Make Qwen3VL compatible with Transformers v5 (#34262)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com> Signed-off-by: Roger Wang <hey@rogerw.io> Co-authored-by: Roger Wang <hey@rogerw.io>
This commit is contained in:
@@ -1112,17 +1112,6 @@ class Qwen3VLMultiModalProcessor(BaseMultiModalProcessor[Qwen3VLProcessingInfo])
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}
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)
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class Qwen3LLMModel(Qwen3Model):
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def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
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super().__init__(vllm_config=vllm_config, prefix=prefix)
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vision_config = vllm_config.model_config.hf_config.vision_config
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if not get_pp_group().is_first_rank and hasattr(
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vision_config, "deepstack_visual_indexes"
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):
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assert self.start_layer >= len(vision_config.deepstack_visual_indexes), (
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"start_layer should be greater than or equal to "
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"len(deepstack_visual_indexes)"
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)
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def forward(
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self,
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input_ids: torch.Tensor | None,
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@@ -1178,7 +1167,7 @@ class Qwen3LLMModel(Qwen3Model):
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class Qwen3LLMForCausalLM(Qwen3ForCausalLM):
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def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
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super(Qwen3ForCausalLM, self).__init__()
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config = vllm_config.model_config.hf_config.text_config
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config = vllm_config.model_config.hf_config
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quant_config = vllm_config.quant_config
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self.config = config
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@@ -1298,7 +1287,18 @@ class Qwen3VLForConditionalGeneration(
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with self._mark_language_model(vllm_config):
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self.language_model = Qwen3LLMForCausalLM(
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vllm_config=vllm_config, prefix=maybe_prefix(prefix, "language_model")
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vllm_config=vllm_config.with_hf_config(config.text_config),
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prefix=maybe_prefix(prefix, "language_model"),
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)
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if not get_pp_group().is_first_rank and hasattr(
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config.vision_config, "deepstack_visual_indexes"
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):
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assert self.language_model.start_layer >= len(
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config.vision_config.deepstack_visual_indexes
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), (
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"start_layer should be greater than or equal to "
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"len(deepstack_visual_indexes)"
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)
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self.make_empty_intermediate_tensors = (
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@@ -48,7 +48,6 @@ from vllm.sequence import IntermediateTensors
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from .interfaces import MixtureOfExperts
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from .qwen3_moe import (
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Qwen3MoeDecoderLayer,
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Qwen3MoeForCausalLM,
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Qwen3MoeModel,
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Qwen3MoeSparseMoeBlock,
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@@ -83,27 +82,6 @@ class Qwen3VLMoeProcessingInfo(Qwen3VLProcessingInfo):
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}
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)
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class Qwen3MoeLLMModel(Qwen3MoeModel):
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def __init__(
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self,
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*,
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vllm_config: VllmConfig,
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prefix: str = "",
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decoder_layer_type: type[torch.nn.Module] = Qwen3MoeDecoderLayer,
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):
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super().__init__(
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vllm_config=vllm_config,
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prefix=prefix,
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decoder_layer_type=decoder_layer_type,
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)
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vision_config = vllm_config.model_config.hf_config.vision_config
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if not get_pp_group().is_first_rank and hasattr(
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vision_config, "deepstack_visual_indexes"
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):
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assert self.start_layer >= len(vision_config.deepstack_visual_indexes), (
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"start_layer should be greater than or equal to "
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"len(deepstack_visual_indexes)"
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)
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def forward(
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self,
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input_ids: torch.Tensor | None,
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@@ -352,7 +330,7 @@ class Qwen3MoeLLMModel(Qwen3MoeModel):
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class Qwen3MoeLLMForCausalLM(Qwen3MoeForCausalLM):
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def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
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super(Qwen3MoeForCausalLM, self).__init__()
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self.config = vllm_config.model_config.hf_config.text_config
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self.config = vllm_config.model_config.hf_config
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self.quant_config = vllm_config.quant_config
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self.model = Qwen3MoeLLMModel(
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vllm_config=vllm_config, prefix=maybe_prefix(prefix, "model")
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@@ -473,10 +451,20 @@ class Qwen3VLMoeForConditionalGeneration(
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with self._mark_language_model(vllm_config):
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self.language_model = Qwen3MoeLLMForCausalLM(
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vllm_config=vllm_config,
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vllm_config=vllm_config.with_hf_config(config.text_config),
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prefix=maybe_prefix(prefix, "language_model"),
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)
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if not get_pp_group().is_first_rank and hasattr(
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config.vision_config, "deepstack_visual_indexes"
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):
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assert self.language_model.start_layer >= len(
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config.vision_config.deepstack_visual_indexes
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), (
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"start_layer should be greater than or equal to "
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"len(deepstack_visual_indexes)"
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)
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# Whether to include the gate_up_proj mapping is determined by
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# the language model.
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self.packed_modules_mapping = (
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