akarbown commented on a change in pull request #19896:
URL: https://github.com/apache/incubator-mxnet/pull/19896#discussion_r643227909
##########
File path: src/operator/contrib/adaptive_avg_pooling.cc
##########
@@ -219,6 +295,11 @@ The pooling kernel and stride sizes are automatically
chosen for desired output
.set_attr<FCompute>("FCompute<cpu>", AdaptiveAvgPoolOpForward<cpu>)
.set_attr<nnvm::FGradient>("FGradient",
ElemwiseGradUseNone{"_backward_contrib_AdaptiveAvgPooling2D"})
+.set_attr<FInferStorageType>("FInferStorageType", AdaptivePoolingStorageType)
+#if MXNET_USE_MKLDNN == 1
Review comment:
Please change it to MXNET_USE_ONEDNN.
##########
File path: src/operator/nn/mkldnn/mkldnn_adaptive_pooling-inl.h
##########
@@ -0,0 +1,146 @@
+/*
+ * 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.
+ */
+
+/*!
+ * Copyright (c) 2021 by Contributors
+ * \file mkldnn_adaptive_pooling-inl.h
+*/
+#ifndef MXNET_OPERATOR_NN_MKLDNN_MKLDNN_ADAPTIVE_POOLING_INL_H_
+#define MXNET_OPERATOR_NN_MKLDNN_MKLDNN_ADAPTIVE_POOLING_INL_H_
+
+#if MXNET_USE_MKLDNN == 1
Review comment:
Please change it to MXNET_USE_ONEDNN.
##########
File path: src/operator/nn/mkldnn/mkldnn_adaptive_pooling-inl.h
##########
@@ -0,0 +1,146 @@
+/*
+ * 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.
+ */
+
+/*!
+ * Copyright (c) 2021 by Contributors
+ * \file mkldnn_adaptive_pooling-inl.h
+*/
+#ifndef MXNET_OPERATOR_NN_MKLDNN_MKLDNN_ADAPTIVE_POOLING_INL_H_
+#define MXNET_OPERATOR_NN_MKLDNN_MKLDNN_ADAPTIVE_POOLING_INL_H_
+
+#if MXNET_USE_MKLDNN == 1
+
+#include <mkldnn.hpp>
+#include <utility>
+#include "../../operator_common.h"
+#include "./mkldnn_base-inl.h"
+
+namespace mxnet {
+namespace op {
+
+class MKLDNNAdaptivePoolingFwd {
+ public:
+ MKLDNNAdaptivePoolingFwd(const mxnet::NDArray &input,
+ const mxnet::NDArray &output,
+ const mkldnn::memory::dims &kernel,
+ const mkldnn::memory::dims &strides,
+ const mkldnn::memory::dims &pad_l,
+ const mkldnn::memory::dims &pad_r,
+ const mkldnn::algorithm alg_kind,
+ const bool with_workspace, const bool is_train)
+ : with_workspace_(with_workspace), fwd_(nullptr) {
+ Init(input, output, kernel, strides, pad_l, pad_r, is_train, alg_kind);
+ }
+ ~MKLDNNAdaptivePoolingFwd() = default;
+
+ public:
+ void Execute(const NDArray &input, const OpReqType req, const NDArray
&output,
+ const NDArray *workspace);
+
+ private:
+ bool with_workspace_;
+ std::shared_ptr<mkldnn::pooling_forward::primitive_desc> fwd_pd_;
+ std::shared_ptr<mkldnn::pooling_forward> fwd_;
+
+ private:
+ void Init(const mxnet::NDArray &input, const mxnet::NDArray &output,
+ const mkldnn::memory::dims &kernel,
+ const mkldnn::memory::dims &strides,
+ const mkldnn::memory::dims &pad_l,
+ const mkldnn::memory::dims &pad_r, const bool is_train,
+ const mkldnn::algorithm alg_kind);
+};
+
+template <typename T = mkldnn::memory::dims>
+void updateAdaptivePaddingKernel(T *kernel, T *strides, T *pad_l, T *pad_r,
+ const NDArray &in_data,
+ const NDArray &out_data) {
+ const int IH = in_data.shape()[2];
+ const int IW = in_data.shape()[3];
+ const int OH = out_data.shape()[2];
+ const int OW = out_data.shape()[3];
+
+ strides->at(0) = floor((IH << 1) / OH) - floor(IH / OH);
+ strides->at(1) = floor((IW << 1) / OW) - floor(IW / OW);
