"vscode:/vscode.git/clone" did not exist on "68cf1601d3ccac7b7a661390d972a2469a7b4c61"
Commit c721b814 authored by zhuwenwen's avatar zhuwenwen
Browse files

sync v0.15.1

parent d53fe7e5
...@@ -1056,7 +1056,7 @@ class OpenPanguModel(nn.Module): ...@@ -1056,7 +1056,7 @@ class OpenPanguModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -1286,7 +1286,7 @@ class OpenPanguModelBase(nn.Module, SupportsPP, SupportsLoRA): ...@@ -1286,7 +1286,7 @@ class OpenPanguModelBase(nn.Module, SupportsPP, SupportsLoRA):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -1375,4 +1375,4 @@ class PanguUltraMoEForCausalLM(OpenPanguMoEModel): ...@@ -1375,4 +1375,4 @@ class PanguUltraMoEForCausalLM(OpenPanguMoEModel):
class PanguProMoEV2ForCausalLM(OpenPanguMoEModel): class PanguProMoEV2ForCausalLM(OpenPanguMoEModel):
pass pass
\ No newline at end of file
...@@ -104,7 +104,7 @@ class OpenPanguMTP(nn.Module): ...@@ -104,7 +104,7 @@ class OpenPanguMTP(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
hidden_states: torch.Tensor, hidden_states: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
...@@ -262,4 +262,4 @@ class OpenPanguMTP(nn.Module): ...@@ -262,4 +262,4 @@ class OpenPanguMTP(nn.Module):
elif shared_weight: elif shared_weight:
# treat shared weights as top level weights # treat shared weights as top level weights
name = name.replace(f"model.layers.{spec_layer}.", "model.") name = name.replace(f"model.layers.{spec_layer}.", "model.")
return name return name
\ No newline at end of file
...@@ -267,7 +267,7 @@ class OPTDecoder(nn.Module): ...@@ -267,7 +267,7 @@ class OPTDecoder(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -316,7 +316,7 @@ class OPTModel(nn.Module): ...@@ -316,7 +316,7 @@ class OPTModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -399,7 +399,7 @@ class OPTForCausalLM(nn.Module, SupportsPP, SupportsLoRA): ...@@ -399,7 +399,7 @@ class OPTForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -423,4 +423,4 @@ class OPTForCausalLM(nn.Module, SupportsPP, SupportsLoRA): ...@@ -423,4 +423,4 @@ class OPTForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
["lm_head.weight"] if self.config.tie_word_embeddings else None ["lm_head.weight"] if self.config.tie_word_embeddings else None
), ),
) )
return loader.load_weights(weights, mapper=self.hf_to_vllm_mapper) return loader.load_weights(weights, mapper=self.hf_to_vllm_mapper)
\ No newline at end of file
...@@ -253,7 +253,7 @@ class OrionModel(nn.Module): ...@@ -253,7 +253,7 @@ class OrionModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -343,7 +343,7 @@ class OrionForCausalLM(nn.Module, SupportsPP): ...@@ -343,7 +343,7 @@ class OrionForCausalLM(nn.Module, SupportsPP):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -362,4 +362,4 @@ class OrionForCausalLM(nn.Module, SupportsPP): ...@@ -362,4 +362,4 @@ class OrionForCausalLM(nn.Module, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(self) loader = AutoWeightsLoader(self)
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -357,7 +357,7 @@ class OuroModel(nn.Module): ...@@ -357,7 +357,7 @@ class OuroModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -482,7 +482,7 @@ class OuroForCausalLM(nn.Module, SupportsLoRA): ...@@ -482,7 +482,7 @@ class OuroForCausalLM(nn.Module, SupportsLoRA):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -504,4 +504,4 @@ class OuroForCausalLM(nn.Module, SupportsLoRA): ...@@ -504,4 +504,4 @@ class OuroForCausalLM(nn.Module, SupportsLoRA):
self, self,
skip_prefixes=(["lm_head."] if self.config.tie_word_embeddings else None), skip_prefixes=(["lm_head."] if self.config.tie_word_embeddings else None),
) )
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -525,7 +525,7 @@ class Ovis(nn.Module, SupportsMultiModal, SupportsPP): ...@@ -525,7 +525,7 @@ class Ovis(nn.Module, SupportsMultiModal, SupportsPP):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -552,4 +552,4 @@ class Ovis(nn.Module, SupportsMultiModal, SupportsPP): ...@@ -552,4 +552,4 @@ class Ovis(nn.Module, SupportsMultiModal, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(self) loader = AutoWeightsLoader(self)
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -632,7 +632,7 @@ class Ovis2_5(nn.Module, SupportsMultiModal, SupportsPP): ...@@ -632,7 +632,7 @@ class Ovis2_5(nn.Module, SupportsMultiModal, SupportsPP):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -659,4 +659,4 @@ class Ovis2_5(nn.Module, SupportsMultiModal, SupportsPP): ...@@ -659,4 +659,4 @@ class Ovis2_5(nn.Module, SupportsMultiModal, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(self) loader = AutoWeightsLoader(self)
