| /* Copyright 2017 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| #ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_STRIDED_SLICE_H_ |
| #define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_STRIDED_SLICE_H_ |
| |
| #include "tensorflow/lite/kernels/internal/common.h" |
| #include "tensorflow/lite/kernels/internal/compatibility.h" |
| #include "tensorflow/lite/kernels/internal/strided_slice_logic.h" |
| #include "tensorflow/lite/kernels/internal/types.h" |
| |
| namespace tflite { |
| |
| namespace reference_ops { |
| template <typename T> |
| inline void StridedSlice(const tflite::StridedSliceParams& op_params, |
| const RuntimeShape& unextended_input_shape, |
| const T* input_data, |
| const RuntimeShape& unextended_output_shape, |
| T* output_data) { |
| using strided_slice::LoopCondition; |
| using strided_slice::StartForAxis; |
| using strided_slice::StopForAxis; |
| // Note that the output_shape is not used herein. |
| tflite::StridedSliceParams params_copy = op_params; |
| |
| TFLITE_DCHECK_LE(unextended_input_shape.DimensionsCount(), 5); |
| TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 5); |
| const RuntimeShape input_shape = |
| RuntimeShape::ExtendedShape(5, unextended_input_shape); |
| const RuntimeShape output_shape = |
| RuntimeShape::ExtendedShape(5, unextended_output_shape); |
| |
| // Reverse and pad to 5 dimensions because that is what the runtime code |
| // requires (ie. all shapes must be 5D and are given backwards). |
| strided_slice::StridedSlicePadIndices(¶ms_copy, 5); |
| |
| const int start_0 = StartForAxis(params_copy, input_shape, 0); |
| const int stop_0 = StopForAxis(params_copy, input_shape, 0, start_0); |
| const int start_1 = StartForAxis(params_copy, input_shape, 1); |
| const int stop_1 = StopForAxis(params_copy, input_shape, 1, start_1); |
| const int start_2 = StartForAxis(params_copy, input_shape, 2); |
| const int stop_2 = StopForAxis(params_copy, input_shape, 2, start_2); |
| const int start_3 = StartForAxis(params_copy, input_shape, 3); |
| const int stop_3 = StopForAxis(params_copy, input_shape, 3, start_3); |
| const int start_4 = StartForAxis(params_copy, input_shape, 4); |
| const int stop_4 = StopForAxis(params_copy, input_shape, 4, start_4); |
| |
| T* out_ptr = output_data; |
| for (int offset_0 = start_0 * input_shape.Dims(1), |
| end_0 = stop_0 * input_shape.Dims(1), |
| step_0 = params_copy.strides[0] * input_shape.Dims(1); |
| !LoopCondition(offset_0, end_0, params_copy.strides[0]); |
| offset_0 += step_0) { |
| for (int offset_1 = (offset_0 + start_1) * input_shape.Dims(2), |
| end_1 = (offset_0 + stop_1) * input_shape.Dims(2), |
| step_1 = params_copy.strides[1] * input_shape.Dims(2); |
| !LoopCondition(offset_1, end_1, params_copy.strides[1]); |
| offset_1 += step_1) { |
| for (int offset_2 = (offset_1 + start_2) * input_shape.Dims(3), |
| end_2 = (offset_1 + stop_2) * input_shape.Dims(3), |
| step_2 = params_copy.strides[2] * input_shape.Dims(3); |
| !LoopCondition(offset_2, end_2, params_copy.strides[2]); |
| offset_2 += step_2) { |
| for (int offset_3 = (offset_2 + start_3) * input_shape.Dims(4), |
| end_3 = (offset_2 + stop_3) * input_shape.Dims(4), |
| step_3 = params_copy.strides[3] * input_shape.Dims(4); |
| !LoopCondition(offset_3, end_3, params_copy.strides[3]); |
| offset_3 += step_3) { |
| for (int offset_4 = offset_3 + start_4, end_4 = offset_3 + stop_4; |
| !LoopCondition(offset_4, end_4, params_copy.strides[4]); |
| offset_4 += params_copy.strides[4]) { |
| *out_ptr++ = input_data[offset_4]; |
| } |
| } |
| } |
| } |
| } |
| } |
| } // namespace reference_ops |
| } // namespace tflite |
| |
| #endif // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_STRIDED_SLICE_H_ |