add float64 support to concat GPU

mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/concatv2_gpu_kernel.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2021 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.
@@ -18,6 +18,9 @@
 
 namespace mindspore {
 namespace kernel {
+MS_REG_GPU_KERNEL_ONE(
+  Concat, KernelAttr().AddAllSameAttr(true).AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64),
+  ConcatV2GpuFwdKernel, double)
 MS_REG_GPU_KERNEL_ONE(
   Concat, KernelAttr().AddAllSameAttr(true).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
   ConcatV2GpuFwdKernel, float)

mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/concatv2_gpu_kernel.h

@@ -14,8 +14,8 @@
  * limitations under the License.
  */
 
-#ifndef MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CONCATV2_GPU_KERNEL_H
-#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CONCATV2_GPU_KERNEL_H
+#ifndef MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_ARRAYS_CONCATV2_GPU_KERNEL_H_
+#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_ARRAYS_CONCATV2_GPU_KERNEL_H_
 
 #include <vector>
 #include <memory>
@@ -133,4 +133,4 @@ class ConcatV2GpuFwdKernel : public GpuKernel {
 }  // namespace kernel
 }  // namespace mindspore
 
-#endif  // MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CONCATV2_GPU_KERNEL_H
+#endif  // MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_ARRAYS_CONCATV2_GPU_KERNEL_H_

mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/concatv2_impl.cu

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2021 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.
@@ -19,9 +19,8 @@
 #include <cuda_runtime.h>
 #include "backend/kernel_compiler/gpu/cuda_impl/concatv2_impl.cuh"
 template <typename T>
-__global__ void Concat(const size_t size, const int input_num,
-                       const int all_size_before_axis, const int all_size_axis,
-                       int* len_axis, T** inputs, T* output) {
+__global__ void Concat(const size_t size, const int input_num, const int all_size_before_axis, const int all_size_axis,
+                       int *len_axis, T **inputs, T *output) {
   for (int pos = blockIdx.x * blockDim.x + threadIdx.x; pos < (size); pos += blockDim.x * gridDim.x) {
     int num = pos % all_size_before_axis / all_size_axis;
     int block = -1;
@@ -37,45 +36,38 @@ __global__ void Concat(const size_t size, const int input_num,
     }
     block_len = len_axis[block];
     axis_inc -= len_axis[block];
-    int block_pos = pos / all_size_before_axis * block_len * all_size_axis +
-                    (num - axis_inc) * all_size_axis + pos % all_size_axis;;
+    int block_pos =
+      pos / all_size_before_axis * block_len * all_size_axis + (num - axis_inc) * all_size_axis + pos % all_size_axis;
     output[pos] = inputs[block][block_pos];
   }
   return;
 }
 
 template <typename T>
-void ConcatKernel(const size_t size, const int input_num,
-                  const int all_size_before_axis, const int all_size_axis,
-                  int* len_axis, T** inputs, T* output,
-                  cudaStream_t cuda_stream) {
-  Concat<<<GET_BLOCKS(size), GET_THREADS, 0, cuda_stream>>>(size, input_num,
-                                                            all_size_before_axis, all_size_axis,
+void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis, const int all_size_axis,
+                  int *len_axis, T **inputs, T *output, cudaStream_t cuda_stream) {
+  Concat<<<GET_BLOCKS(size), GET_THREADS, 0, cuda_stream>>>(size, input_num, all_size_before_axis, all_size_axis,
                                                             len_axis, inputs, output);
   return;
 }
 
