- Sort Score
- Result 10 results
- Languages All
Results 1 - 2 of 2 for _create_depthwise_conv2d_model (0.29 sec)
-
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 - Viewed (0) -
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 - Viewed (0)