/*
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* Copyright (C) 2018 The Android Open Source Project
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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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// Contains the implementation of the operations.
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#define LOG_TAG "Operations"
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#include "CpuOperationUtils.h"
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#include "Operations.h"
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#include "tensorflow/lite/kernels/internal/reference/legacy_reference_ops.h"
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#include "Tracing.h"
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namespace android {
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namespace nn {
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bool stridedSliceGeneric(const uint8_t* inputData, const Shape& inputShape,
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const int32_t* beginData, const int32_t* endData,
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const int32_t* stridesData, int32_t beginMask, int32_t endMask,
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int32_t shrinkAxisMask, uint8_t* outputData, const Shape& outputShape) {
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NNTRACE_TRANS("stridedSliceGeneric");
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// This Op only supports 1-4D cases and since we use the reference 4D
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// implementation, the 1-3D tensors are mapped to 4D.
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const int kMaxDim = 4;
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std::vector<int> starts;
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std::vector<int> stops;
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std::vector<int> strides;
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int32_t numInputDims = static_cast<int32_t>(getNumberOfDimensions(inputShape));
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for (int32_t idx = numInputDims - 1; idx >= 0; --idx) {
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starts.emplace_back(beginData[idx]);
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stops.emplace_back(endData[idx]);
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strides.emplace_back(stridesData[idx]);
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}
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for (int i = numInputDims; i < kMaxDim; i++) {
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starts.emplace_back(0);
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stops.emplace_back(1);
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strides.emplace_back(1);
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}
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beginMask = ReverseMaskBits(beginMask, numInputDims);
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endMask = ReverseMaskBits(endMask, numInputDims);
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shrinkAxisMask = ReverseMaskBits(shrinkAxisMask, numInputDims);
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if (inputShape.type == OperandType::TENSOR_FLOAT32) {
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NNTRACE_COMP_SWITCH("reference_ops::StridedSlice::float");
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tflite::reference_ops::StridedSlice(
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reinterpret_cast<const float*>(inputData), convertShapeToDims(inputShape),
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beginMask, endMask, shrinkAxisMask, starts, stops, strides,
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reinterpret_cast<float*>(outputData), convertShapeToDims(outputShape));
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} else if (inputShape.type == OperandType::TENSOR_FLOAT16) {
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NNTRACE_COMP_SWITCH("reference_ops::StridedSlice::float16");
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tflite::reference_ops::StridedSlice(
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reinterpret_cast<const _Float16*>(inputData), convertShapeToDims(inputShape),
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beginMask, endMask, shrinkAxisMask, starts, stops, strides,
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reinterpret_cast<_Float16*>(outputData), convertShapeToDims(outputShape));
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} else if (inputShape.type == OperandType::TENSOR_QUANT8_ASYMM) {
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NNTRACE_COMP_SWITCH("reference_ops::StridedSlice::uint8");
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tflite::reference_ops::StridedSlice(
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reinterpret_cast<const uint8_t*>(inputData), convertShapeToDims(inputShape),
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beginMask, endMask, shrinkAxisMask, starts, stops, strides,
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reinterpret_cast<uint8_t*>(outputData), convertShapeToDims(outputShape));
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} else {
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LOG(ERROR) << "Unsupported data type";
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return false;
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}
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return true;
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}
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} // namespace nn
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} // namespace android
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