| /* |
| * 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_dropout.h" |
| #ifdef USE_CUDNN |
| #include <cudnn.h> |
| // cudnn dropout is added in cudnn 5 |
| #if CUDNN_MAJOR >= 5 |
| |
| #include <chrono> |
| |
| #include "./cudnn_utils.h" |
| #include "singa/utils/logging.h" |
| |
| namespace singa { |
| RegisterLayerClass(cudnn_dropout, CudnnDropout); |
| CudnnDropout::~CudnnDropout() { |
| if (drop_desc_ != nullptr) |
| CUDNN_CHECK(cudnnDestroyDropoutDescriptor(drop_desc_)); |
| if (x_desc_ != nullptr) CUDNN_CHECK(cudnnDestroyTensorDescriptor(x_desc_)); |
| if (y_desc_ != nullptr) CUDNN_CHECK(cudnnDestroyTensorDescriptor(y_desc_)); |
| } |
| |
| void CudnnDropout::InitCudnn(int size, DataType dtype, |
| std::shared_ptr<Device> dev, Context* ctx) { |
| CHECK(!has_init_cudnn_); |
| CUDNN_CHECK(cudnnCreateTensorDescriptor(&x_desc_)); |
| CUDNN_CHECK(cudnnCreateTensorDescriptor(&y_desc_)); |
| CUDNN_CHECK(cudnnCreateDropoutDescriptor(&drop_desc_)); |
| |
| CUDNN_CHECK(cudnnSetTensor4dDescriptor( |
| x_desc_, CUDNN_TENSOR_NCHW, GetCudnnDataType(dtype), 1, 1, 1, size)); |
| CUDNN_CHECK(cudnnSetTensor4dDescriptor( |
| y_desc_, CUDNN_TENSOR_NCHW, GetCudnnDataType(dtype), 1, 1, 1, size)); |
| |
| cudnnDropoutGetStatesSize(ctx->cudnn_handle, &state_size_); |
| state_ = Tensor(Shape{state_size_}, dev, kChar); |
| cudnnDropoutGetReserveSpaceSize(x_desc_, &reserve_size_); |
| mask_ = Tensor(Shape{reserve_size_}, dev, kChar); |
| // TODO(wangwei) update for async running, |
| // where reserve_size_ may not available |
| CHECK_EQ(reserve_size_, mask_.MemSize()); |
| |
| // TODO(wangwei) get seed from ctx or user config? |
| auto seed = std::chrono::system_clock::now().time_since_epoch().count(); |
| cudnnSetDropoutDescriptor(drop_desc_, ctx->cudnn_handle, 1 - dropout_ratio_, |
| state_.block()->mutable_data(), state_size_, seed); |
| has_init_cudnn_ = true; |
| } |
| |
| const Tensor CudnnDropout::Forward(int flag, const Tensor& input) { |
| if (flag & kTrain) { |
| auto size = input.Size(); |
| DataType dtype = input.data_type(); |
| auto dev = input.device(); |
| if (!has_init_cudnn_) { |
| input.device()->Exec([size, dtype, this, dev](Context* ctx) { |
| this->InitCudnn(size, dtype, dev, ctx); |
| }, {}, {this->state_.block()}); |
| } |
| Tensor output; |
| output.ResetLike(input); |
| output.device()->Exec([input, output, this](Context* ctx) { |
| Block* inblock = input.block(), * outblock = output.block(), |
| * mblock = mask_.block(); |
| cudnnDropoutForward(ctx->cudnn_handle, this->drop_desc_, this->x_desc_, |
| inblock->data(), this->y_desc_, |
| outblock->mutable_data(), mblock->mutable_data(), |
| this->reserve_size_); |
| }, {input.block()}, {output.block(), mask_.block()}); |
| return output; |
| } else { |
| return input; |
| } |
| } |
| |
| const std::pair<Tensor, vector<Tensor>> CudnnDropout::Backward( |
| int flag, const Tensor& grad) { |
| vector<Tensor> param_grad; |
| Tensor dx; |
| if (flag & kTrain) { |
| dx.ResetLike(grad); |
| dx.device()->Exec([dx, grad, this](Context* ctx) { |
| Block* dyblock = grad.block(), * dxblock = dx.block(), |
| * mblock = this->mask_.block(); |
| cudnnDropoutBackward(ctx->cudnn_handle, this->drop_desc_, this->y_desc_, |
| dyblock->data(), this->x_desc_, |
| dxblock->mutable_data(), mblock->mutable_data(), |
| this->reserve_size_); |
| }, {grad.block(), mask_.block()}, {dx.block()}); |
| } else { |
| LOG(ERROR) << "Do not call backward for evaluation phase"; |
| } |
| return std::make_pair(dx, param_grad); |
| } |
| void CudnnDropout::ToDevice(std::shared_ptr<Device> device) { |
| Dropout::ToDevice(device); |
| state_.ToDevice(device); |
| } |
| } // namespace singa |
| #endif // CUDNN_MAJOR>=5 |
| #endif // USE_CUDNN |