+ kernel->at(0) = ceil((IH << 1) / OH) - floor(IH / OH);
+ kernel->at(1) = ceil((IW << 1) / OW) - floor(IW / OW);
+ pad_l->at(0) = (strides->at(0) * (OH - 1) + kernel->at(0) - IH) >> 1;
+ pad_l->at(1) = (strides->at(1) * (OW - 1) + kernel->at(1) - IW) >> 1;
+}
+
+template <typename T>
+MKLDNNAdaptivePoolingFwd &GetPoolingFwd(const T ¶m, const bool is_train,
+ const NDArray &input,
+ const NDArray &output) {
+ if (input.shape().ndim() != 4) {
+ LOG(FATAL) << "MKLDNN Adaptive Avg Pool 2d: Expect only 2D input";
+ }
+ typedef ParamOpSign<T> MKLDNNPoolingSignature;
+#if DMLC_CXX11_THREAD_LOCAL
+ static thread_local std::unordered_map<MKLDNNPoolingSignature,
+ MKLDNNAdaptivePoolingFwd, OpHash>
+ pooling_fwds;
+#else
+ static MX_THREAD_LOCAL std::unordered_map<MKLDNNPoolingSignature,
+ MKLDNNAdaptivePoolingFwd, OpHash>
+ pooling_fwds;
+#endif
+ bool with_workspace = is_train;
+ MKLDNNPoolingSignature key(param);
+ key.AddSign(is_train);
+ key.AddSign(with_workspace);
+ key.AddSign(input);
+ key.AddSign(output);
+
+ auto it = pooling_fwds.find(key);
+ if (it == pooling_fwds.end()) {
+ const int kernel_ndims = input.shape().ndim();
+
+ mkldnn::memory::dims kernel(kernel_ndims);
+ mkldnn::memory::dims strides(kernel_ndims);
+ mkldnn::memory::dims pad_l(kernel_ndims);
+ mkldnn::memory::dims pad_r(kernel_ndims);
+
+ updateAdaptivePaddingKernel(&kernel, &strides, &pad_l, &pad_r, input,
+ output);
+ mkldnn::memory::validate_dims(kernel);
+ mkldnn::memory::validate_dims(strides);
+ mkldnn::memory::validate_dims(pad_l);
+ mkldnn::memory::validate_dims(pad_r);
+
+ mkldnn::algorithm kind = mkldnn::algorithm::pooling_avg;
+ MKLDNNAdaptivePoolingFwd fwd(input, output, kernel, kernel, pad_l, pad_r,
+ kind, false, false);
+ it = AddToCache(&pooling_fwds, key, fwd);
+ }
+ return it->second;
+}
+
+template <typename T>
+void MKLDNNAdaptivePoolingCompute(const OpContext &ctx, const T ¶m,
+ const NDArray &in_data, const OpReqType req,
+ const NDArray &out_data,
+ const NDArray *workspace) {
+ auto &fwd = GetPoolingFwd(param, ctx.is_train, in_data, out_data);
+ fwd.Execute(in_data, req, out_data, workspace);
+}
+} // namespace op
+} // namespace mxnet
+#endif // MXNET_USE_MKLDNN == 1
Review comment:
Please change it to MXNET_USE_ONEDNN.
##########
File path: src/operator/nn/mkldnn/mkldnn_adaptive_pooling.cc
##########
@@ -0,0 +1,97 @@
+/*
+ * 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.
+ */
+
+/*!
+ * Copyright (c) 2021 by Contributors
+ * \file mkldnn_adaptive_pooling.cc
+*/
+
+#if MXNET_USE_MKLDNN == 1
Review comment:
Please change it to MXNET_USE_ONEDNN.
##########
File path: src/operator/nn/mkldnn/mkldnn_adaptive_pooling.cc
##########
@@ -0,0 +1,97 @@
+/*
+ * 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.
+ */
+
+/*!
+ * Copyright (c) 2021 by Contributors
+ * \file mkldnn_adaptive_pooling.cc
+*/
+
+#if MXNET_USE_MKLDNN == 1
+
+#include "./mkldnn_adaptive_pooling-inl.h"
+
+namespace mxnet {
+namespace op {
+void MKLDNNAdaptivePoolingFwd::Init(
Review comment:
Functions: MKLDNNAdaptivePoolingFwd::Init() and
MKLDNNAdaptivePoolingFwd::Execute() are more or less the same as the one that
are in the mkldnn_poolling.cc file (MKLDNNPoolingFwd::Init() &&
MKLDNNPoolingFwd::Execute()). What do you think about combining them together?
