get_image_features 段错误(吐核)

[yanqiangmiffy]

段错误(吐核)

        inputs = self.clip_processor(images=image, return_tensors="pt").to(self.device)
        print("clip_processor",inputs)
        print("clip_processor",inputs['pixel_values'].shape)
        image_features = self.clip_model.get_image_features(pixel_values=inputs['pixel_values'])
        print("image_features", image_features.shape)

clip_processor {'pixel_values': tensor([[[[1.9011, 1.9303, 1.9011,  ..., 1.9011, 1.9011, 1.8865],
          [1.9303, 1.9303, 1.9303,  ..., 1.9011, 1.9303, 1.8865],
          [1.9011, 1.9303, 1.9011,  ..., 1.9011, 1.9303, 1.8865],
          ...,
          [1.9011, 1.9303, 1.9011,  ..., 1.8865, 1.9303, 1.8865],
          [1.9011, 1.9303, 1.9303,  ..., 1.9303, 1.9303, 1.8865],
          [1.9011, 1.9011, 1.9011,  ..., 1.8865, 1.9303, 1.9011]],

         [[1.8948, 1.9098, 1.9098,  ..., 1.9098, 1.9998, 1.8798],
          [1.9248, 2.0449, 2.0299,  ..., 1.9098, 2.0599, 1.8948],
          [1.8948, 1.9248, 1.9098,  ..., 1.9098, 2.0599, 1.9248],
          ...,
          [1.8948, 1.9848, 1.8948,  ..., 1.8798, 2.0299, 1.8798],
          [1.9248, 2.0449, 1.9248,  ..., 1.9698, 2.0599, 1.8948],
          [1.9098, 1.9698, 1.8948,  ..., 1.8648, 2.0149, 1.8798]],

         [[2.1032, 2.1175, 2.1032,  ..., 2.0890, 2.1175, 2.0748],
          [2.1175, 2.1459, 2.1459,  ..., 2.0890, 2.1459, 2.0748],
          [2.0890, 2.1032, 2.0890,  ..., 2.0890, 2.1459, 2.0748],
          ...,
          [2.0748, 2.1459, 2.0890,  ..., 2.0748, 2.1317, 2.0748],
          [2.0890, 2.1459, 2.1175,  ..., 2.1459, 2.1459, 2.0606],
          [2.1032, 2.1175, 2.0890,  ..., 2.0606, 2.1175, 2.0606]]]],
       device='cuda:0')}
clip_processor torch.Size([1, 3, 224, 224])
段错误(吐核)