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -1159,7 +1159,7 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support ...@@ -1159,7 +1159,7 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -1227,4 +1227,4 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support ...@@ -1227,4 +1227,4 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(self) loader = AutoWeightsLoader(self)
autoloaded_weights = loader.load_weights(weights, mapper=self.hf_to_vllm_mapper) autoloaded_weights = loader.load_weights(weights, mapper=self.hf_to_vllm_mapper)
return autoloaded_weights return autoloaded_weights
\ No newline at end of file
...@@ -389,7 +389,7 @@ class PaliGemmaForConditionalGeneration( ...@@ -389,7 +389,7 @@ class PaliGemmaForConditionalGeneration(
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -425,4 +425,4 @@ class PaliGemmaForConditionalGeneration( ...@@ -425,4 +425,4 @@ class PaliGemmaForConditionalGeneration(
return num_image_tokens return num_image_tokens
def get_num_mm_connector_tokens(self, num_vision_tokens: int) -> int: def get_num_mm_connector_tokens(self, num_vision_tokens: int) -> int:
return num_vision_tokens return num_vision_tokens
\ No newline at end of file
...@@ -271,7 +271,7 @@ class PersimmonModel(nn.Module): ...@@ -271,7 +271,7 @@ class PersimmonModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -348,7 +348,7 @@ class PersimmonForCausalLM(nn.Module, SupportsPP): ...@@ -348,7 +348,7 @@ class PersimmonForCausalLM(nn.Module, SupportsPP):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -370,4 +370,4 @@ class PersimmonForCausalLM(nn.Module, SupportsPP): ...@@ -370,4 +370,4 @@ class PersimmonForCausalLM(nn.Module, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(self) loader = AutoWeightsLoader(self)
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -234,7 +234,7 @@ class PhiModel(nn.Module): ...@@ -234,7 +234,7 @@ class PhiModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -340,7 +340,7 @@ class PhiForCausalLM(nn.Module, SupportsLoRA, SupportsPP): ...@@ -340,7 +340,7 @@ class PhiForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -360,4 +360,4 @@ class PhiForCausalLM(nn.Module, SupportsLoRA, SupportsPP): ...@@ -360,4 +360,4 @@ class PhiForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(self) loader = AutoWeightsLoader(self)
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -686,7 +686,7 @@ class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP, SupportsQuant) ...@@ -686,7 +686,7 @@ class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP, SupportsQuant)
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -716,4 +716,4 @@ class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP, SupportsQuant) ...@@ -716,4 +716,4 @@ class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP, SupportsQuant)
if "embed_tokens.weight" not in autoloaded_weights: if "embed_tokens.weight" not in autoloaded_weights:
self.embed_tokens = self.language_model.model.embed_tokens self.embed_tokens = self.language_model.model.embed_tokens
autoloaded_weights.add("embed_tokens.weight") autoloaded_weights.add("embed_tokens.weight")
return autoloaded_weights return autoloaded_weights
\ No newline at end of file
...@@ -1211,7 +1211,7 @@ class Phi4MMForCausalLM(nn.Module, SupportsLoRA, SupportsMultiModal): ...@@ -1211,7 +1211,7 @@ class Phi4MMForCausalLM(nn.Module, SupportsLoRA, SupportsMultiModal):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -1248,4 +1248,4 @@ class Phi4MMForCausalLM(nn.Module, SupportsLoRA, SupportsMultiModal): ...@@ -1248,4 +1248,4 @@ class Phi4MMForCausalLM(nn.Module, SupportsLoRA, SupportsMultiModal):
language_model="model.", language_model="model.",
connector=["audio_projection_for_vision", "audio_projection"], connector=["audio_projection_for_vision", "audio_projection"],
tower_model=["vision_encoder", "embed_tokens_extend"], tower_model=["vision_encoder", "embed_tokens_extend"],
) )
\ No newline at end of file
...@@ -483,7 +483,7 @@ class PhiMoEModel(nn.Module): ...@@ -483,7 +483,7 @@ class PhiMoEModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -649,7 +649,7 @@ class PhiMoEForCausalLM(nn.Module, SupportsLoRA, SupportsPP): ...@@ -649,7 +649,7 @@ class PhiMoEForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -668,4 +668,4 @@ class PhiMoEForCausalLM(nn.Module, SupportsLoRA, SupportsPP): ...@@ -668,4 +668,4 @@ class PhiMoEForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
return loader.load_weights(weights) return loader.load_weights(weights)
def get_expert_mapping(self) -> list[tuple[str, str, int, str]]: def get_expert_mapping(self) -> list[tuple[str, str, int, str]]:
return self.model.get_expert_mapping() return self.model.get_expert_mapping()
