[VLM] Move supported limits and max tokens to merged multi-modal processor (#11669)
Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk> Signed-off-by: Isotr0py <2037008807@qq.com> Co-authored-by: Isotr0py <2037008807@qq.com>
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@@ -538,6 +538,11 @@ def _test_processing_cache_correctness(
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else:
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hf_overrides = {}
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limit_mm_per_prompt = {
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modality: 3 if supports_multi else 1
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for modality, supports_multi in modalities.items()
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}
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model_config = ModelConfig(
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model_id,
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task="auto",
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@@ -548,6 +553,7 @@ def _test_processing_cache_correctness(
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dtype="float16",
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revision=None,
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hf_overrides=hf_overrides,
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limit_mm_per_prompt=limit_mm_per_prompt,
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)
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model_cls = MULTIMODAL_REGISTRY._get_model_cls(model_config)
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@@ -580,18 +586,14 @@ def _test_processing_cache_correctness(
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min_wh=128,
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max_wh=256),
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"audio":
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partial(_rand_audio, rng, min_len=256, max_len=512, sr=16000),
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}
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input_max_count = {
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modality: 3 if supports_multi else 1
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for modality, supports_multi in modalities.items()
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partial(_rand_audio, rng, min_len=512, max_len=1024, sr=16000),
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}
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for batch_idx in range(num_batches):
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mm_data = {
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k:
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[(input_to_hit[k] if rng.rand() < hit_rate else input_factory[k]())
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for _ in range(rng.randint(input_max_count[k]))]
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for _ in range(rng.randint(limit_mm_per_prompt[k]))]
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for k in modalities
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}
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