/* * Copyright (C) 2017 The Android Open Source Project * * 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. */ #include "Operations.h" #include "CpuOperationUtils.h" #include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h" namespace android { namespace nn { bool concatenationFloat32(const std::vector& inputDataPtrs, const std::vector& inputShapes, int32_t axis, float* outputData, const Shape& outputShape) { int num_inputs = inputShapes.size(); std::vector*> inputDimsPtr(num_inputs); std::vector > inputDims(num_inputs); for (int i=0; i( getNumberOfDimensions(outputShape) - axis - 1, inputDataPtrs.data(), inputDimsPtr.data(), num_inputs, outputData, convertShapeToDims(outputShape)); return true; } bool concatenationQuant8(const std::vector& inputDataPtrs, const std::vector& inputShapes, int32_t axis, uint8_t* outputData, const Shape& outputShape) { int num_inputs = inputShapes.size(); std::vector*> inputDimsPtr(num_inputs); std::vector > inputDims(num_inputs); for (int i=0; i( getNumberOfDimensions(outputShape) - axis - 1, inputDataPtrs.data(), inputDimsPtr.data(), num_inputs, outputData, convertShapeToDims(outputShape)); return true; } } // namespace nn } // namespace android