-template void ConcatKernel(const size_t size, const int input_num,
-                           const int all_size_before_axis, const int all_size_axis,
-                           int* len_axis, float** inputs, float* output,
+template void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis,
+                           const int all_size_axis, int *len_axis, double **inputs, double *output,
                            cudaStream_t cuda_stream);
-template void ConcatKernel(const size_t size, const int input_num,
-                           const int all_size_before_axis, const int all_size_axis,
-                           int* len_axis, int** inputs, int* output,
+template void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis,
+                           const int all_size_axis, int *len_axis, float **inputs, float *output,
                            cudaStream_t cuda_stream);
-template void ConcatKernel(const size_t size, const int input_num,
-                           const int all_size_before_axis, const int all_size_axis,
-                           int* len_axis, half** inputs, half* output,
+template void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis,
+                           const int all_size_axis, int *len_axis, int **inputs, int *output, cudaStream_t cuda_stream);
+template void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis,
+                           const int all_size_axis, int *len_axis, half **inputs, half *output,
                            cudaStream_t cuda_stream);
-template void ConcatKernel(const size_t size, const int input_num,
-                           const int all_size_before_axis, const int all_size_axis,
-                           int* len_axis, short** inputs, short* output,  // NOLINT
+template void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis,
+                           const int all_size_axis, int *len_axis, short **inputs, short *output,  // NOLINT
                            cudaStream_t cuda_stream);
-template void ConcatKernel(const size_t size, const int input_num,
-                           const int all_size_before_axis, const int all_size_axis,
-                           int* len_axis, unsigned char** inputs, unsigned char* output,
+template void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis,
+                           const int all_size_axis, int *len_axis, unsigned char **inputs, unsigned char *output,
                            cudaStream_t cuda_stream);
-template void ConcatKernel(const size_t size, const int input_num,
-                           const int all_size_before_axis, const int all_size_axis,
-                           int* len_axis, bool** inputs, bool* output,
+template void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis,
+                           const int all_size_axis, int *len_axis, bool **inputs, bool *output,
                            cudaStream_t cuda_stream);

mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/concatv2_impl.cuh

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * Copyright 2019-2021 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.
@@ -14,13 +14,11 @@
  * limitations under the License.
  */
 
-#ifndef MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_CONCATV2IMPL_H_
-#define MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_CONCATV2IMPL_H_
+#ifndef MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_CONCATV2_IMPL_CUH_
+#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_CONCATV2_IMPL_CUH_
 
 #include "runtime/device/gpu/cuda_common.h"
 template <typename T>
-void ConcatKernel(const size_t size, const int input_num,
-                  const int all_size_before_axis, const int all_size_axis,
-                  int* len_axis, T** inputs, T* output,
-                  cudaStream_t cuda_stream);
-#endif  // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_CONCATV2IMPL_H_
+void ConcatKernel(const size_t size, const int input_num, const int all_size_before_axis, const int all_size_axis,
+                  int *len_axis, T **inputs, T *output, cudaStream_t cuda_stream);
+#endif  // MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_CUDA_IMPL_CONCATV2_IMPL_CUH_

mindspore/ops/operations/array_ops.py

@@ -2162,7 +2162,7 @@ class Concat(PrimitiveWithInfer):
 
     @prim_attr_register
     def __init__(self, axis=0):
-        """Initialize Tile"""
+        """Initialize Concat"""
         validator.check_value_type("axis", axis, [int], self.name)
 
     def __infer__(self, input_x):

tests/st/ops/gpu/test_concatv2_op.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2021 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.
@@ -49,9 +49,14 @@ def axis32(nptype):
                         [1., 2., 3.]],
                        [[2., 4., 5.],
                         [3., 6., 7.]]]).astype(nptype)
-    print(output)
     assert (output.asnumpy() == expect).all()
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_axis32_float64():
+    axis32(np.float64)
+
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
@@ -106,8 +111,12 @@ def axis43(nptype):
                         [[12., 13., 18., 19., 20.],
                          [14., 15., 21., 22., 23.]]]]).astype(nptype)
     assert (output.asnumpy() == expect).all()
-    print(output)
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_axis43_float64():
+    axis43(np.float64)
 
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
@@ -155,7 +164,12 @@ def axis21(nptype):
     expect = np.array([[0., 1., 0., 1., 2.],
                        [2., 3., 3., 4., 5.]]).astype(nptype)
     assert (output.asnumpy() == expect).all()
-    print(output)
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_axis21_float64():
+    axis21(np.float64)
 
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
@@ -208,6 +222,12 @@ def concat_3i(nptype):
     diff = output_ms.asnumpy() - output_np
     assert np.all(diff < error)
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_concat_3i_float64():
+    concat_3i(np.float64)
+
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
@@ -273,6 +293,12 @@ def concat_4i(nptype):
     diff = output_ms.asnumpy() - output_np
     assert np.all(diff < error)
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_concat_4i_float64():
+    concat_4i(np.float64)
+
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard