[V0 Deprecation] Remove V0 logic from get_input_embeddings interface (#25242)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/model_executor/models/hyperclovax_vision.py

@@ -46,7 +46,8 @@ from vllm.sequence import IntermediateTensors
 from .clip import CLIPVisionModel
 from .interfaces import MultiModalEmbeddings, SupportsMultiModal, SupportsPP
 from .siglip import SiglipVisionModel
-from .utils import AutoWeightsLoader, init_vllm_registered_model, maybe_prefix
+from .utils import (AutoWeightsLoader, init_vllm_registered_model,
+                    maybe_prefix, merge_multimodal_embeddings)
 from .vision import get_vision_encoder_info
 
 EOT = "<|endofturn|>"
@@ -740,33 +741,20 @@ class HCXVisionForCausalLM(nn.Module, SupportsMultiModal, SupportsPP):
         self,
         input_ids: torch.Tensor,
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
-        **kwargs,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if (kwargs.get("pixel_values_images") is not None
-                or kwargs.get("pixel_values_videos")
-                is not None):  # v0 compatibility
-            multimodal_embeddings = self.get_multimodal_embeddings(**kwargs)
-        if multimodal_embeddings is not None:
-            multimodal_embeddings = torch.cat(multimodal_embeddings, dim=0)
-            _mask_image = input_ids == self.config.image_token_id
-            _mask_video = input_ids == self.config.video_token_id
-            assert _mask_image.sum() + _mask_video.sum() == len(
-                multimodal_embeddings)
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
+            inputs_embeds = merge_multimodal_embeddings(
+                input_ids,
+                inputs_embeds,
+                multimodal_embeddings,
+                placeholder_token_id=[
+                    self.config.image_token_id,
+                    self.config.video_token_id,
+                ],
+            )
 
-            if multimodal_embeddings.dtype != inputs_embeds.dtype:
-                multimodal_embeddings = multimodal_embeddings.to(
-                    dtype=inputs_embeds.dtype)
-            if multimodal_embeddings.device != inputs_embeds.device:
-                multimodal_embeddings = multimodal_embeddings.to(
-                    device=inputs_embeds.device)
-
-            if _mask_image.sum() > 0:
-                inputs_embeds[
-                    _mask_image] = multimodal_embeddings[:sum(_mask_image)]
-            if _mask_video.sum() > 0:
-                inputs_embeds[_mask_video] = multimodal_embeddings[
-                    -sum(_mask_video):]
         return inputs_embeds
 
     def forward(
@@ -783,8 +771,9 @@ class HCXVisionForCausalLM(nn.Module, SupportsMultiModal, SupportsPP):
         # NOTE: In v1, inputs_embeds is always generated at model runner, this
         # condition is for v0 compatibility.
         elif inputs_embeds is None:
-            inputs_embeds = self.get_input_embeddings(input_ids=input_ids,
-                                                      **kwargs)
+            multimodal_embeddings = self.get_multimodal_embeddings(**kwargs)
+            inputs_embeds = self.get_input_embeddings(input_ids,
+                                                      multimodal_embeddings)
             input_ids = None
         hidden_states = self.language_model.model(input_ids,
                                                   positions,

vllm/model_executor/models/interfaces.py

@@ -23,7 +23,6 @@ from vllm.utils import supports_kw
 from .interfaces_base import is_pooling_model
 
 if TYPE_CHECKING:
-    from vllm.attention import AttentionMetadata
     from vllm.config import VllmConfig
     from vllm.model_executor.models.utils import WeightsMapper
     from vllm.sequence import IntermediateTensors
@@ -97,33 +96,10 @@ class SupportsMultiModal(Protocol):
         """
         ...
 
