ead5162c97
* libnd4j first step of softmax mkldnn implementation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j raw implementation of mkldnn softmax Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j merge master and added softmax to MklDnnTests Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j some corrections for softmax mkldnn Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j merge branch, fixed problem with negative axis, fixed dnnl::memory::format_tag selection, test cases added Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j minor corrections to avoid risk connected with negative axis usage Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed windows builds, added switcher to use mkldnn sofmax version only for 3D, 4D, 5D, 6D arrays Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed dataType selection per request Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fix for mac and windows builds Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j builds fix Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j first spet of elementwize tanh implementation on mkldnn Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed typo in error message for softmax MKLDNN, test case added, implementation of tanh on MKLDNN, need supported DataType testing Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j several fixes for tanh and temporary performance test added Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed mkldnn platform loader for tanh Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j MklDnn tanh removed unsupported data types, removed performance test case, added more appropriate equivalence test case, code clean up Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j fixed problem with empty input case for MklDnn tanh and softmax Signed-off-by: Oleg <oleg.semeniv@gmail.com>
159 lines
8.0 KiB
C++
159 lines
8.0 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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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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* 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 <legacy/NativeOps.h>
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#include <array/NDArray.h>
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#include <dnnl.hpp>
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#include <helpers/MKLDNNStream.h>
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#include <graph/Context.h>
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#include <ops/declarable/PlatformHelper.h>
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#include <system/platform_boilerplate.h>
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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(tanh, ENGINE_CPU);
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}
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}
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namespace mkldnnUtils {
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void poolingMKLDNN(const NDArray* input, NDArray* output, const int kD, const int kH, const int kW, const int sD, const int sH, const int sW, const int pD, const int pH, const int pW, const int isNCHW, const dnnl::algorithm mode);
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void poolingBpMKLDNN(const NDArray* input, const NDArray* gradO, NDArray* gradI, const int kD, const int kH, const int kW, const int sD, const int sH, const int sW, const int pD, const int pH, const int pW, const int isNCHW, const dnnl::algorithm mode);
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void getMKLDNNMemoryDescLrn(const NDArray* src, const NDArray* diff_src, const NDArray* dst,
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dnnl::memory::desc* lrn_src_md, dnnl::memory::desc* lrn_diff_src_md, dnnl::memory::desc* lrn_dst_md,
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dnnl::memory::desc* user_src_md, 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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* Utility methods for MKLDNN
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*/
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/* void getMKLDNNMemoryDescConv2d(
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int kH, int kW, int sH, int sW, int pH, int pW, int dH, int dW, const int paddingMode, bool isNCHW,
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int bS, int iC, int iH, int iW, int oC, int oH, int oW, const NDArray* src, const NDArray* diff_src,
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const NDArray* weights, const NDArray* diff_weights, const NDArray* bias, const NDArray* dst,
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dnnl::memory::desc* conv_src_md, dnnl::memory::desc* conv_diff_src_md, dnnl::memory::desc* conv_weights_md,
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dnnl::memory::desc* conv_diff_weights_md, dnnl::memory::desc* conv_bias_md, dnnl::memory::desc* conv_dst_md,
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dnnl::memory::desc* user_src_md, dnnl::memory::desc* user_diff_src_md, dnnl::memory::desc* user_weights_md,
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dnnl::memory::desc* user_diff_weights_md, dnnl::memory::desc* user_bias_md, dnnl::memory::desc* user_dst_md,
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dnnl::memory::dims& conv_strides, dnnl::memory::dims& conv_padding, dnnl::memory::dims& conv_padding_r, dnnl::memory::dims& conv_dilation);
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void getMKLDNNMemoryDescConv3d(
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int kD, int kH, int kW, int sD, int sH, int sW, int pD, int pH, int pW, int dD, int dH, int dW, bool isSameMode, bool isNCDHW,
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int bS, int iC, int iD, int iH, int iW, int oC, int oD, int oH, int oW, const NDArray* src, const NDArray* diff_src,
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const NDArray* weights, const NDArray* diff_weights, const NDArray* bias, const NDArray* dst,
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dnnl::memory::desc* conv_src_md, dnnl::memory::desc* conv_diff_src_md, dnnl::memory::desc* conv_weights_md,
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dnnl::memory::desc* conv_diff_weights_md, dnnl::memory::desc* conv_bias_md, dnnl::memory::desc* conv_dst_md,
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dnnl::memory::desc* user_src_md, dnnl::memory::desc* user_diff_src_md, dnnl::memory::desc* user_weights_md,
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dnnl::memory::desc* user_diff_weights_md, dnnl::memory::desc* user_bias_md, dnnl::memory::desc* user_dst_md,
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dnnl::memory::dims& conv_strides, dnnl::memory::dims& conv_padding, dnnl::memory::dims& conv_padding_r, dnnl::memory::dims& conv_dilation);
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void getMKLDNNMemoryDescPool2d(
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int kH, int kW, int sH, int sW, int pH, int pW, int dH, int dW, int poolingMode, int extraParam0, bool isNCHW,
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int bS, int iC, int iH, int iW, int oC, int oH, int oW,
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const NDArray* src, const NDArray* diff_src, const NDArray* dst, dnnl::algorithm& algorithm,
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dnnl::memory::desc* pool_src_md, dnnl::memory::desc* pool_diff_src_md, dnnl::memory::desc* pool_dst_md,
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dnnl::memory::desc* user_src_md, dnnl::memory::desc* user_diff_src_md, dnnl::memory::desc* user_dst_md,
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dnnl::memory::dims& pool_strides, dnnl::memory::dims& pool_kernel, dnnl::memory::dims& pool_padding, dnnl::memory::dims& pool_padding_r);
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void getMKLDNNMemoryDescPool3d(
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int kD, int kH, int kW, int sD, int sH, int sW, int pD, int pH, int pW, int dD, int dH, int dW, int poolingMode, int extraParam0, bool isNCDHW,
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int bS, int iC, int iD, int iH, int iW, int oC, int oD, int oH, int oW,
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const NDArray* src, const NDArray* diff_src, const NDArray* dst, dnnl::algorithm& algorithm,
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dnnl::memory::desc* pool_src_md, dnnl::memory::desc* pool_diff_src_md, dnnl::memory::desc* pool_dst_md,
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dnnl::memory::desc* user_src_md, dnnl::memory::desc* user_diff_src_md, dnnl::memory::desc* user_dst_md,
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dnnl::memory::dims& pool_strides, dnnl::memory::dims& pool_kernel, dnnl::memory::dims& pool_padding, dnnl::memory::dims& pool_padding_r);
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void getMKLDNNMemoryDescBatchNorm(const NDArray* src, const NDArray* diff_src, const NDArray* dst,
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dnnl::memory::desc* batchnorm_src_md, dnnl::memory::desc* batchnorm_diff_src_md, dnnl::memory::desc* batchnorm_dst_md,
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dnnl::memory::desc* user_src_md, dnnl::memory::desc* user_diff_src_md, dnnl::memory::desc* user_dst_md, int axis);
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*/
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}
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}
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#endif //DEV_TESTS_MKLDNNUTILS_H
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