So that the code won't be duplicated.
##########
File path: src/operator/nn/mkldnn/mkldnn_adaptive_pooling.cc
##########
@@ -0,0 +1,97 @@
+/*
+ * 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.
+ */
+
+/*!
+ * Copyright (c) 2021 by Contributors
+ * \file mkldnn_adaptive_pooling.cc
+*/
+
+#if MXNET_USE_MKLDNN == 1
+
+#include "./mkldnn_adaptive_pooling-inl.h"
+
+namespace mxnet {
+namespace op {
+void MKLDNNAdaptivePoolingFwd::Init(
+ const mxnet::NDArray &input, const mxnet::NDArray &output,
+ const mkldnn::memory::dims &kernel, const mkldnn::memory::dims &strides,
+ const mkldnn::memory::dims &pad_l, const mkldnn::memory::dims &pad_r,
+ const bool is_train, const mkldnn::algorithm alg_kind) {
+ const auto src_md = input.GetMKLDNNData()->get_desc();
+ const auto dst_md = GetMemDesc(output);
+ const mkldnn::engine engine = CpuEngine::Get()->get_engine();
+
+ if (alg_kind != mkldnn::algorithm::pooling_avg &&
+ alg_kind != mkldnn::algorithm::pooling_avg_include_padding &&
+ alg_kind != mkldnn::algorithm::pooling_avg_exclude_padding) {
+ LOG(FATAL) << "MKLDNN Adaptive Pooling: algorithm is not supported";
+ }
+
+ mkldnn::prop_kind prop = mkldnn::prop_kind::forward_scoring;
+ if (is_train && alg_kind != mkldnn::algorithm::pooling_avg) {
+ prop = mkldnn::prop_kind::forward_training;
+ }
+ if (is_train && prop == mkldnn::prop_kind::forward_scoring) {
+ LOG(INFO) << "MKLDNN Pooling: training with prop_kind is forward_scoring";
+ }
+
+ const auto fwd_desc = mkldnn::pooling_forward::desc(
+ prop, alg_kind, src_md, dst_md, strides, kernel, pad_l, pad_r);
+ this->fwd_pd_.reset(
+ new mkldnn::pooling_forward::primitive_desc(fwd_desc, engine));
+ this->fwd_.reset(new mkldnn::pooling_forward(*(this->fwd_pd_)));
+}
+
+void MKLDNNAdaptivePoolingFwd::Execute(const NDArray &input,
+ const OpReqType req,
+ const NDArray &output,
+ const NDArray *workspace) {
+ NDArray in_buffer = input;
+ if (input.IsView() && input.IsMKLDNNData()) {
+ in_buffer = input.Reorder2Default();
+ }
+
+ auto input_mem = in_buffer.GetMKLDNNData();
+ auto output_mem_t = CreateMKLDNNMem(output, this->fwd_pd_->dst_desc(), req);
+
+ mkldnn_args_map_t args = {{MKLDNN_ARG_SRC, *input_mem},
+ {MKLDNN_ARG_DST, *(output_mem_t.second)}};
+
+ if (this->with_workspace_) {
+ auto engine = CpuEngine::Get()->get_engine();
+ if (workspace == nullptr) {
+ LOG(FATAL) << "MKLDNN Average Pooling: incorrect worskapce input";
+ }
+ auto ws = std::make_shared<mkldnn::memory>(
+ this->fwd_pd_->workspace_desc(), engine,
+ workspace->GetMKLDNNData()->get_data_handle());
+ args[MKLDNN_ARG_WORKSPACE] = *ws;
+ }
+ if (this->fwd_) {
+ MKLDNNStream::Get()->RegisterPrimArgs(*(this->fwd_), args);
+ CommitOutput(output, output_mem_t);
+ MKLDNNStream::Get()->Submit();
+ } else {
+ LOG(FATAL) << "MKLDNN Pooling: forward primitive is nullptr";
+ }
+}
+
+} // namespace op
+} // namespace mxnet
+#endif // MXNET_USE_MKLDNN == 1
Review comment:
Please change it to MXNET_USE_ONEDNN.
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