Harry MellorandClaude Opus 5
8c1557a79c
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com> Signed-off-by: Harry Mellor <hej.mellor@gmail.com> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Helpers for testing both processors of the Transformers modelling backend."""
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import pytest
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from vllm.config import ModelConfig
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from vllm.model_executor.models.transformers.multimodal import (
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LegacyMultiModalProcessor,
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MultiModalDummyInputsBuilder,
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MultiModalProcessingInfo,
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MultiModalProcessor,
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OffsetsMultiModalProcessor,
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)
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from vllm.multimodal.cache import MultiModalProcessorOnlyCache
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from vllm.multimodal.processing import InputProcessingContext
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from vllm.tokenizers.registry import cached_tokenizer_from_config
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offsets_only = pytest.mark.skipif(
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MultiModalProcessor is not OffsetsMultiModalProcessor,
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reason="Replacement offsets are only used from transformers 5.15.0 onwards",
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)
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PROCESSOR_CLASSES = [
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pytest.param(LegacyMultiModalProcessor, id="legacy"),
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pytest.param(OffsetsMultiModalProcessor, id="offsets", marks=offsets_only),
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]
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def create_processor(model_id: str, processor_cls):
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"""Build a processor directly, because the registry only ever builds the one the
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installed transformers version selects, leaving the other path untested.
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"""
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model_config = ModelConfig(model=model_id, model_impl="transformers")
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ctx = InputProcessingContext(
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model_config, cached_tokenizer_from_config(model_config)
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)
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info = MultiModalProcessingInfo(ctx)
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return processor_cls(info, MultiModalDummyInputsBuilder(info))
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def create_cached_processor(model_id: str, processor_cls):
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"""Build a processor backed by a real multi-modal processor cache, and hand the
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cache back so a test can check it was actually used.
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"""
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model_config = ModelConfig(model=model_id, model_impl="transformers")
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model_config.multimodal_config.mm_processor_cache_gb = 4
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ctx = InputProcessingContext(
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model_config, cached_tokenizer_from_config(model_config)
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)
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info = MultiModalProcessingInfo(ctx)
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cache = MultiModalProcessorOnlyCache(model_config)
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return processor_cls(info, MultiModalDummyInputsBuilder(info), cache=cache), cache
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