\ No newline at end of file
...@@ -479,7 +479,7 @@ class PixtralForConditionalGeneration( ...@@ -479,7 +479,7 @@ class PixtralForConditionalGeneration(
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -1413,4 +1413,4 @@ class PixtralHFVisionModel(nn.Module): ...@@ -1413,4 +1413,4 @@ class PixtralHFVisionModel(nn.Module):
weight_loader = getattr(param, "weight_loader", default_weight_loader) weight_loader = getattr(param, "weight_loader", default_weight_loader)
weight_loader(param, loaded_weight) weight_loader(param, loaded_weight)
loaded_params.add(name) loaded_params.add(name)
return loaded_params return loaded_params
\ No newline at end of file
...@@ -775,7 +775,7 @@ class Plamo2Model(torch.nn.Module): ...@@ -775,7 +775,7 @@ class Plamo2Model(torch.nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -852,7 +852,7 @@ class Plamo2ForCausalLM( ...@@ -852,7 +852,7 @@ class Plamo2ForCausalLM(
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -996,4 +996,4 @@ class Plamo2ForCausalLM( ...@@ -996,4 +996,4 @@ class Plamo2ForCausalLM(
param = params_dict[name] param = params_dict[name]
weight_loader = getattr(param, "weight_loader", default_weight_loader) weight_loader = getattr(param, "weight_loader", default_weight_loader)
weight_loader(param, loaded_weight) weight_loader(param, loaded_weight)
\ No newline at end of file
...@@ -342,7 +342,7 @@ class Plamo3Model(nn.Module): ...@@ -342,7 +342,7 @@ class Plamo3Model(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -412,7 +412,7 @@ class Plamo3ForCausalLM(nn.Module, SupportsLoRA, SupportsPP): ...@@ -412,7 +412,7 @@ class Plamo3ForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -434,4 +434,4 @@ class Plamo3ForCausalLM(nn.Module, SupportsLoRA, SupportsPP): ...@@ -434,4 +434,4 @@ class Plamo3ForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
self, self,
skip_prefixes=(["lm_head."] if self.config.tie_word_embeddings else None), skip_prefixes=(["lm_head."] if self.config.tie_word_embeddings else None),
) )
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -232,7 +232,7 @@ class QWenModel(nn.Module): ...@@ -232,7 +232,7 @@ class QWenModel(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None, intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -366,7 +366,7 @@ class QWenLMHeadModel(QWenBaseModel, SupportsPP, SupportsLoRA): ...@@ -366,7 +366,7 @@ class QWenLMHeadModel(QWenBaseModel, SupportsPP, SupportsLoRA):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -374,4 +374,4 @@ class QWenLMHeadModel(QWenBaseModel, SupportsPP, SupportsLoRA): ...@@ -374,4 +374,4 @@ class QWenLMHeadModel(QWenBaseModel, SupportsPP, SupportsLoRA):
hidden_states = self.transformer( hidden_states = self.transformer(
input_ids, positions, intermediate_tensors, inputs_embeds input_ids, positions, intermediate_tensors, inputs_embeds
) )
return hidden_states return hidden_states
\ No newline at end of file
...@@ -417,7 +417,7 @@ class Qwen2Model(nn.Module): ...@@ -417,7 +417,7 @@ class Qwen2Model(nn.Module):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -575,7 +575,7 @@ class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP, SupportsEagle3): ...@@ -575,7 +575,7 @@ class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP, SupportsEagle3):
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -597,4 +597,4 @@ class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP, SupportsEagle3): ...@@ -597,4 +597,4 @@ class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP, SupportsEagle3):
self, self,
skip_prefixes=(["lm_head."] if self.config.tie_word_embeddings else None), skip_prefixes=(["lm_head."] if self.config.tie_word_embeddings else None),
) )
return loader.load_weights(weights) return loader.load_weights(weights)
\ No newline at end of file
...@@ -1298,7 +1298,7 @@ class Qwen2_5OmniThinkerForConditionalGeneration( ...@@ -1298,7 +1298,7 @@ class Qwen2_5OmniThinkerForConditionalGeneration(
def forward( def forward(
self, self,
input_ids: torch.Tensor | None, input_ids: torch.Tensor,
positions: torch.Tensor, positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None, intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None, inputs_embeds: torch.Tensor | None = None,
...@@ -1330,4 +1330,4 @@ class Qwen2_5OmniThinkerForConditionalGeneration( ...@@ -1330,4 +1330,4 @@ class Qwen2_5OmniThinkerForConditionalGeneration(
language_model="language_model", language_model="language_model",
connector="merger.", connector="merger.",
tower_model=["visual.", "audio_tower."], tower_model=["visual.", "audio_tower."],
) )
\ No newline at end of file
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