Commit c721b814 authored by zhuwenwen's avatar zhuwenwen
Browse files

sync v0.15.1

parent d53fe7e5
......@@ -1056,7 +1056,7 @@ class OpenPanguModel(nn.Module):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -1286,7 +1286,7 @@ class OpenPanguModelBase(nn.Module, SupportsPP, SupportsLoRA):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -1375,4 +1375,4 @@ class PanguUltraMoEForCausalLM(OpenPanguMoEModel):
class PanguProMoEV2ForCausalLM(OpenPanguMoEModel):
pass
pass
\ No newline at end of file
......@@ -104,7 +104,7 @@ class OpenPanguMTP(nn.Module):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
hidden_states: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
......@@ -262,4 +262,4 @@ class OpenPanguMTP(nn.Module):
elif shared_weight:
# treat shared weights as top level weights
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -316,7 +316,7 @@ class OPTModel(nn.Module):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -399,7 +399,7 @@ class OPTForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -423,4 +423,4 @@ class OPTForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
["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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -343,7 +343,7 @@ class OrionForCausalLM(nn.Module, SupportsPP):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -362,4 +362,4 @@ class OrionForCausalLM(nn.Module, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -482,7 +482,7 @@ class OuroForCausalLM(nn.Module, SupportsLoRA):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -504,4 +504,4 @@ class OuroForCausalLM(nn.Module, SupportsLoRA):
self,
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -552,4 +552,4 @@ class Ovis(nn.Module, SupportsMultiModal, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -659,4 +659,4 @@ class Ovis2_5(nn.Module, SupportsMultiModal, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
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
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -1227,4 +1227,4 @@ class PaddleOCRVLForConditionalGeneration(nn.Module, SupportsMultiModal, Support
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(self)
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(
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -425,4 +425,4 @@ class PaliGemmaForConditionalGeneration(
return num_image_tokens
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -348,7 +348,7 @@ class PersimmonForCausalLM(nn.Module, SupportsPP):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -370,4 +370,4 @@ class PersimmonForCausalLM(nn.Module, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -340,7 +340,7 @@ class PhiForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -360,4 +360,4 @@ class PhiForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
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)
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -716,4 +716,4 @@ class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP, SupportsQuant)
if "embed_tokens.weight" not in autoloaded_weights:
self.embed_tokens = self.language_model.model.embed_tokens
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -1248,4 +1248,4 @@ class Phi4MMForCausalLM(nn.Module, SupportsLoRA, SupportsMultiModal):
language_model="model.",
connector=["audio_projection_for_vision", "audio_projection"],
tower_model=["vision_encoder", "embed_tokens_extend"],
)
)
\ No newline at end of file
......@@ -483,7 +483,7 @@ class PhiMoEModel(nn.Module):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -649,7 +649,7 @@ class PhiMoEForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -668,4 +668,4 @@ class PhiMoEForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
return loader.load_weights(weights)
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(
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -1413,4 +1413,4 @@ class PixtralHFVisionModel(nn.Module):
weight_loader = getattr(param, "weight_loader", default_weight_loader)
weight_loader(param, loaded_weight)
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -852,7 +852,7 @@ class Plamo2ForCausalLM(
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -996,4 +996,4 @@ class Plamo2ForCausalLM(
param = params_dict[name]
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -412,7 +412,7 @@ class Plamo3ForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -434,4 +434,4 @@ class Plamo3ForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
self,
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
......@@ -366,7 +366,7 @@ class QWenLMHeadModel(QWenBaseModel, SupportsPP, SupportsLoRA):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -374,4 +374,4 @@ class QWenLMHeadModel(QWenBaseModel, SupportsPP, SupportsLoRA):
hidden_states = self.transformer(
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):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -575,7 +575,7 @@ class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP, SupportsEagle3):
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -597,4 +597,4 @@ class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP, SupportsEagle3):
self,
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(
def forward(
self,
input_ids: torch.Tensor | None,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
......@@ -1330,4 +1330,4 @@ class Qwen2_5OmniThinkerForConditionalGeneration(
language_model="language_model",
connector="merger.",
tower_model=["visual.", "audio_tower."],
)
)
\ No newline at end of file
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