Revert "fix: fix video input for qwen3-vl" (#11437)
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@@ -1126,11 +1126,6 @@ class MRotaryEmbedding(RotaryEmbedding):
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second_per_grid_ts: Optional[torch.Tensor] = None,
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second_per_grid_ts: Optional[torch.Tensor] = None,
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**kwargs,
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**kwargs,
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) -> Tuple[torch.Tensor, torch.Tensor]:
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) -> Tuple[torch.Tensor, torch.Tensor]:
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if model_type.startswith("qwen3_vl") and video_grid_thw is not None:
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video_grid_thw = torch.repeat_interleave(
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video_grid_thw, video_grid_thw[:, 0], dim=0
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)
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video_grid_thw[:, 0] = 1
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mrope_position_deltas = []
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mrope_position_deltas = []
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if input_ids is not None and (
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if input_ids is not None and (
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image_grid_thw is not None or video_grid_thw is not None
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image_grid_thw is not None or video_grid_thw is not None
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@@ -186,6 +186,7 @@ UNBALANCED_MODEL_LOADING_TIMEOUT_S = 300
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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if _is_npu:
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if _is_npu:
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import torch_npu
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import torch_npu
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@@ -624,22 +625,6 @@ class ModelRunner:
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"Setting hicache_io_backend to vanilla I/O, which may lead to suboptimal performance with small page sizes."
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"Setting hicache_io_backend to vanilla I/O, which may lead to suboptimal performance with small page sizes."
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)
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)
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if self.model_config.hf_config.model_type == "qwen3_vl_moe":
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if (
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quantization_config := getattr(
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self.model_config.hf_config, "quantization_config"
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)
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) is not None:
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text_config = self.model_config.hf_text_config
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weight_block_size_n = quantization_config["weight_block_size"][0]
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if (
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text_config.moe_intermediate_size
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// (self.tp_size // self.moe_ep_size)
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) % weight_block_size_n != 0:
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raise ValueError(
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f"For qwen3-vl-fp8 models, please make sure ({text_config.moe_intermediate_size=} // ({self.tp_size=} // {self.moe_ep_size=})) % {weight_block_size_n=} == 0"
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)
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def init_torch_distributed(self):
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def init_torch_distributed(self):
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logger.info("Init torch distributed begin.")
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logger.info("Init torch distributed begin.")
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@@ -50,27 +50,6 @@ class TestQwen2VLServer(ImageOpenAITestMixin, VideoOpenAITestMixin):
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cls.base_url += "/v1"
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cls.base_url += "/v1"
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class TestQwen3VLServer(ImageOpenAITestMixin, VideoOpenAITestMixin):
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@classmethod
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def setUpClass(cls):
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cls.model = "Qwen/Qwen3-VL-30B-A3B-Instruct"
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.api_key = "sk-123456"
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cls.process = popen_launch_server(
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cls.model,
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cls.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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api_key=cls.api_key,
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other_args=[
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"--mem-fraction-static",
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"0.80",
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"--cuda-graph-max-bs",
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"4",
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],
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)
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cls.base_url += "/v1"
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class TestQwen2_5_VLServer(ImageOpenAITestMixin, VideoOpenAITestMixin):
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class TestQwen2_5_VLServer(ImageOpenAITestMixin, VideoOpenAITestMixin):
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@classmethod
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@classmethod
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def setUpClass(cls):
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def setUpClass(cls):
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@@ -494,7 +494,7 @@ class VideoOpenAITestMixin(TestOpenAIOmniServerBase):
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**(self.get_vision_request_kwargs()),
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**(self.get_vision_request_kwargs()),
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)
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)
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video_response = response.choices[0].message.content.lower()
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video_response = response.choices[0].message.content
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print("-" * 30)
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print("-" * 30)
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print(f"Video response:\n{video_response}")
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print(f"Video response:\n{video_response}")
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@@ -502,10 +502,9 @@ class VideoOpenAITestMixin(TestOpenAIOmniServerBase):
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# Add assertions to validate the video response
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# Add assertions to validate the video response
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assert (
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assert (
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"ipod" in video_response
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"iPod" in video_response
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or "device" in video_response
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or "device" in video_response
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or "microphone" in video_response
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or "microphone" in video_response
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or "phone" in video_response
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), f"video_response: {video_response}, should contain 'iPod' or 'device'"
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), f"video_response: {video_response}, should contain 'iPod' or 'device'"
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assert (
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assert (
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"man" in video_response
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"man" in video_response
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