Revert "[V1] Scatter and gather placeholders in the model runner" (#16075)

vllm/v1/worker/utils.py

@@ -1,6 +1,4 @@
 # SPDX-License-Identifier: Apache-2.0
-from typing import Optional
-
 import torch
 
 
@@ -29,46 +27,3 @@ def sanity_check_mm_encoder_outputs(
         f"but got tensors with shapes {[e.shape for e in mm_embeddings]} "
         "instead. This is most likely due to incorrect implementation "
         "of the model's `get_multimodal_embeddings` method.")
-
-
-def scatter_mm_placeholders(
-    embeds: torch.Tensor,
-    is_embed: Optional[torch.Tensor],
-) -> torch.Tensor:
-    """
-    Scatter the multimodal embeddings into a contiguous tensor that represents
-    the placeholder tokens.
-
-    :class:`vllm.multimodal.processing.PromptUpdateDetails.is_embed`.
-
-    Args:
-        embeds: The multimodal embeddings.
-          Shape: `(num_embeds, embed_dim)`
-        is_embed: A boolean mask indicating which positions in the placeholder
-          tokens need to be filled with multimodal embeddings.
-          Shape: `(num_placeholders, num_embeds)`
-    """
-    if is_embed is None:
-        return embeds
-
-    placeholders = embeds.new_full(
-        (is_embed.shape[0], embeds.shape[-1]),
-        fill_value=torch.nan,
-    )
-    placeholders[is_embed] = embeds
-    return placeholders
-
-
-def gather_mm_placeholders(
-    placeholders: torch.Tensor,
-    is_embed: Optional[torch.Tensor],
-) -> torch.Tensor:
-    """
-    Reconstructs the embeddings from the placeholder tokens.
-
-    This is the operation of :func:`scatter_mm_placeholders`.
-    """
-    if is_embed is None:
-        return placeholders
-
-    return placeholders[is_embed]