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[4/N] Initialize MM components in context managers (M-P) (#32663)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2026-01-20 22:06:32 +08:00
committed by GitHub
parent bb9172030e
commit fda3f03eb2
24 changed files with 290 additions and 353 deletions
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59
vllm/model_executor/models/paddleocr_vl.py
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@@ -999,6 +999,13 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support
}
)
@classmethod
def get_placeholder_str(cls, modality: str, i: int) -> str | None:
if modality.startswith("image"):
return "<|IMAGE_START|><|IMAGE_PLACEHOLDER|><|IMAGE_END|>"
raise ValueError("Only image modality is supported")
def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
super().__init__()
config = vllm_config.model_config.hf_config
@@ -1008,22 +1015,24 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support
self.config = config
self.multimodal_config = multimodal_config
self.visual = SiglipVisionModel(
config=config.vision_config,
quant_config=quant_config,
multimodal_config=multimodal_config,
prefix=maybe_prefix(prefix, "visual"),
)
self.mlp_AR = Projector(config, config.vision_config)
with self._mark_tower_model(vllm_config, "image"):
self.visual = SiglipVisionModel(
config=config.vision_config,
quant_config=quant_config,
multimodal_config=multimodal_config,
prefix=maybe_prefix(prefix, "visual"),
)
self.mlp_AR = Projector(config, config.vision_config)
self.language_model = Ernie4_5ForCausalLM(
vllm_config=vllm_config,
prefix=maybe_prefix(prefix, "language_model"),
)
with self._mark_language_model(vllm_config):
self.language_model = language_model = Ernie4_5ForCausalLM(
vllm_config=vllm_config,
prefix=maybe_prefix(prefix, "language_model"),
)
for layer in self.language_model.model.layers:
if not isinstance(layer, PPMissingLayer):
layer.self_attn.rotary_emb.is_neox_style = True
for layer in language_model.model.layers:
if not isinstance(layer, PPMissingLayer):
layer.self_attn.rotary_emb.is_neox_style = True
self.make_empty_intermediate_tensors = (
self.language_model.make_empty_intermediate_tensors
@@ -1151,9 +1160,6 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support
return llm_positions, mrope_position_delta
def get_language_model(self) -> nn.Module:
return self.language_model
def _parse_and_validate_image_input(
self, **kwargs: object
) -> PaddleOCRImagePixelInputs | None:
@@ -1180,29 +1186,10 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support
if intermediate_tensors is not None:
inputs_embeds = None
elif inputs_embeds is None:
vision_embeddings = self.embed_multimodal(**kwargs)
is_multimodal = kwargs.pop("is_multimodal", None)
handle_oov_mm_token = kwargs.pop("handle_oov_mm_token", False)
inputs_embeds = self.embed_input_ids(
input_ids,
vision_embeddings,
is_multimodal=is_multimodal,
handle_oov_mm_token=handle_oov_mm_token,
)
input_ids = None
return self.language_model(
input_ids, positions, intermediate_tensors, inputs_embeds
)
@classmethod
def get_placeholder_str(cls, modality: str, i: int) -> str | None:
if modality.startswith("image"):
return "<|IMAGE_START|><|IMAGE_PLACEHOLDER|><|IMAGE_END|>"
raise ValueError("Only image modality is supported")
def encode_image(
self, pixel_values: torch.Tensor, image_grid_thw: torch.Tensor
) -> torch.Tensor: