From 46afb18e2586bf61b311d9c26e2b4514ace9d34c Mon Sep 17 00:00:00 2001
From: VectorSL <shiliang10@huawei.com>
Date: Tue, 16 Jun 2020 14:56:59 +0800
Subject: [PATCH] update argmaxwithvalue

---
 .../gpu/arrays/argmaxwithvalue_gpu_kernel.h   | 39 +++++++------------
 .../gpu/cuda_impl/argmaxwithvalue_impl.cu     |  6 +--
 .../gpu/cuda_impl/argmaxwithvalue_impl.cuh    |  2 +-
 3 files changed, 17 insertions(+), 30 deletions(-)

diff --git a/mindspore/ccsrc/kernel/gpu/arrays/argmaxwithvalue_gpu_kernel.h b/mindspore/ccsrc/kernel/gpu/arrays/argmaxwithvalue_gpu_kernel.h
index 9d42f31eb6..fb7796b022 100644
--- a/mindspore/ccsrc/kernel/gpu/arrays/argmaxwithvalue_gpu_kernel.h
+++ b/mindspore/ccsrc/kernel/gpu/arrays/argmaxwithvalue_gpu_kernel.h
@@ -26,15 +26,7 @@ namespace kernel {
 template <typename T, typename S>
 class ArgmaxWithValueGpuKernel : public GpuKernel {
  public:
-  ArgmaxWithValueGpuKernel()
-      : input_size_(0),
-        output_size_(0),
-        workspace_size_(0),
-        axis_(0),
-        dims_(1),
-        bound_(0),
-        outerSize_(0),
-        innerSize_(0) {}
+  ArgmaxWithValueGpuKernel() : input_size_(0), output_size_(0), bound_(0), outerSize_(0), innerSize_(0) {}
   ~ArgmaxWithValueGpuKernel() override = default;
 
   const std::vector<size_t> &GetInputSizeList() const override { return input_size_list_; }
@@ -46,37 +38,36 @@ class ArgmaxWithValueGpuKernel : public GpuKernel {
     T *input = GetDeviceAddress<T>(inputs, 0);
     T *output = GetDeviceAddress<T>(outputs, 1);
     S *index = GetDeviceAddress<S>(outputs, 0);
-    CalArgmaxWithValue(input_size_ / sizeof(T), input, bound_, outerSize_, innerSize_, axis_, dims_, index, output,
+    CalArgmaxWithValue(input_size_ / sizeof(T), input, bound_, outerSize_, innerSize_, index, output,
                        reinterpret_cast<cudaStream_t>(stream_ptr));
     return true;
   }
 
   bool Init(const CNodePtr &kernel_node) override {
-    shape_ = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
+    std::vector<size_t> shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
     auto output_shape = AnfAlgo::GetOutputInferShape(kernel_node, 1);
-    dims_ = shape_.size();
-
-    axis_ = GetAttr<int>(kernel_node, "axis");
-    if (axis_ < 0) {
-      axis_ += dims_;
+    int dims = shape.size();
+    int axis = GetAttr<int>(kernel_node, "axis");
+    if (axis < 0) {
+      axis += dims;
     }
     input_size_ = sizeof(T);
-    for (auto x : shape_) {
+    for (auto x : shape) {
       input_size_ *= x;
     }
     output_size_ = sizeof(S);
     for (auto x : output_shape) {
       output_size_ *= x;
     }
-    bound_ = shape_[axis_];
+    bound_ = shape[axis];
     outerSize_ = 1;
-    for (int i = axis_ - 1; i >= 0; i--) {
-      outerSize_ *= shape_[i];
+    for (int i = axis - 1; i >= 0; i--) {
+      outerSize_ *= shape[i];
     }
 
     innerSize_ = 1;
-    for (int i = axis_ + 1; i < dims_; i++) {
-      innerSize_ *= shape_[i];
+    for (int i = axis + 1; i < dims; i++) {
+      innerSize_ *= shape[i];
     }
     InitSizeLists();
     return true;
@@ -92,13 +83,9 @@ class ArgmaxWithValueGpuKernel : public GpuKernel {
  private:
   size_t input_size_;
   size_t output_size_;
-  size_t workspace_size_;
   std::vector<size_t> input_size_list_;
   std::vector<size_t> output_size_list_;
   std::vector<size_t> workspace_size_list_;
-  std::vector<size_t> shape_;
-  int axis_;
-  int dims_;
   int bound_;
   int outerSize_;
   int innerSize_;
diff --git a/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cu b/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cu
index 47a794cdcd..a0687a2768 100644
--- a/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cu
+++ b/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cu
@@ -44,15 +44,15 @@ __global__ void ArgmaxWithValue(size_t size, const T* input, const int bound, in
 
 template <typename T, typename S>
 void CalArgmaxWithValue(size_t size, const T* input, const int bound_, const int outerSize_, const int innerSize_,
-                        int axis_, int dims_, S* index, T* output, cudaStream_t cuda_stream) {
+                        S* index, T* output, cudaStream_t cuda_stream) {
   ArgmaxWithValue<<<GET_BLOCKS(size), GET_THREADS, 0, cuda_stream>>>(size, input, bound_, outerSize_, innerSize_,
                                                                      index, output);
   return;
 }
 
 template void CalArgmaxWithValue<float, int>(size_t size, const float* input, const int bound_, const int outerSize_,
-                                  const int innerSize_, int axis_, int dims_, int* index, float* output,
+                                  const int innerSize_, int* index, float* output,
                                   cudaStream_t cuda_stream);
 template void CalArgmaxWithValue<half, int>(size_t size, const half* input, const int bound_, const int outerSize_,
-                                  const int innerSize_, int axis_, int dims_, int* index, half* output,
+                                  const int innerSize_, int* index, half* output,
                                   cudaStream_t cuda_stream);
diff --git a/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cuh b/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cuh
index eebe4c8fa6..0d4f4b62a3 100644
--- a/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cuh
+++ b/mindspore/ccsrc/kernel/gpu/cuda_impl/argmaxwithvalue_impl.cuh
@@ -18,5 +18,5 @@
 #define MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMP_ARGMAXWITHVALUE_H_
 template <typename T, typename S>
 void CalArgmaxWithValue(size_t size, const T* input, const int bound_, const int outerSize_, const int innerSize_,
-                        int axis_, int dims_, S* index, T* output, cudaStream_t cuda_stream);
+                        S* index, T* output, cudaStream_t cuda_stream);
 #endif  // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMP_ARGMAXWITHVALUE_H_