wehub-resource-sync
172 lines
5.2 KiB
C++
172 lines
5.2 KiB
C++
/* ******************************************************************************
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*
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author saudet
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// @author Yurii Shyrma (iuriish@yahoo.com)
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//
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#ifndef DEV_TESTS_MKLDNNUTILS_H
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#define DEV_TESTS_MKLDNNUTILS_H
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#include <array/NDArray.h>
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#include <graph/Context.h>
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#include <helpers/MKLDNNStream.h>
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#include <legacy/NativeOps.h>
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#include <ops/declarable/PlatformHelper.h>
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#include <system/platform_boilerplate.h>
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#include <dnnl.hpp>
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using namespace samediff;
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namespace sd {
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namespace ops {
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namespace platforms {
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/**
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* Here we actually declare our platform helpers
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*/
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DECLARE_PLATFORM(conv2d, ENGINE_CPU);
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DECLARE_PLATFORM(conv2d_bp, ENGINE_CPU);
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DECLARE_PLATFORM(avgpool2d, ENGINE_CPU);
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DECLARE_PLATFORM(avgpool2d_bp, ENGINE_CPU);
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DECLARE_PLATFORM(maxpool2d, ENGINE_CPU);
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DECLARE_PLATFORM(maxpool2d_bp, ENGINE_CPU);
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DECLARE_PLATFORM(conv3dnew, ENGINE_CPU);
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DECLARE_PLATFORM(conv3dnew_bp, ENGINE_CPU);
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DECLARE_PLATFORM(maxpool3dnew, ENGINE_CPU);
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DECLARE_PLATFORM(maxpool3dnew_bp, ENGINE_CPU);
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DECLARE_PLATFORM(avgpool3dnew, ENGINE_CPU);
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DECLARE_PLATFORM(avgpool3dnew_bp, ENGINE_CPU);
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DECLARE_PLATFORM(lrn, ENGINE_CPU);
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DECLARE_PLATFORM(batchnorm, ENGINE_CPU);
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DECLARE_PLATFORM(batchnorm_bp, ENGINE_CPU);
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DECLARE_PLATFORM(lstmLayer, ENGINE_CPU);
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DECLARE_PLATFORM(deconv2d, ENGINE_CPU);
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DECLARE_PLATFORM(deconv2d_tf, ENGINE_CPU);
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DECLARE_PLATFORM(deconv3d, ENGINE_CPU);
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DECLARE_PLATFORM(deconv2d_bp, ENGINE_CPU);
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DECLARE_PLATFORM(deconv3d_bp, ENGINE_CPU);
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DECLARE_PLATFORM(depthwise_conv2d, ENGINE_CPU);
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DECLARE_PLATFORM(depthwise_conv2d_bp, ENGINE_CPU);
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DECLARE_PLATFORM(matmul, ENGINE_CPU);
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DECLARE_PLATFORM(softmax, ENGINE_CPU);
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DECLARE_PLATFORM(softmax_bp, ENGINE_CPU);
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DECLARE_PLATFORM(tanh, ENGINE_CPU);
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DECLARE_PLATFORM(tanh_bp, ENGINE_CPU);
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DECLARE_PLATFORM(xw_plus_b, ENGINE_CPU);
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DECLARE_PLATFORM(xw_plus_b_bp, ENGINE_CPU);
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DECLARE_PLATFORM(concat, ENGINE_CPU);
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} // namespace platforms
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} // namespace ops
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namespace onednnUtils {
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void poolingONEDNN(NDArray* input, NDArray* output, const int kD, const int kH, const int kW, const int sD,
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const int sH, const int sW, const int pD, const int pH, const int pW, const int isNCHW,
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const dnnl::algorithm mode);
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void poolingBpONEDNN(NDArray* input, NDArray* gradO, NDArray* gradI, const int kD, const int kH,
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const int kW, const int sD, const int sH, const int sW, const int pD, const int pH, const int pW,
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const int isNCHW, const dnnl::algorithm mode);
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void getONEDNNMemoryDescLrn(NDArray* src, NDArray* diff_src, NDArray* dst,
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dnnl::memory::desc* lrn_src_md, dnnl::memory::desc* lrn_diff_src_md,
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dnnl::memory::desc* lrn_dst_md, dnnl::memory::desc* user_src_md,
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dnnl::memory::desc* user_diff_src_md, dnnl::memory::desc* user_dst_md, int axis);
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dnnl::engine& getEngine(void* ptr);
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/**
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* This function creates memory dimentions
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* @param const pointer to array
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* @param const array rank
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* @param reference to memory dimentions
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*/
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void getDims(NDArray* array, const int rank, dnnl::memory::dims& mklDims);
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/**
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* This function evaluate memory format tag based on array shapeInfo
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* @param const array
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* @return memory format
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*/
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dnnl::memory::format_tag getFormat(NDArray& arr);
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void setBlockStrides(NDArray& array, dnnl::memory::desc& mklMd, const std::vector<int>& permut = {});
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//////////////////////////////////////////////////////////////////////
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/**
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* This function load and reorder user memory to mkl
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* @param const pointer to dataset
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* @param reference to mkl engine
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* @param reference to mkl stream
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* @param reference to args container for dnnl
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* @param reference to user memory description
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* @param primitive memory descriptor
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* @param dnnl arg activation enumerator
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*/
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dnnl::memory loadDataToMklStream(NDArray& array, const dnnl::engine& engine, const dnnl::stream& stream,
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const dnnl::memory::desc& user_md, const dnnl::memory::desc& primitive_md,
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dnnl::memory& arg);
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/**
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* @brief This function checks adittional ONEDNN pooling requirements
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*
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* @param reqs Requirements block to store the check result
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* @param block Context block to extract positional integer arguments.
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* @param in in NDArray
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* @param out out NDArray
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*/
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void checkPoolingONEDNN(Requirements& reqs, sd::graph::Context& block, sd::NDArray* in, sd::NDArray* out);
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} // namespace onednnUtils
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} // namespace sd
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#endif // DEV_TESTS_MKLDNNUTILS_H
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