| /********************************************************* |
| * |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you 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 "cudnn_lrn.h" |
| #ifdef USE_CUDNN |
| #include "cudnn_utils.h" |
| |
| namespace singa { |
| RegisterLayerClass(cudnn_lrn, CudnnLRN); |
| CudnnLRN::~CudnnLRN() { |
| if (has_init_cudnn_) { |
| CUDNN_CHECK(cudnnDestroyLRNDescriptor(lrn_desc_)); |
| CUDNN_CHECK(cudnnDestroyTensorDescriptor(shape_desc_)); |
| } |
| } |
| void CudnnLRN::InitCudnn(const Shape& shape, DataType dtype) { |
| CHECK_EQ(shape.size(), 4u); |
| if (!has_init_cudnn_) { |
| mode_ = CUDNN_LRN_CROSS_CHANNEL_DIM1; |
| CUDNN_CHECK(cudnnCreateTensorDescriptor(&shape_desc_)); |
| CUDNN_CHECK(cudnnCreateLRNDescriptor(&lrn_desc_)); |
| CUDNN_CHECK(cudnnSetLRNDescriptor(lrn_desc_, local_size_, alpha_, beta_, k_)); |
| } |
| CUDNN_CHECK(cudnnSetTensor4dDescriptor(shape_desc_, CUDNN_TENSOR_NCHW, |
| GetCudnnDataType(dtype), shape[0], |
| shape[1], shape[2], shape[3])); |
| has_init_cudnn_ = true; |
| } |
| const Tensor CudnnLRN::Forward(int flag, const Tensor& input) { |
| auto shape = input.shape(); |
| auto dtype = input.data_type(); |
| if (!has_init_cudnn_) { |
| InitCudnn(shape, dtype); |
| } else { |
| int n, c, h, w, s; |
| cudnnDataType_t type; |
| CUDNN_CHECK(cudnnGetTensor4dDescriptor(shape_desc_, &type, |
| &n, &c, &h, &w, &s, &s, &s, &s)); |
| if (shape[0] != static_cast<size_t>(n)) |
| InitCudnn(shape, dtype); |
| CHECK(input.shape(1) == static_cast<size_t>(c) |
| && input.shape(2) == static_cast<size_t>(h) |
| && input.shape(3) == static_cast<size_t>(w)) |
| << "input sample shape should not change" |
| << "previous shape " << c << ", " << h << ", " << w |
| << "current shape " << input.shape(1) << ", " << input.shape(2) << ", " |
| << input.shape(3); |
| } |
| |
| Tensor output; |
| output.ResetLike(input); |
| output.device()->Exec([=](Context* ctx) { |
| Block* inblock = input.block(), * outblock = output.block(); |
| const float alpha = 1.0f, beta = 0.0f; |
| CUDNN_CHECK(cudnnLRNCrossChannelForward( |
| ctx->cudnn_handle, this->lrn_desc_, this->mode_, &alpha, |
| this->shape_desc_, inblock->data(), &beta, this->shape_desc_, |
| outblock->mutable_data())); |
| }, {input.block()}, {output.block()}); |
| |
| if (flag & kTrain) { |
| buf_.push(input); |
| buf_.push(output); |
| } |
| return output; |
| } |
| |
| const std::pair<Tensor, vector<Tensor>> CudnnLRN::Backward(int flag, |
| const Tensor& grad) { |
| vector<Tensor> param_grad; |
| Tensor dx; |
| CHECK(!buf_.empty()); |
| Tensor output = buf_.top(); |
| buf_.pop(); |
| Tensor input = buf_.top(); |
| buf_.pop(); |
| if ((flag & kTrain) == kTrain) { |
| dx.ResetLike(grad); |
| dx.device()->Exec([=](Context* ctx) { |
| Block* dyblock = grad.block(), * dxblock = dx.block(); |
| Block* yblock = output.block(), * xblock = input.block(); |
| float alpha = 1.0f, beta = 0.0f; |
| CUDNN_CHECK(cudnnLRNCrossChannelBackward( |
| ctx->cudnn_handle, this->lrn_desc_, this->mode_, &alpha, |
| this->shape_desc_, yblock->data(), this->shape_desc_, dyblock->data(), |
| this->shape_desc_, xblock->data(), &beta, this->shape_desc_, |
| dxblock->mutable_data())); |
| }, {output.block(), grad.block(), input.block()}, {dx.block()}); |
| } else { |
| LOG(ERROR) << "Do not call backward for evaluation phase"; |
| } |
| return std::make_pair(dx, param_grad); |
| } |
| } // namespace |
| |
| #endif // USE_CUDNN |