diff --git a/mindspore/ccsrc/kernel/gpu/other/assign_gpu_kernel.cc b/mindspore/ccsrc/kernel/gpu/other/assign_gpu_kernel.cc new file mode 100644 index 00000000000..0f3e0c95f49 --- /dev/null +++ b/mindspore/ccsrc/kernel/gpu/other/assign_gpu_kernel.cc @@ -0,0 +1,33 @@ +/** + * Copyright 2020 Huawei Technologies Co., Ltd + * + * Licensed 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. + */ + +#include "kernel/gpu/other/assign_gpu_kernel.h" + +namespace mindspore { +namespace kernel { +MS_REG_GPU_KERNEL_ONE( + Assign, + KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32), + AssignGpuKernel, float) +MS_REG_GPU_KERNEL_ONE( + Assign, + KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16), + AssignGpuKernel, half) +MS_REG_GPU_KERNEL_ONE( + Assign, KernelAttr().AddInputAttr(kNumberTypeInt32).AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32), + AssignGpuKernel, int) +} // namespace kernel +} // namespace mindspore diff --git a/mindspore/ccsrc/kernel/gpu/other/assign_gpu_kernel.h b/mindspore/ccsrc/kernel/gpu/other/assign_gpu_kernel.h new file mode 100644 index 00000000000..1c1cde4fd48 --- /dev/null +++ b/mindspore/ccsrc/kernel/gpu/other/assign_gpu_kernel.h @@ -0,0 +1,93 @@ +/** + * Copyright 2020 Huawei Technologies Co., Ltd + * + * Licensed 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. + */ + +#ifndef MINDSPORE_CCSRC_KERNEL_GPU_ASSIGN_GPU_KERNEL_H +#define MINDSPORE_CCSRC_KERNEL_GPU_ASSIGN_GPU_KERNEL_H + +#include +#include "kernel/gpu/gpu_kernel.h" +#include "kernel/gpu/gpu_kernel_factory.h" + +namespace mindspore { +namespace kernel { +template +class AssignGpuKernel : public GpuKernel { + public: + AssignGpuKernel() : input_size_(0) {} + ~AssignGpuKernel() override = default; + const std::vector &GetInputSizeList() const override { return input_size_list_; } + const std::vector &GetOutputSizeList() const override { return output_size_list_; } + const std::vector &GetWorkspaceSizeList() const override { return workspace_size_list_; } + + bool Launch(const std::vector &inputs, const std::vector &, + const std::vector &outputs, uintptr_t stream_ptr) override { + T *var = GetDeviceAddress(inputs, 0); + T *value = GetDeviceAddress(inputs, 1); + T *output = GetDeviceAddress(outputs, 0); + CHECK_CUDA_RET_WITH_EXCEPT( + cudaMemcpyAsync(var, value, input_size_, cudaMemcpyDeviceToDevice, reinterpret_cast(stream_ptr)), + "cudaMemxcpyAsync failed."); + CHECK_CUDA_RET_WITH_EXCEPT( + cudaMemcpyAsync(output, value, input_size_, cudaMemcpyDeviceToDevice, reinterpret_cast(stream_ptr)), + "cudaMemxcpyAsync failed."); + return true; + } + + bool Init(const CNodePtr &kernel_node) override { + if (!CheckParam(kernel_node)) { + return false; + } + auto shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0); + input_size_ = sizeof(T); + for (size_t x : shape) { + input_size_ = input_size_ * x; + } + InitSizeLists(); + return true; + } + + protected: + void InitSizeLists() override { + input_size_list_.push_back(input_size_); + input_size_list_.push_back(input_size_); + output_size_list_.push_back(input_size_); + } + + private: + bool CheckParam(const CNodePtr &kernel_node) { + size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node); + if (input_num != 2) { + MS_LOG(ERROR) << "Input number is " << input_num << ", but AssignGpuKernel needs 2 output."; + return false; + } + size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node); + if (output_num != 1) { + MS_LOG(ERROR) << "Output number is " << output_num << ", but AssignGpuKernel needs 1 output."; + return false; + } + return true; + } + + std::vector input_size_list_; + std::vector output_size_list_; + std::vector workspace_size_list_; + + size_t input_size_; +}; +} // namespace kernel +} // namespace mindspore + +#endif // MINDSPORE_CCSRC_KERNEL_GPU_ASSIGN_GPU_KERNEL_H diff --git a/tests/st/ops/gpu/test_assign_op.py b/tests/st/ops/gpu/test_assign_op.py new file mode 100644 index 00000000000..4cf730d7631 --- /dev/null +++ b/tests/st/ops/gpu/test_assign_op.py @@ -0,0 +1,50 @@ +# Copyright 2020 Huawei Technologies Co., Ltd +# +# Licensed 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. +# ============================================================================ + +import pytest +from mindspore import Tensor +from mindspore.ops import operations as P +import mindspore.nn as nn +import numpy as np +import mindspore.context as context + + +class Net(nn.Cell): + def __init__(self): + super(Net, self).__init__() + self.assign = P.Assign() + + def construct(self, var, value): + return self.assign(var, value) + +x = np.array([[1.2, 1], [1, 0]]).astype(np.float32) +value = np.array([[1, 2], [3, 4.0]]).astype(np.float32) + +@pytest.mark.level0 +@pytest.mark.platform_x86_gpu_training +@pytest.mark.env_onecard +def test_assign(): + context.set_context(mode=context.GRAPH_MODE, device_target="GPU") + assign = Net() + var = Tensor(x) + output = assign(var, Tensor(value)) + + error = np.ones(shape=[2, 2]) * 1.0e-6 + diff1 = output.asnumpy() - value + diff2 = var.asnumpy() - value + assert np.all(diff1 < error) + assert np.all(-diff1 < error) + assert np.all(diff2 < error) + assert np.all(-diff2 < error)