add int64 support to transpose GPU

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

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * 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.
@@ -23,5 +23,7 @@ MS_REG_GPU_KERNEL_ONE(Transpose, KernelAttr().AddInputAttr(kNumberTypeFloat16).A
                       TransposeGpuFwdKernel, half)
 MS_REG_GPU_KERNEL_ONE(Transpose, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32),
                       TransposeGpuFwdKernel, int)
+MS_REG_GPU_KERNEL_ONE(Transpose, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt64),
+                      TransposeGpuFwdKernel, int64_t)
 }  // namespace kernel
 }  // namespace mindspore

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

@@ -79,10 +79,7 @@ class TransposeGpuFwdKernel : public GpuKernel {
     }
     input_size_ *= sizeof(T);
     output_size_ = input_size_;
-    std::vector<int> perm;
+    std::vector<int64_t> perm = GetAttr<std::vector<int64_t>>(kernel_node, "perm");
-    std::vector<int64_t> perm_me = GetAttr<std::vector<int64_t>>(kernel_node, "perm");
-    (void)std::transform(perm_me.begin(), perm_me.end(), std::back_inserter(perm),
-                         [](const int64_t &value) { return static_cast<int>(value); });
     for (size_t j = 0; j < perm.size(); j++) {
       input_axis_.push_back(perm[j]);
     }

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

@@ -20,8 +20,8 @@
 #include "runtime/device/gpu/cuda_common.h"
 
 template <typename T>
-__global__ void Transpose(const size_t size, const T* input, const size_t* input_shape,
+__global__ void Transpose(const size_t size, const T *input, const size_t *input_shape, const size_t *input_axis,
-                          const size_t* input_axis, const size_t shape_size, T* output) {
+                          const size_t shape_size, T *output) {
   size_t pos_size;
   size_t temp_pos;
   size_t newpos;
@@ -36,7 +36,7 @@ __global__ void Transpose(const size_t size, const T* input, const size_t* input
     temp_pos = pos;
     pos_size = size / input_shape[0];
     pos_array[0] = temp_pos / pos_size;
-    for (int i = 1; i < shape_size; i++) {
+    for (size_t i = 1; i < shape_size; i++) {
       temp_pos -= pos_array[i - 1] * pos_size;
       pos_size = pos_size / input_shape[i];
       pos_array[i] = temp_pos / pos_size;
@@ -44,7 +44,7 @@ __global__ void Transpose(const size_t size, const T* input, const size_t* input
 
     newpos = pos_array[input_axis[shape_size - 1]];
     newpos_size = 1;
-    for (int j = shape_size - 2; j >= 0; j--) {
+    for (int64_t j = shape_size - 2; j >= 0; j--) {
       newpos_size *= input_shape[input_axis[j + 1]];
       newpos += pos_array[input_axis[j]] * newpos_size;
     }
@@ -54,19 +54,22 @@ __global__ void Transpose(const size_t size, const T* input, const size_t* input
   return;
 }
 template <typename T>
-void CalTranspose(const size_t size, const T* input, const size_t* input_shape, const size_t* input_axis,
+void CalTranspose(const size_t size, const T *input, const size_t *input_shape, const size_t *input_axis,
-                  const size_t shape_size, T* output, cudaStream_t cuda_stream) {
+                  const size_t shape_size, T *output, cudaStream_t cuda_stream) {
   Transpose<<<GET_BLOCKS(size), GET_THREADS, 0, cuda_stream>>>(size, input, input_shape, input_axis, shape_size,
                                                                output);
   return;
 }
 
-template void CalTranspose<float>(const size_t size, const float* input, const size_t* input_shape,
+template void CalTranspose<float>(const size_t size, const float *input, const size_t *input_shape,
-                                  const size_t* input_axis, const size_t shape_size, float* output,
+                                  const size_t *input_axis, const size_t shape_size, float *output,
                                   cudaStream_t cuda_stream);
-template void CalTranspose<half>(const size_t size, const half* input, const size_t* input_shape,
+template void CalTranspose<half>(const size_t size, const half *input, const size_t *input_shape,
-                                 const size_t* input_axis, const size_t shape_size, half* output,
+                                 const size_t *input_axis, const size_t shape_size, half *output,
                                  cudaStream_t cuda_stream);
-template void CalTranspose<int>(const size_t size, const int* input, const size_t* input_shape,
+template void CalTranspose<int>(const size_t size, const int *input, const size_t *input_shape,
-                                const size_t* input_axis, const size_t shape_size, int* output,
+                                const size_t *input_axis, const size_t shape_size, int *output,
+                                cudaStream_t cuda_stream);
+template void CalTranspose<int64_t>(const size_t size, const int64_t *input, const size_t *input_shape,
+                                    const size_t *input_axis, const size_t shape_size, int64_t *output,
                                     cudaStream_t cuda_stream);

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

@@ -1,5 +1,5 @@
 /**
- * Copyright 2019 Huawei Technologies Co., Ltd
+ * 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.

tests/st/ops/gpu/test_transpose_op.py

@@ -1,4 +1,4 @@
-# Copyright 2019 Huawei Technologies Co., Ltd
+# 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.
@@ -253,6 +253,24 @@ def test_transpose_float16():
 def test_transpose_int32():
     transpose1(np.int32)
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_transpose_int64():
+    transpose1(np.int64)
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_transpose_dynamic_int64():
+    transpose_d(np.int64)
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_transpose_dynamic_two_inputs_int64():
+    transpose_d2(np.int64)
+
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard