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Results 1 - 2 of 2 for _create_depthwise_conv2d_model (0.24 sec)

  1. tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py

            """Performs a gather operation."""
            out = array_ops.gather_v2(self.w, input_tensor)
            return {'output': out}
    
        return GatherModel(use_variable)
    
      def _create_depthwise_conv2d_model(
          self,
          input_shape: Sequence[int],
          filter_shape: Sequence[int],
          has_bias: bool = False,
          has_batch_norm: bool = False,
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Mar 21 08:51:46 UTC 2024
    - 51.2K bytes
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  2. tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py

          enable_per_channel_quantization: bool,
      ):
        input_shape = [None, None, None, 3] if input_shape_dynamic else [1, 3, 4, 3]
        filter_shape = [2, 3, 3, 1]
        model = self._create_depthwise_conv2d_model(
            input_shape, filter_shape, has_bias, has_batch_norm, activation_fn
        )
        saved_model_save.save(model, self._input_saved_model_path)
    
        def data_gen() -> repr_dataset.RepresentativeDataset:
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri May 17 03:36:50 UTC 2024
    - 235.6K bytes
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