 hit exactly that; these tests pin the general case.
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"""
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from __future__ import annotations
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import pytest
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from vllm_omni.config.pipeline_registry import OMNI_PIPELINES
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from vllm_omni.config.stage_config import StageExecutionType
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from vllm_omni.config.vllm_native_pipelines import LLAMA_PIPELINE
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def test_llama_resolves_from_the_registry():
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"""MiniCPM5-2B declares model_type "llama"; without this entry the
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orchestrator cannot resolve it at all."""
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assert OMNI_PIPELINES["llama"] is LLAMA_PIPELINE
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def test_it_is_one_autoregressive_text_stage():
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assert LLAMA_PIPELINE.get_validation_errors() == []
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assert len(LLAMA_PIPELINE.stages) == 1
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stage = LLAMA_PIPELINE.stages[0]
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assert stage.execution_type is StageExecutionType.LLM_AR
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assert stage.input_sources == ()
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assert stage.final_output and stage.final_output_type == "text"
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assert stage.owns_tokenizer
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assert stage.model_arch == "LlamaForCausalLM"
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def test_the_stage_declares_no_cross_chunk_state():
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"""A causal LM's state is its KV cache, which the backend owns. Claiming
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otherwise would make the scheduler park requests to hold capacity."""
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assert not LLAMA_PIPELINE.stages[0].retains_state_across_chunks
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def test_registering_llama_is_keyed_on_architecture_not_checkpoint():
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"""Worth pinning because it is the surprising part: this entry covers every
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checkpoint whose config says "llama", not only the one it was added for.
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That is the right granularity — pipeline shape is a property of the
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architecture — but it is a claim about shape, not a verification of any
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particular weights."""
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assert LLAMA_PIPELINE.model_type == "llama"
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assert LLAMA_PIPELINE.hf_architectures == ("LlamaForCausalLM",)
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