dynamic shape op initial changes

fix ci

fix ci

mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/dynamic_shape_gpu_kernel.cc

@@ -0,0 +1,31 @@
+/**
+ * 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 <cstdint>
+
+#include "backend/kernel_compiler/gpu/arrays/dynamic_shape_gpu_kernel.h"
+
+namespace mindspore {
+namespace kernel {
+MS_REG_GPU_KERNEL_ONE(DynamicShape, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32),
+                      DynamicShapeGpuKernel, int32_t)
+MS_REG_GPU_KERNEL_ONE(DynamicShape, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32),
+                      DynamicShapeGpuKernel, half)
+MS_REG_GPU_KERNEL_ONE(DynamicShape, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32),
+                      DynamicShapeGpuKernel, float)
+MS_REG_GPU_KERNEL_ONE(DynamicShape, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32),
+                      DynamicShapeGpuKernel, bool)
+}  // namespace kernel
+}  // namespace mindspore

mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/dynamic_shape_gpu_kernel.h

@@ -0,0 +1,101 @@
+/**
+ * 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_BACKEND_KERNEL_COMPILER_GPU_DYNAMIC_SHAPE_GPU_KERNEL_H_
+#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_DYNAMIC_SHAPE_GPU_KERNEL_H_
+
+#include <cuda_runtime.h>
+
+#include <vector>
+
+#include "backend/kernel_compiler/gpu/gpu_kernel.h"
+#include "backend/kernel_compiler/gpu/gpu_kernel_factory.h"
+
+namespace mindspore {
+namespace kernel {
+template <typename T>
+class DynamicShapeGpuKernel : public GpuKernel {
+ public:
+  DynamicShapeGpuKernel() { ResetResource(); }
+  ~DynamicShapeGpuKernel() = 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 {
+    int *output_device_address = GetDeviceAddress<int>(outputs, 0);
+    size_t prev_node_output_shape_size = prev_node_output_shape_.size() * sizeof(int);
+    CHECK_CUDA_RET_WITH_EXCEPT(
+      cudaMemcpyAsync(output_device_address, prev_node_output_shape_.data(), prev_node_output_shape_size,
+                      cudaMemcpyHostToDevice, reinterpret_cast<cudaStream_t>(stream_ptr)),
+      "cudaMemcpyAsync prev_node_output_shape failed");
+
+    return true;
+  }
+
+  bool Init(const CNodePtr &kernel_node) override {
+    size_t input_count = AnfAlgo::GetInputTensorNum(kernel_node);
+    if (input_count != 1) {
+      MS_LOG(EXCEPTION) << input_count << " arguments were provided, but DynamicShapeGpuKernel expects 1.";
+    }
+
+    std::vector<size_t> prev_node_output_shape_tmp = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
+    input_size_ = 1;
+    for (const size_t &e : prev_node_output_shape_tmp) {
+      input_size_ *= e;
+      // shapes are Tensors with elements of type int32, but GetPrevNodeOutputInferShape returns vector of size_t,
+      // so we use an int* for allocated output memory and cast to an int here, otherwise the memcpy will fail with a
+      // silently.
+      prev_node_output_shape_.push_back(e);
+    }
+
+    output_size_ = prev_node_output_shape_.size();
+
+    InitSizeLists();
+
+    return true;
+  }
+
+  void ResetResource() noexcept override {
+    input_size_ = -1;
+    output_size_ = -1;
+    prev_node_output_shape_.clear();
+    input_size_list_.clear();
+    output_size_list_.clear();
+    workspace_size_list_.clear();
+  }
+
+ protected:
+  void InitSizeLists() override {
+    input_size_list_.push_back(input_size_ * sizeof(T));
+    output_size_list_.push_back(output_size_ * sizeof(int));
+  }
+
+ private:
+  size_t input_size_;
+  size_t output_size_;
+  std::vector<int> prev_node_output_shape_;
+
+  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_BACKEND_KERNEL_COMPILER_GPU_DYNAMIC_SHAPE_GPU_KERNEL_H_