!14201 Add new GPU kernel Tile

From: @TFbunny
Reviewed-by: @tom__chen
Signed-off-by:

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

@@ -0,0 +1,34 @@
+/**
+ * Copyright 2021 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 "backend/kernel_compiler/gpu/arrays/tile_gpu_kernel.h"
+
+namespace mindspore {
+namespace kernel {
+MS_REG_GPU_KERNEL_ONE(Tile, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64),
+                      TileGpuKernel, double)
+MS_REG_GPU_KERNEL_ONE(Tile, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
+                      TileGpuKernel, float)
+MS_REG_GPU_KERNEL_ONE(Tile, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
+                      TileGpuKernel, half)
+MS_REG_GPU_KERNEL_ONE(Tile, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt16), TileGpuKernel,
+                      int16_t)
+MS_REG_GPU_KERNEL_ONE(Tile, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32), TileGpuKernel,
+                      int)
+MS_REG_GPU_KERNEL_ONE(Tile, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt64), TileGpuKernel,
+                      int64_t)
+}  // namespace kernel
+}  // namespace mindspore

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

@@ -0,0 +1,125 @@
+/**
+ * Copyright 2021 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_ARRAYS_TILE_GPU_KERNEL_H_
+#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_ARRAYS_TILE_GPU_KERNEL_H_
+
+#include <vector>
+#include "backend/kernel_compiler/gpu/gpu_kernel.h"
+#include "backend/kernel_compiler/gpu/gpu_kernel_factory.h"
+#include "backend/kernel_compiler/gpu/cuda_impl/tile_impl.cuh"
+
+namespace mindspore {
+namespace kernel {
+template <typename T>
+class TileGpuKernel : public GpuKernel {
+ public:
+  TileGpuKernel() { ResetResource(); }
+  ~TileGpuKernel() 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 {
+    T *input = GetDeviceAddress<T>(inputs, 0);
+    size_t *input_shape_ptr = GetDeviceAddress<size_t>(workspace, 0);
+    size_t *output_shape_ptr = GetDeviceAddress<size_t>(workspace, 1);
+    T *output = GetDeviceAddress<T>(outputs, 0);
+
+    CHECK_CUDA_RET_WITH_EXCEPT(kernel_node_,
+                               cudaMemcpyAsync(input_shape_ptr, &input_shape_[0], input_shape_.size() * sizeof(size_t),
+                                               cudaMemcpyHostToDevice, reinterpret_cast<cudaStream_t>(stream_ptr)),
+                               "cudaMemcpyAsync input_shape_ failed");
+    CHECK_CUDA_RET_WITH_EXCEPT(
+      kernel_node_,
+      cudaMemcpyAsync(output_shape_ptr, &output_shape_[0], output_shape_.size() * sizeof(size_t),
+                      cudaMemcpyHostToDevice, reinterpret_cast<cudaStream_t>(stream_ptr)),
+      "cudaMemcpyAsync output_shape_ failed");
+    CalTile(output_size_, input_size_, shape_size_, input_shape_ptr, output_shape_ptr, input, output,
+            reinterpret_cast<cudaStream_t>(stream_ptr));
+    return true;
+  }
+
+  bool Init(const CNodePtr &kernel_node) override {
+    kernel_node_ = kernel_node;
+    size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
+    if (input_num != 1) {
+      MS_LOG(EXCEPTION) << "Input number is " << input_num << ", but Tile needs 1 input.";
+      return false;
+    }
+    size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
+    if (output_num != 1) {
+      MS_LOG(EXCEPTION) << "Output number is " << output_num << ", but Tile has 1 output.";
+      return false;
+    }
+    input_shape_ = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
+    input_size_ = 1;
+    for (size_t i = 0; i < input_shape_.size(); i++) {
+      input_size_ *= input_shape_[i];
+    }
+    output_shape_ = AnfAlgo::GetOutputInferShape(kernel_node, 0);
+    output_size_ = 1;
+    if (output_shape_.size() > TILE_MAX_DIMENSION) {
+      MS_LOG(EXCEPTION) << "Output is " << output_shape_.size() << "-D, but Tile supports up to " << TILE_MAX_DIMENSION
+                        << "-D.";
+    }
+    shape_size_ = output_shape_.size();
+    for (size_t i = 0; i < output_shape_.size(); i++) {
+      output_size_ *= output_shape_[i];
+    }
+    std::vector<int64_t> multiples = GetAttr<std::vector<int64_t>>(kernel_node, "multiples");
+    int64_t filling_value = static_cast<int64_t>(multiples.size()) - static_cast<int64_t>(input_shape_.size());
+    // input_shape_.size() == output_shape_.size() == shape_size_
+    input_shape_.insert(input_shape_.begin(), LongToSize(filling_value), 1);
+    InitSizeLists();
+    return true;
+  }
+
+  void ResetResource() noexcept override {
+    input_size_ = 1;
+    output_size_ = 1;
+    shape_size_ = 1;
+    input_shape_.clear();
+    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));
+    workspace_size_list_.push_back(input_shape_.size() * sizeof(size_t));
+    workspace_size_list_.push_back(output_shape_.size() * sizeof(size_t));
+    output_size_list_.push_back(output_size_ * sizeof(T));
+  }
+
+ private:
+  size_t input_size_;
+  size_t output_size_;
+  size_t shape_size_;
+  std::vector<size_t> input_shape_;
+  std::vector<size_t> 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_ARRAYS_TILE_GPU_KERNEL_H_

mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/tile_impl.cu

@@ -0,0 +1,74 @@
+/**
+ * Copyright 2021 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 "backend/kernel_compiler/gpu/cuda_impl/tile_impl.cuh"
+
+template <typename T>
+__global__ void Tile(const size_t output_size, const size_t input_size, const size_t shape_size,
+                     const size_t *input_shape, const size_t *output_shape, const T *input, T *output) {
+  // for example 4-D: pos = pos_array[0] * output_shape[1] * output_shape[2] * output_shape[3] +
+  //                        pos_array[1] * output_shape[2] * output_shape[3] +
+  //                        pos_array[2] * output_shape[3] +
+  //                        pos_array[3]
+  size_t pos_array[TILE_MAX_DIMENSION];
+  for (size_t pos = blockIdx.x * blockDim.x + threadIdx.x; pos < output_size; pos += blockDim.x * gridDim.x) {
+    size_t tmp_pos = pos;
+    size_t pos_size = output_size / output_shape[0];
+    pos_array[0] = tmp_pos / pos_size;
+    for (size_t i = 1; i < shape_size; i++) {
+      tmp_pos -= pos_array[i - 1] * pos_size;
+      pos_size = pos_size / output_shape[i];
+      pos_array[i] = tmp_pos / pos_size;
+    }
+    for (size_t i = 0; i < shape_size; i++) {
+      pos_array[i] = pos_array[i] % input_shape[i];
+    }
+    pos_size = input_size;
+    size_t input_pos = 0;
+    for (size_t i = 0; i < shape_size; i++) {
+      pos_size /= input_shape[i];
+      input_pos += (pos_array[i] * pos_size);
+    }
+    output[pos] = input[input_pos];
+  }
+}
+
+template <typename T>
+void CalTile(const size_t output_size, const size_t input_size, const size_t shape_size, const size_t *input_shape,
+             const size_t *output_shape, const T *input, T *output, cudaStream_t cuda_stream) {
+  Tile<<<GET_BLOCKS(output_size), GET_THREADS, 0, cuda_stream>>>(output_size, input_size, shape_size, input_shape,
+                                                                 output_shape, input, output);
+  return;
+}
+
+template void CalTile<double>(const size_t output_size, const size_t input_size, const size_t shape_size,
+                              const size_t *input_shape, const size_t *output_shape, const double *input,
+                              double *output, cudaStream_t cuda_stream);
+template void CalTile<float>(const size_t output_size, const size_t input_size, const size_t shape_size,
+                             const size_t *input_shape, const size_t *output_shape, const float *input, float *output,
+                             cudaStream_t cuda_stream);
+template void CalTile<half>(const size_t output_size, const size_t input_size, const size_t shape_size,
+                            const size_t *input_shape, const size_t *output_shape, const half *input, half *output,
+                            cudaStream_t cuda_stream);
+template void CalTile<int16_t>(const size_t output_size, const size_t input_size, const size_t shape_size,
+                               const size_t *input_shape, const size_t *output_shape, const int16_t *input,
+                               int16_t *output, cudaStream_t cuda_stream);
+template void CalTile<int>(const size_t output_size, const size_t input_size, const size_t shape_size,
+                           const size_t *input_shape, const size_t *output_shape, const int *input, int *output,
+                           cudaStream_t cuda_stream);
+template void CalTile<int64_t>(const size_t output_size, const size_t input_size, const size_t shape_size,
+                               const size_t *input_shape, const size_t *output_shape, const int64_t *input,
+                               int64_t *output, cudaStream_t cuda_stream);

mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/tile_impl.cuh

@@ -0,0 +1,27 @@
+/**
+ * Copyright 2021 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_CUDA_IMPL_TILE_IMPL_CUH_
+#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_TILE_IMPL_CUH_
+
+#define TILE_MAX_DIMENSION 100
+#include "runtime/device/gpu/cuda_common.h"
+
+template <typename T>
+void CalTile(const size_t output_size, const size_t input_size, const size_t shape_size, const size_t *input_shape,
+             const size_t *output_shape, const T *input, T *output, cudaStream_t cuda_stream);
+
+#endif  // MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_TILE_IMPL_CUH_