lingyunli63
4 years ago
parent
b79b613acc
commit
a500a57c72
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://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,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "backend/optimizer/graph_kernel/graph_kernel_cse.h"
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#include <memory>
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#include "backend/session/anf_runtime_algorithm.h"
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#include "runtime/device/kernel_info.h"
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namespace mindspore {
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namespace opt {
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bool GraphKernelBackendCSE::CheckEqualKernelBuildInfo(const AnfNodePtr &main, const AnfNodePtr &node) const {
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MS_EXCEPTION_IF_NULL(main);
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MS_EXCEPTION_IF_NULL(node);
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auto main_kernel_info = dynamic_cast<device::KernelInfo *>(main->kernel_info());
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auto node_kernel_info = dynamic_cast<device::KernelInfo *>(node->kernel_info());
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if (main_kernel_info == nullptr && node_kernel_info == nullptr) {
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return true;
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}
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if (main_kernel_info != nullptr && node_kernel_info != nullptr) {
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auto main_build_info = main_kernel_info->GetMutableSelectKernelBuildInfo();
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auto node_build_info = node_kernel_info->GetMutableSelectKernelBuildInfo();
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if (main_build_info == nullptr && node_build_info == nullptr) {
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return true;
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}
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if (main_build_info == nullptr || node_build_info == nullptr) {
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return false;
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}
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if (main_build_info->fusion_type() != node_build_info->fusion_type() ||
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main_build_info->processor() != node_build_info->processor()) {
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return false;
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}
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return main_build_info->IsSimilarityKernelBuildInfo(*node_build_info);
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}
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return false;
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}
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bool GraphKernelCSE::Run(const FuncGraphPtr &func_graph) {
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MS_EXCEPTION_IF_NULL(func_graph);
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auto graphkernel_backend_cse = std::make_shared<GraphKernelBackendCSE>();
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return graphkernel_backend_cse->Cse(func_graph, func_graph->manager());
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,38 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://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,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GRAPH_KERNEL_CSE_H_
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#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GRAPH_KERNEL_CSE_H_
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#include "backend/optimizer/pass/common_subexpression_elimination.h"
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namespace mindspore {
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namespace opt {
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class GraphKernelCSE : public Pass {
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public:
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GraphKernelCSE() : Pass("graph_kernel_cse") {}
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~GraphKernelCSE() override = default;
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bool Run(const FuncGraphPtr &func_graph) override;
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};
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class GraphKernelBackendCSE : public BackendCSE {
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public:
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GraphKernelBackendCSE() = default;
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~GraphKernelBackendCSE() override = default;
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bool CheckEqualKernelBuildInfo(const AnfNodePtr &main, const AnfNodePtr &node) const override;
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};
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GRAPH_KERNEL_CSE_H_
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@ -0,0 +1,51 @@
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://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,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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from mindspore import Tensor
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from mindspore.nn import Cell
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import mindspore.ops.operations as P
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context.set_context(mode=context.GRAPH_MODE, enable_graph_kernel=True, device_target="GPU")
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class Net(Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.add = P.TensorAdd()
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self.mul = P.Mul()
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def construct(self, x):
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mul_res = self.mul(x, x)
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square_res = P.Square()(x)
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return self.add(mul_res, square_res)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_basic():
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input_x = np.random.normal(0, 1, [2, 3, 4, 3]).astype(np.float32)
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mul_res = input_x * input_x
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square_res = np.square(input_x)
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expect = mul_res + square_res
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net = Net()
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result = net(Tensor(input_x))
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res = np.allclose(expect, result.asnumpy(), rtol=1.e-4, atol=1.e-7, equal_nan=True)
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assert res
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