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