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[Docs] add __init__.py to vllm/model_executor/layers/quantization/compressed_tensors/transform (#24974)
Signed-off-by: samzong <samzong.lu@gmail.com>
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@ -680,7 +680,7 @@ class Blip2ForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsPP,
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batch.
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Info:
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[Blip2ImageInputs][]
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[`Blip2ImageInputs`][vllm.model_executor.models.blip2.Blip2ImageInputs]
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"""
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if intermediate_tensors is not None:
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@ -737,7 +737,7 @@ class LlavaForConditionalGeneration(nn.Module, SupportsMultiModal, SupportsPP):
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inputs_embeds: Optional tensor of input embeddings.
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Info:
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[LlavaImageInputs][]
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[`LlavaImageInputs`][vllm.model_executor.models.llava.LlavaImageInputs]
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"""
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if intermediate_tensors is not None:
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inputs_embeds = None
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@ -527,7 +527,8 @@ class LlavaNextForConditionalGeneration(nn.Module, SupportsMultiModal,
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Unlike in LLaVA-1.5, the number of image tokens inputted to the language
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model depends on the original size of the input image. Including the
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original image token in the input, the required number of image tokens
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is given by [get_llava_next_image_feature_size][].
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is given by [`LlavaNextProcessingInfo.get_num_image_tokens`][vllm.\
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model_executor.models.llava_next.LlavaNextProcessingInfo.get_num_image_tokens].
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This way, the `positions` and `attn_metadata` are consistent
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with the `input_ids`.
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@ -540,7 +541,7 @@ class LlavaNextForConditionalGeneration(nn.Module, SupportsMultiModal,
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inputs_embeds: Optional tensor of input embeddings.
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Info:
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[LlavaNextImageInputs][]
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[`LlavaNextImageInputs`][vllm.model_executor.models.llava_next.LlavaNextImageInputs]
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"""
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if intermediate_tensors is not None:
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inputs_embeds = None
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