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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2022/01/12 15:18:55 UTC
[GitHub] [incubator-mxnet] bgawrych commented on a change in pull request #20713: [FEATURE] Integrate oneDNN binary primitive support for forward add, subtract, multiply, divide.
bgawrych commented on a change in pull request #20713:
URL: https://github.com/apache/incubator-mxnet/pull/20713#discussion_r783150164
##########
File path: src/operator/nn/dnnl/dnnl_binary.cc
##########
@@ -0,0 +1,75 @@
+/*
+ * 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.
+ */
+
+/*!
+ * \file dnnl_binary.cc
+ * \author: Adam Grabowski, adam.grabowski@intel.com
+ */
+
+#if MXNET_USE_ONEDNN == 1
+#include "./dnnl_binary-inl.h"
+
+namespace mxnet {
+namespace op {
+
+DNNLBinaryOpFwd::DNNLBinaryOpFwd(const dnnl::algorithm alg,
+ const nnvm::NodeAttrs& attrs,
+ const std::vector<NDArray>& inputs,
+ const std::vector<NDArray>& outputs) {
+ auto src0_desc = inputs[0].GetDNNLData()->get_desc();
+ auto src1_desc = inputs[1].GetDNNLData()->get_desc();
+ auto dst_desc = outputs[0].GetDNNLData()->get_desc();
+
+ dnnl::binary::desc fwd_desc(alg, src0_desc, src1_desc, dst_desc);
+ fwd_pd = std::make_shared<binary_op_fwd_pd_t>(fwd_desc, mxnet::CpuEngine::Get()->get_engine());
+ fwd = std::make_shared<binary_op_fwd_t>(*fwd_pd);
+}
+
+void DNNLBinaryOpFwd::Execute(const std::vector<NDArray>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<NDArray>& outputs) {
+ auto engine = mxnet::CpuEngine::Get()->get_engine();
+ auto src0 = inputs[0].GetDNNLData();
+ auto src1 = inputs[1].GetDNNLData();
+ dnnl_output_t out_mem = CreateDNNLMem(outputs[0], fwd_pd->dst_desc(), req[0], &inputs[0]);
Review comment:
either inputs[0] or inputs[1] can be inplace - maybe it is worth checking which input is used as output when inplace
##########
File path: src/operator/nn/dnnl/dnnl_binary-inl.h
##########
@@ -0,0 +1,89 @@
+/*
+ * 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.
+ */
+
+/*!
+ * \file dnnl_binary-inl.h
+ * \author: Adam Grabowski, adam.grabowski@intel.com
+ */
+
+#ifndef MXNET_OPERATOR_NN_DNNL_DNNL_BINARY_INL_H_
+#define MXNET_OPERATOR_NN_DNNL_DNNL_BINARY_INL_H_
+
+#if MXNET_USE_ONEDNN == 1
+#include "./dnnl_base-inl.h"
+#include "./dnnl_ops-inl.h"
+#include <vector>
+
+#include "../../tensor/elemwise_binary_broadcast_op.h"
+
+namespace mxnet {
+namespace op {
+
+using binary_op_fwd_t = dnnl::binary;
Review comment:
binary_op_fwd_t => binary_fwd_t ?
##########
File path: src/operator/nn/dnnl/dnnl_binary-inl.h
##########
@@ -0,0 +1,89 @@
+/*
+ * 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.
+ */
+
+/*!
+ * \file dnnl_binary-inl.h
+ * \author: Adam Grabowski, adam.grabowski@intel.com
+ */
+
+#ifndef MXNET_OPERATOR_NN_DNNL_DNNL_BINARY_INL_H_
+#define MXNET_OPERATOR_NN_DNNL_DNNL_BINARY_INL_H_
+
+#if MXNET_USE_ONEDNN == 1
+#include "./dnnl_base-inl.h"
+#include "./dnnl_ops-inl.h"
+#include <vector>
+
+#include "../../tensor/elemwise_binary_broadcast_op.h"
+
+namespace mxnet {
+namespace op {
+
+using binary_op_fwd_t = dnnl::binary;
+using binary_op_fwd_pd_t = dnnl::binary::primitive_desc;
+
+class DNNLBinaryOpFwd {
+ public:
+ template <dnnl::algorithm alg>
+ static DNNLBinaryOpFwd& GetBinaryOpForward(const nnvm::NodeAttrs& attrs,
+ const std::vector<NDArray>& inputs,
+ const std::vector<NDArray>& outputs);
+ DNNLBinaryOpFwd(const dnnl::algorithm alg,
+ const nnvm::NodeAttrs& attrs,
+ const std::vector<NDArray>& inputs,
+ const std::vector<NDArray>& outputs);
+
+ void Execute(const std::vector<NDArray>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<NDArray>& outputs);
+
+ private:
+ std::shared_ptr<binary_op_fwd_t> fwd;
+ std::shared_ptr<binary_op_fwd_pd_t> fwd_pd;
+};
+
+template <dnnl::algorithm alg>
+DNNLBinaryOpFwd& DNNLBinaryOpFwd::GetBinaryOpForward(const nnvm::NodeAttrs& attrs,
+ const std::vector<NDArray>& inputs,
+ const std::vector<NDArray>& outputs) {
+ using binary_op_fwd_map = std::unordered_map<OpSignature, DNNLBinaryOpFwd, OpHash>;
+#if DMLC_CXX11_THREAD_LOCAL
+ static thread_local binary_op_fwd_map fwds;
+#else
+ static MX_THREAD_LOCAL binary_op_fwd_map fwds;
+#endif
+ OpSignature key;
+ key.AddSign(static_cast<int>(alg));
Review comment:
+1 to remove attrs
##########
File path: tests/python/unittest/test_operator.py
##########
@@ -1915,7 +1915,11 @@ def gen_broadcast_data(idx):
[[1, 1, 65, 2, 22], [1, 1, 65, 1, 1]],
[[1, 24, 103, 17, 18], [1, 24, 1, 1, 1]],
[[1, 1, 1, 1, 2], [1, 24, 194, 50, 1]],
- [[1, 1, 107, 84, 9], [1, 1, 1, 1, 1]]])
+ [[1, 1, 107, 84, 9], [1, 1, 1, 1, 1]],
+ [[8, 1, 6, 1], [7, 1, 5]], [[5, 4], [1]],
+ [[256, 256, 3], [3]], [[5, 4], [4]],
+ [[15, 3, 5], [3, 5]], [[15, 3, 5], [1, 5]],
+ [[15, 3, 5], [3, 1]]])
Review comment:
please check if it works when rhs shape is longer than lhs e.g. [15,3] and [4, 15, 3]
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