!311 GPU add akg kernel select

Merge pull request !311 from VectorSL/select

mindspore/ccsrc/kernel/gpu/arrays/select_gpu_kernel.cc

@@ -0,0 +1,43 @@
+/**
+ * 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/arrays/select_gpu_kernel.h"
+
+namespace mindspore {
+namespace kernel {
+MS_REG_GPU_KERNEL_ONE(Select,
+                      KernelAttr()
+                        .AddInputAttr(kNumberTypeBool)
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddOutputAttr(kNumberTypeFloat32),
+                      SelectGpuKernel, float)
+MS_REG_GPU_KERNEL_ONE(Select,
+                      KernelAttr()
+                        .AddInputAttr(kNumberTypeBool)
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddOutputAttr(kNumberTypeFloat16),
+                      SelectGpuKernel, half)
+MS_REG_GPU_KERNEL_ONE(Select,
+                      KernelAttr()
+                        .AddInputAttr(kNumberTypeBool)
+                        .AddInputAttr(kNumberTypeInt32)
+                        .AddInputAttr(kNumberTypeInt32)
+                        .AddOutputAttr(kNumberTypeInt32),
+                      SelectGpuKernel, int)
+}  // namespace kernel
+}  // namespace mindspore

mindspore/ccsrc/kernel/gpu/arrays/select_gpu_kernel.h

@@ -0,0 +1,95 @@
+/**
+ * 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_SELECT_GPU_KERNEL_H
+#define MINDSPORE_CCSRC_KERNEL_GPU_SELECT_GPU_KERNEL_H
+
+#include <vector>
+#include "kernel/gpu/gpu_kernel.h"
+#include "kernel/gpu/gpu_kernel_factory.h"
+#include "kernel/gpu/cuda_impl/select_impl.cuh"
+
+namespace mindspore {
+namespace kernel {
+template <typename T>
+class SelectGpuKernel : public GpuKernel {
+ public:
+  SelectGpuKernel() : input_size_(0), output_size_(0) {}
+  ~SelectGpuKernel() 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> &,
+              const std::vector<AddressPtr> &outputs, uintptr_t stream_ptr) override {
+    bool *input_cond = GetDeviceAddress<bool>(inputs, 0);
+    T *input_x = GetDeviceAddress<T>(inputs, 1);
+    T *input_y = GetDeviceAddress<T>(inputs, 2);
+    T *output = GetDeviceAddress<T>(outputs, 0);
+    CalSelect(output_size_ / sizeof(T), input_cond, input_x, input_y, output,
+              reinterpret_cast<cudaStream_t>(stream_ptr));
+    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(bool);
+    output_size_ = sizeof(T);
+    for (size_t x : shape) {
+      input_size_ = input_size_ * x;
+      output_size_ = output_size_ * x;
+    }
+    InitSizeLists();
+    return true;
+  }
+
+ protected:
+  void InitSizeLists() override {
+    input_size_list_.push_back(input_size_);
+    input_size_list_.push_back(output_size_);
+    input_size_list_.push_back(output_size_);
+    output_size_list_.push_back(output_size_);
+  }
+
+ private:
+  bool CheckParam(const CNodePtr &kernel_node) {
+    size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
+    if (input_num != 3) {
+      MS_LOG(ERROR) << "Input number is " << input_num << ", but SelectGpuKernel needs 3 output.";
+      return false;
+    }
+    size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
+    if (output_num != 1) {
+      MS_LOG(ERROR) << "Output number is " << output_num << ", but SelectGpuKernel needs 1 output.";
+      return false;
+    }
+    return true;
+  }
+
+  std::vector<size_t> input_size_list_;
+  std::vector<size_t> output_size_list_;
+  std::vector<size_t> workspace_size_list_;
+
+  size_t input_size_;
+  size_t output_size_;
+};
+}  // namespace kernel
+}  // namespace mindspore
+
+#endif  // MINDSPORE_CCSRC_KERNEL_GPU_SELECT_GPU_KERNEL_H

mindspore/ccsrc/kernel/gpu/cuda_impl/select_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 <stdio.h>
+#include <stdint.h>
+#include <include/cuda_runtime.h>
+#include "kernel/gpu/cuda_impl/select_impl.cuh"
+
+template <typename T>
+__global__ void Select(const size_t size, const bool* cond, const T* input_x, const T* input_y, T* output) {
+  for (size_t pos = blockIdx.x * blockDim.x + threadIdx.x; pos < (size); pos += blockDim.x * gridDim.x) {
+    output[pos] = cond[pos] ? input_x[pos] : input_y[pos];
+  }
+  return;
+}
+
+template <typename T>
+void CalSelect(const size_t size, const bool* cond, const T* input_x, const T* input_y, T* output,
+               cudaStream_t cuda_stream) {
+  Select<<<GET_BLOCKS(size), GET_THREADS, 0, cuda_stream>>>(size, cond, input_x, input_y, output);
+  return;
+}
+
+template void CalSelect<float>(const size_t size, const bool* cond, const float* input_X, const float* input_y,
+                               float* output, cudaStream_t cuda_stream);
+template void CalSelect<int>(const size_t size, const bool* cond, const int* input_X, const int* input_y, int* output,
+                             cudaStream_t cuda_stream);
+template void CalSelect<half>(const size_t size, const bool* cond, const half* input_X, const half* input_y,
+                              half* output, cudaStream_t cuda_stream);

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

@@ -0,0 +1,25 @@
+/**
+ * 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_SELECT_IMPL_H_
+#define MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_SELECT_IMPL_H_
+
+#include "device/gpu/cuda_common.h"
+
+template <typename T>
+void CalSelect(const size_t size, const bool* cond, const T* input_x, const T* input_y, T* output,
+               cudaStream_t cuda_stream);
+#endif  // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_SELECT_IMPL_H_

tests/st/ops/gpu/test_select_op.py

@@ -0,0 +1,47 @@
+# 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.select = P.Select()
+
+    def construct(self, cond, x, y):
+        return self.select(cond, x, y)
+
+cond = np.array([[True, False], [True, False]]).astype(np.bool)
+x = np.array([[1.2, 1], [1, 0]]).astype(np.float32)
+y = 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_select():
+    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
+    select = Net()
+    output = select(Tensor(cond), Tensor(x), Tensor(y))
+    expect = [[1.2, 2], [1, 4.0]]
+    error = np.ones(shape=[2, 2]) * 1.0e-6
+    diff = output.asnumpy() - expect
+    assert np.all(diff < error)
+    assert np.all(-diff < error)