-    # Only for models that support v0 chunked prefill
-    # TODO(ywang96): Remove this overload once v0 is deprecated
-    @overload
     def get_input_embeddings(
         self,
         input_ids: Tensor,
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
-        attn_metadata: Optional["AttentionMetadata"] = None,
-    ) -> Tensor:
-        ...
-
-    # TODO: Remove this overload once v0 is deprecated
-    @overload
-    def get_input_embeddings(
-        self,
-        input_ids: Tensor,
-        multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
-    ) -> Tensor:
-        ...
-
-    def get_input_embeddings(
-        self,
-        input_ids: Tensor,
-        multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
-        # Only necessary so that the v0 overload is valid
-        # TODO: Remove attn_metadata once v0 is deprecated
-        attn_metadata: Optional["AttentionMetadata"] = None,
     ) -> Tensor:
         """
         Returns the input embeddings merged from the text embeddings from 

vllm/model_executor/models/ultravox.py

@@ -13,9 +13,7 @@ from transformers import BatchFeature, ProcessorMixin
 from transformers.models.whisper import WhisperFeatureExtractor
 from transformers.models.whisper.modeling_whisper import WhisperEncoder
 
-from vllm import envs
 from vllm.config import VllmConfig
-from vllm.forward_context import get_forward_context
 from vllm.model_executor.layers.activation import MulAndSilu, get_act_fn
 from vllm.model_executor.layers.layernorm import RMSNorm
 from vllm.model_executor.model_loader import DefaultModelLoader
@@ -37,8 +35,7 @@ from .interfaces import (MultiModalEmbeddings, SupportsLoRA,
                          SupportsMultiModal, SupportsPP)
 from .utils import (AutoWeightsLoader, WeightsMapper, flatten_bn,
                     init_vllm_registered_model, maybe_prefix,
-                    merge_multimodal_embeddings,
-                    merge_multimodal_embeddings_from_map)
+                    merge_multimodal_embeddings)
 
 _AUDIO_PLACEHOLDER_OVERRIDE = "<|audio|>"
 _MAX_ENCODER_BATCH_SIZE = 16
@@ -568,17 +565,9 @@ class UltravoxModel(nn.Module, SupportsMultiModal, SupportsPP, SupportsLoRA):
             safe_input_ids)
         if multimodal_embeddings is not None and len(
                 multimodal_embeddings) > 0:
-
-            # TODO(ywang96): remove this block after v0 is deprecated.
-            if not envs.VLLM_USE_V1:
-                attn_metadata = get_forward_context().attn_metadata
-                merge_multimodal_embeddings_from_map(
-                    inputs_embeds, multimodal_embeddings,
-                    attn_metadata.multi_modal_placeholder_index_maps["audio"])
-            else:
-                inputs_embeds = merge_multimodal_embeddings(
-                    input_ids, inputs_embeds, multimodal_embeddings,
-                    self.config.audio_token_index)
+            inputs_embeds = merge_multimodal_embeddings(
+                input_ids, inputs_embeds, multimodal_embeddings,
+                self.config.audio_token_index)
         return inputs_embeds
 
     def forward(self,

vllm/model_executor/models/utils.py

@@ -15,7 +15,7 @@ import vllm.envs as envs
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
-from vllm.multimodal import MultiModalPlaceholderMap, NestedTensors
+from vllm.multimodal import NestedTensors
 from vllm.sequence import IntermediateTensors
 from vllm.utils import (get_cuda_view_from_cpu_tensor, is_pin_memory_available,
                         is_uva_available)
@@ -389,22 +389,6 @@ def _embedding_count_expression(embeddings: NestedTensors) -> str:
         _embedding_count_expression(inner) for inner in embeddings)
 
 
-def merge_multimodal_embeddings_from_map(
-        inputs_embeds: torch.Tensor, multimodal_embeddings: NestedTensors,
-        placeholder_map: MultiModalPlaceholderMap.IndexMap) -> torch.Tensor:
-    """
-    Merge ``multimodal_embeddings`` into ``inputs_embeds`` using the provided
-    placeholder map .
-
-    Note:
-        This updates ``inputs_embeds`` in place.
-    """
-    flattened_embeddings = _flatten_embeddings(multimodal_embeddings)
-    inputs_embeds[placeholder_map.dest] = flattened_embeddings[
-        placeholder_map.src].to(dtype=inputs_embeds.dtype)
-    return inputs_embeds
-
-
 def _merge_multimodal_embeddings(
     inputs_embeds: torch.Tensor,
     is_multimodal: torch.Tensor,