!2925 Add random normal op at GPU

Merge pull request !2925 from peixu_ren/custom_gpu

mindspore/ccsrc/kernel/gpu/cuda_impl/random_op_impl.cu

@@ -0,0 +1,42 @@
+/**
+ * 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 "random_op_impl.cuh"
+template <typename T>
+__global__ void NormalKernel(int seed, curandState *globalState, T *output, size_t count) {
+  for (size_t i = blockIdx.x * blockDim.x + threadIdx.x; i < (count); i += blockDim.x * gridDim.x) {
+    curand_init(seed, i, 0, &globalState[i]);
+    output[i] = curand_normal(&globalState[i]);
+  }
+  return;
+}
+
+template <typename T>
+void StandardNormal(int seed, int seed2, curandState *globalState, T *output, size_t count, cudaStream_t cuda_stream) {
+  int RNG_seed = 0;
+  if (seed2 != 0) {
+    RNG_seed = seed2;
+  } else if (seed != 0) {
+    RNG_seed = seed;
+  } else {
+    RNG_seed = time(NULL);
+  }
+  NormalKernel<<<GET_BLOCKS(count), GET_THREADS, 0, cuda_stream>>>(RNG_seed, globalState, output, count);
+  return;
+}
+
+template void StandardNormal<float>(int seed, int seed2, curandState *globalState,
+                                    float *output, size_t count, cudaStream_t cuda_stream);

mindspore/ccsrc/kernel/gpu/cuda_impl/random_op_impl.cuh

@@ -0,0 +1,26 @@
+/**
+ * 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_CUDA_IMPL_RANDOMOPIMPL_H_
+#define MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_RANDOMOPIMPL_H_
+
+#include <curand_kernel.h>
+#include "device/gpu/cuda_common.h"
+
+template <typename T>
+void StandardNormal(int seed, int seed2, curandState *globalState,
+                    T *output, size_t count, cudaStream_t cuda_stream);
+#endif  // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_RANDOMOPIMPL_H_

mindspore/ccsrc/kernel/gpu/math/random_op_gpu_kernel.cc

@@ -0,0 +1,24 @@
+/**
+ * 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/math/random_op_gpu_kernel.h"
+
+namespace mindspore {
+namespace kernel {
+MS_REG_GPU_KERNEL_ONE(StandardNormal, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeFloat32),
+                      RandomOpGpuKernel, float)
+}  // namespace kernel
+}  // namespace mindspore

mindspore/ccsrc/kernel/gpu/math/random_op_gpu_kernel.h

@@ -0,0 +1,121 @@
+/**
+ * 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_RANDOMOP_GPU_KERNEL_H_
+#define MINDSPORE_CCSRC_KERNEL_GPU_RANDOMOP_GPU_KERNEL_H_
+
+#include <curand_kernel.h>
+#include <cuda_runtime_api.h>
+#include <vector>
+#include <string>
+#include <map>
+#include "kernel/gpu/gpu_kernel.h"
+#include "kernel/gpu/gpu_kernel_factory.h"
+#include "kernel/gpu/cuda_impl/random_op_impl.cuh"
+
+namespace mindspore {
+namespace kernel {
+enum RandomOptype { RANDOM_OP_NORMAL = 0, RANDOM_OP_INVALID_TYPE = 255 };
+
+const std::map<std::string, RandomOptype> kRandomOpTypeMap = {{"StandardNormal", RANDOM_OP_NORMAL}};
+template <typename T>
+class RandomOpGpuKernel : public GpuKernel {
+ public:
+  RandomOpGpuKernel()
+      : random_op_type_(RANDOM_OP_INVALID_TYPE),
+        input_size_0_(0),
+        output_size_(sizeof(T)),
+        workspace_size_(sizeof(curandState)) {}
+  ~RandomOpGpuKernel() override = default;
+
+  const std::vector<size_t> &GetInputSizeList() const override { return input_size_list_; }
+  const std::vector<size_t> &GetOutputSizeList() const override { return output_size_list_; }
+  const std::vector<size_t> &GetWorkspaceSizeList() const override { return workspace_size_list_; }
+
+  bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
+              const std::vector<AddressPtr> &outputs, void *stream_ptr) override {
+    void *workspace_addr = GetDeviceAddress<void *>(workspace, 0);
+    curandState *devStates = reinterpret_cast<curandState *>(workspace_addr);
+    T *output_addr = GetDeviceAddress<T>(outputs, 0);
+
+    switch (random_op_type_) {
+      case RANDOM_OP_NORMAL: {
+        StandardNormal(seed_, seed2_, devStates, output_addr, outputs[0]->size / sizeof(T),
+                       reinterpret_cast<cudaStream_t>(stream_ptr));
+        break;
+      }
+      default: {
+        MS_LOG(EXCEPTION) << "Random operation " << random_op_type_ << " is not supported.";
+      }
+    }
+    return true;
+  }
+  bool Init(const CNodePtr &kernel_node) override {
+    std::string kernel_name = AnfAlgo::GetCNodeName(kernel_node);
+    auto iter = kRandomOpTypeMap.find(kernel_name);
+    if (iter == kRandomOpTypeMap.end()) {
+      MS_LOG(EXCEPTION) << "Random operation " << kernel_name << " is not supported.";
+    } else {
+      random_op_type_ = iter->second;
+    }
+    size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
+    if (input_num != 1) {
+      MS_LOG(ERROR) << "Input number is " << input_num << ", but random op needs 1 input.";
+      return false;
+    }
+    size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
+    if (output_num != 1) {
+      MS_LOG(ERROR) << "Output number is " << output_num << ", but random op needs 1 output.";
+      return false;
+    }
+    auto input_shape_0 = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
+    for (size_t i = 0; i < input_shape_0.size(); i++) {
+      input_size_0_ += input_shape_0[i];
+    }
+    input_size_0_ *= sizeof(int);
+    auto output_shape = AnfAlgo::GetOutputInferShape(kernel_node, 0);
+    for (size_t i = 0; i < output_shape.size(); i++) {
+      output_size_ *= output_shape[i];
+      workspace_size_ *= output_shape[i];
+    }
+    seed_ = GetValue<int>(AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("seed"));
+    seed2_ = GetValue<int>(AnfAlgo::GetCNodePrimitive(kernel_node)->GetAttr("seed2"));
+    InitSizeLists();
+    return true;
+  }
+
+ protected:
+  void InitSizeLists() override {
+    input_size_list_.push_back(input_size_0_);
+    output_size_list_.push_back(output_size_);
+    workspace_size_list_.push_back(workspace_size_);
+  }
+
+ private:
+  RandomOptype random_op_type_;
+  size_t input_size_0_;
+  size_t output_size_;
+  size_t workspace_size_;
+  int seed_;
+  int seed2_;
+  std::vector<size_t> input_size_list_;
+  std::vector<size_t> output_size_list_;
+  std::vector<size_t> workspace_size_list_;
+};
+}  // namespace kernel
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CCSRC_KERNEL_GPU_RANDOMOP_GPU_KERNEL_H_