add GPU-ScatterUpdate

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

@@ -0,0 +1,36 @@
+/**
+ * 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 "backend/kernel_compiler/gpu/arrays/scatter_update_gpu_kernel.h"
+
+namespace mindspore {
+namespace kernel {
+MS_REG_GPU_KERNEL_ONE(ScatterUpdate,
+                      KernelAttr()
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddInputAttr(kNumberTypeInt32)
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddOutputAttr(kNumberTypeFloat32),
+                      ScatterUpdateKernel, float)
+MS_REG_GPU_KERNEL_ONE(ScatterUpdate,
+                      KernelAttr()
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddInputAttr(kNumberTypeInt32)
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddOutputAttr(kNumberTypeFloat16),
+                      ScatterUpdateKernel, half)
+}  // namespace kernel
+}  // namespace mindspore

mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/scatter_update_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_BACKEND_KERNEL_COMPILER_GPU_ARRAYS_SCATTER_UPDATE_GPU_KERNEL_H_
+#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_ARRAYS_SCATTER_UPDATE_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/scatter_update_impl.cuh"
+
+namespace mindspore {
+namespace kernel {
+template <typename T>
+class ScatterUpdateKernel : public GpuKernel {
+ public:
+  ScatterUpdateKernel() : input_size_(0), inner_size_(0), indices_size_(0), updates_size_(0) {}
+  ~ScatterUpdateKernel() 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);
+    int *indices = GetDeviceAddress<int>(inputs, 1);
+    T *updates = GetDeviceAddress<T>(inputs, 2);
+    T *output = GetDeviceAddress<T>(outputs, 0);
+    CalScatterUpdate(input_size_, inner_size_, indices_size_, input, indices, updates, output,
+                     reinterpret_cast<cudaStream_t>(stream_ptr));
+    return true;
+  }
+
+  bool Init(const CNodePtr &kernel_node) override {
+    size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
+    if (input_num != 3) {
+      MS_LOG(ERROR) << "Input number is " << input_num << ", but ScatterUpdate needs 3 inputs.";
+      return false;
+    }
+    size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
+    if (output_num != 1) {
+      MS_LOG(ERROR) << "Output number is " << output_num << ", but ScatterUpdate has 1 output.";
+      return false;
+    }
+    auto input_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
+    input_size_ = 1;
+    inner_size_ = 1;
+    for (size_t i = 1; i < input_shape.size(); i++) {
+      inner_size_ *= input_shape[i];
+    }
+    input_size_ = input_shape[0] * inner_size_;
+    auto indices_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 1);
+    indices_size_ = 1;
+    for (size_t i = 0; i < indices_shape.size(); i++) {
+      indices_size_ *= indices_shape[i];
+    }
+    updates_size_ = indices_size_ * inner_size_;
+    InitSizeLists();
+    return true;
+  }
+
+ protected:
+  void InitSizeLists() override {
+    input_size_list_.push_back(input_size_ * sizeof(T));
+    input_size_list_.push_back(indices_size_ * sizeof(int));
+    input_size_list_.push_back(updates_size_ * sizeof(T));
+    output_size_list_.push_back(input_size_ * sizeof(T));
+  }
+
+ private:
+  int input_size_;
+  int inner_size_;
+  int indices_size_;
+  int updates_size_;
+  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_SCATTER_UPDATE_GPU_KERNEL_H_

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

@@ -0,0 +1,45 @@
+/**
+ * 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 "backend/kernel_compiler/gpu/cuda_impl/scatter_update_impl.cuh"
+
+template <typename T>
+__global__ void ScatterUpdate(const int input_size, const int inner_size, const int indices_size, const T *input,
+                              const int *indices, const T *updates, T *output) {
+  for (int pos = blockIdx.x * blockDim.x + threadIdx.x; pos < input_size; pos += blockDim.x * gridDim.x) {
+    output[pos] = input[pos];
+    const int index = pos / inner_size;
+    const int offset = pos % inner_size;
+    for (int i = 0; i < indices_size; i++) {
+      const int update_pos = i * inner_size + offset;
+      output[pos] = (indices[i] == index ? updates[update_pos] : output[pos]);
+    }
+  }
+}
+
+template <typename T>
+void CalScatterUpdate(const int &input_size, const int &inner_size, const int &indices_size, const T *input,
+                      const int *indices, const T *updates, T *output, cudaStream_t cuda_stream) {
+  ScatterUpdate<<<GET_BLOCKS(input_size), GET_THREADS, 0, cuda_stream>>>(input_size, inner_size, indices_size, input,
+                                                                         indices, updates, output);
+}
+
+template void CalScatterUpdate<float>(const int &input_size, const int &inner_size, const int &indices_size,
+                                      const float *input, const int *indices, const float *updates, float *output,
+                                      cudaStream_t cuda_stream);
+template void CalScatterUpdate<half>(const int &input_size, const int &inner_size, const int &indices_size,
+                                     const half *input, const int *indices, const half *updates, half *output,
+                                     cudaStream_t cuda_stream);

mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/scatter_update_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_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_SCATTER_UPDATE_IMPL_CUH_
+#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_SCATTER_UPDATE_IMPL_CUH_
+
+#include "runtime/device/gpu/cuda_common.h"
+
+template <typename T>
+void CalScatterUpdate(const int &input_size, const int &inner_size, const int &indices_size, const T *input,
+                      const int *indices, const T *updates, T *output, cudaStream_t cuda_stream);
+
+#endif  // MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_SCATTER_UPDATE_IMPL_CUH_

tests/st/ops/gpu/test_scatter_update_op.py

@@ -0,0 +1,106 @@
+# 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 numpy as np
+import pytest
+import mindspore.context as context
+import mindspore.nn as nn
+from mindspore import Tensor, Parameter
+from mindspore.ops import operations as P
+
+context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
+# all cases tested against dchip
+
+class TestScatterUpdateNet(nn.Cell):
+    def __init__(self, inputx, indices, updates):
+        super(TestScatterUpdateNet, self).__init__()
+        self.scatter_update = P.ScatterUpdate()
+        self.inputx = Parameter(inputx, name="inputx")
+        self.indices = Parameter(indices, name="indices")
+        self.updates = Parameter(updates, name="updates")
+
+    def construct(self):
+        out = self.scatter_update(self.inputx, self.indices, self.updates)
+        return out
+
+def scatter_update_net(inputx, indices, updates):
+    net = TestScatterUpdateNet(inputx, indices, updates)
+    return net()
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_scatter_update_small_float32():
+    inputx = Tensor(np.zeros((2, 3)).astype(np.float32))
+    indices = Tensor(np.array([0, 1]).astype(np.int32))
+    updates = Tensor(np.arange(6).reshape((2, 3)).astype(np.float32))
+    output = scatter_update_net(inputx, indices, updates)
+    expected = np.array([[0., 1., 2.],
+                         [3., 4., 5.]])
+    np.testing.assert_array_almost_equal(output.asnumpy(), expected)
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_scatter_update_input_less_than_1_float32():
+    inputx = Tensor(np.array([[0.214141, 0.415151, 0.51516],
+                              [0.876542, 0.451611, 0.55112],
+                              [0.111244, 0.633333, 0.34444]]).astype(np.float32))
+    indices = Tensor(np.array([1, 0, 2]).astype(np.int32))
+    updates = Tensor(np.arange(34, 43).reshape((3, 3)).astype(np.float32))
+    output = scatter_update_net(inputx, indices, updates)
+    expected = np.array([[37., 38., 39.],
+                         [34., 35., 36.],
+                         [40., 41., 42.]], dtype=np.float32)
+    np.testing.assert_array_almost_equal(output.asnumpy(), expected)
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_scatter_update_float16():
+    inputx = Tensor(np.zeros((2, 3)).astype(np.float16))
+    indices = Tensor(np.array([0, 1]).astype(np.int32))
+    updates = Tensor(np.arange(6).reshape((2, 3)).astype(np.float16))
+    output = scatter_update_net(inputx, indices, updates)
+    expected = np.array([[0., 1., 2.],
+                         [3., 4., 5.]])
+    np.testing.assert_array_almost_equal(output.asnumpy(), expected)
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_scatter_update_large_float16():
+    inputx = Tensor(np.zeros((4, 3)).astype(np.float16))
+    indices = Tensor(np.array([[2, 1], [0, 3]]).astype(np.int32))
+    updates = Tensor(np.arange(63, 75).reshape((2, 2, 3)).astype(np.float16))
+    output = scatter_update_net(inputx, indices, updates)
+    expected = np.array([[69., 70., 71.],
+                         [66., 67., 68.],
+                         [63., 64., 65.],
+                         [72., 73., 74.]])
+    np.testing.assert_array_almost_equal(output.asnumpy(), expected)
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_scatter_update_disordered_float16():
+    inputx = Tensor(np.flip(np.arange(34, 46).reshape(3, 4).astype(np.float16)))
+    indices = Tensor(np.array([1, 2]).astype(np.int32))
+    updates = Tensor(np.arange(63, 71).reshape((2, 4)).astype(np.float16))
+    output = scatter_update_net(inputx, indices, updates)
+    expected = np.array([[45., 44., 43., 42.],
+                         [63., 64., 65., 66.],
+                         [67., 68., 69., 70.]])
+    np.testing.assert_array_almost_equal(output.asnumpy(), expected)