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Results 1 - 3 of 3 for _input_shapes (3.16 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
merge_fusion_with_dequantize: bool, ): lhs_dim_size, rhs_dim_size = dim_sizes input_shape = (*lhs_dim_size,) filter_shape = (*rhs_dim_size,) static_input_shape = [dim if dim is not None else 2 for dim in input_shape] model = self._create_matmul_model( input_shape, filter_shape, self._input_saved_model_path, bias_fn, activation_fn, )
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 51.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
int num_input_dims = ranked_input_type.getRank(); SmallVector<int32_t, 4> padding_begin(num_input_dims, 0); auto input_shape = ranked_input_type.getShape(); SmallVector<int32_t, 4> padding_end(input_shape.begin(), input_shape.end()); SmallVector<int32_t, 4> padding_strides(num_input_dims, 1); int begin_mask = strided_slice_op.getBeginMask();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 64.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/lower_static_tensor_list.cc
size_diff, scalar_zero); // Build the argument/result types for if branch function. auto input_shape = rewriter.create<TF::ShapeOp>( loc, tensorflow::GetTypeFromTFTensorShape({-1}, shape_dtype), input_handle); Type branch_args_type[] = {input_handle.getType(), input_shape.getType(), size_diff.getType(), size.getType()}; Type branch_result_type[] = {result_type};
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 70.7K bytes - Viewed (0)