change var name

paddle/fluid/operators/triu_indices_op.cc

@@ -37,12 +37,12 @@ class TriuIndicesOpMaker : public framework::OpProtoAndCheckerMaker {
   void Make() override {
     AddOutput("out",
               "Tensor, the output tensor, with the shape (2,x), x bounded by "
-              "[0,rows*cols])");
-    AddAttr<int>("rows",
+              "[0,row*col])");
+    AddAttr<int>("row",
                  "int number, the input of triu_indices op"
                  "which describes the number of row of the matrix")
         .SetDefault(0);
-    AddAttr<int>("cols",
+    AddAttr<int>("col",
                  "int number, the input of triu_indices op"
                  "which describes the number of col of the matrix")
         .SetDefault(0);

paddle/phi/api/yaml/legacy_api.yaml

@@ -2748,14 +2748,14 @@
   backward : trilinear_interp_grad
 
 - api : triu_indices
-  args : (int rows, int cols, int offset, DataType dtype, Place place={})
+  args : (int row, int col, int offset, DataType dtype, Place place={})
   output : Tensor(out)
   infer_meta :
     func : TriuIndicesInferMeta
-    param : [rows, cols, offset, dtype]
+    param : [row, col, offset, dtype]
   kernel :
     func : triu_indices
-    param : [rows, cols, offset, dtype]
+    param : [row, col, offset, dtype]
     data_type : dtype
     backend : place
 

paddle/phi/infermeta/nullary.cc

@@ -154,7 +154,7 @@ void TrilIndicesInferMeta(
 }
 
 void TriuIndicesInferMeta(
-    int rows, int cols, int offset, DataType dtype, MetaTensor* out) {
+    int row, int col, int offset, DataType dtype, MetaTensor* out) {
   // number of elements in the first row of the tril,bounded by [0, cols]
   // use total item number minus bottom rectangle item number to get
   // the above rectangle item number
@@ -163,21 +163,21 @@ void TriuIndicesInferMeta(
   // the item on the diagonal line
   offset = offset - 1;
   auto n_first_row =
-      offset > 0 ? std::min<int64_t>(cols, 1 + offset) : rows + offset > 0;
+      offset > 0 ? std::min<int64_t>(col, 1 + offset) : row + offset > 0;
   // number of elements in the last row of the tril, bounded by [0, cols]
   auto n_last_row =
-      std::max<int64_t>(0, std::min<int64_t>(cols, rows + offset));
+      std::max<int64_t>(0, std::min<int64_t>(col, row + offset));
   // number of rows, bounded by [0, rows]
-  auto n_row_all = std::max<int64_t>(0, std::min<int64_t>(rows, rows + offset));
+  auto n_row_all = std::max<int64_t>(0, std::min<int64_t>(row, row + offset));
   auto n_row_trapezoid = (n_last_row - n_first_row + 1);
   // calculate # of elements in the top trapezoid
   auto tril_size = (n_first_row + n_last_row) * n_row_trapezoid >> 1;
   // calculate # of elements in the bottom rectangle if there is any
   auto diff_row = n_row_all - n_row_trapezoid;
   if (diff_row > 0) {
-    tril_size += diff_row * cols;
+    tril_size += diff_row * col;
   }
-  std::vector<int64_t> tmp = {2, rows * cols - tril_size};
+  std::vector<int64_t> tmp = {2, row * col - tril_size};
   auto out_dims = phi::make_ddim(tmp);
   out->set_dims(out_dims);
   out->set_dtype(dtype);

paddle/phi/infermeta/nullary.h

@@ -76,5 +76,5 @@ void TrilIndicesInferMeta(
     int rows, int cols, int offset, DataType dtype, MetaTensor* out);
 
 void TriuIndicesInferMeta(
-    int rows, int cols, int offset, DataType dtype, MetaTensor* out);
+    int row, int col, int offset, DataType dtype, MetaTensor* out);
 }  // namespace phi

paddle/phi/kernels/cpu/triu_indices_kernel.cc

@@ -20,8 +20,8 @@
 namespace phi {
 template <typename T, typename Context>
 void TriuIndicesKernel(const Context& dev_ctx,
-                       int rows,
-                       int cols,
+                       int row,
+                       int col,
                        int offset,
                        DataType dtype,
                        DenseTensor* out) {
@@ -36,7 +36,7 @@ void TriuIndicesKernel(const Context& dev_ctx,
 
     // move to the next column and check if (r, c) is still in bound
     c += 1;
-    if (c >= cols) {
+    if (c >= col) {
       r += 1;
       // not typing std::max with scalar_t as it could be an unsigned type
       // NOTE: not necessary to check if c is less than col or overflows here,

paddle/phi/kernels/gpu/triu_indices_kernel.cu

@@ -25,7 +25,7 @@ namespace phi {
 
 template <typename T>
 __device__ inline int resolve_root_int(int b, int cX4, int x, int32_t sign) {
-  int bXb_cX4 = b * b - cX4;
+  int64_t bXb_cX4 = b * b - cX4;
   double sr = ::sqrt(static_cast<double>(bXb_cX4));
   T res = ::__double2ll_rd((-b + sign * sr) / 2);
   if (bXb_cX4 != static_cast<int>(sr * sr)) {
@@ -90,8 +90,8 @@ __global__ void triu_indices_kernel(T* out_data,
 
 template <typename T, typename Context>
 void TriuIndicesKernel(const Context& dev_ctx,
-                       int rows,
-                       int cols,
+                       int row,
+                       int col,
                        int offset,
                        DataType dtype,
                        DenseTensor* out) {
@@ -103,14 +103,14 @@ void TriuIndicesKernel(const Context& dev_ctx,
 
   if (triu_size > 0) {
     // # of triu elements in the first row
-    auto m_first_row = offset > 0 ? std::max<int>(cols - offset, 0)
+    auto m_first_row = offset > 0 ? std::max<int>(col - offset, 0)
                                   :  // upper bounded by col
-                           cols;
+                           col;
 
     // size of the top rectangle
     int rectangle_size = 0;
     if (offset < 0) {
-      rectangle_size = std::min<int>(rows, -offset) * cols;
+      rectangle_size = std::min<int>(row, -offset) * col;
     }
 
     //  using gpu_launch_config to get grid_size and block_size
@@ -122,7 +122,7 @@ void TriuIndicesKernel(const Context& dev_ctx,
                              dev_ctx.stream()>>>(out_data,
                                                  std::max<int>(0, offset),
                                                  m_first_row,
-                                                 cols,
+                                                 col,
                                                  rectangle_size,
                                                  triu_size);
   }

paddle/phi/kernels/triu_indices_kernel.h

@@ -20,8 +20,8 @@ namespace phi {
 
 template <typename T, typename Context>
 void TriuIndicesKernel(const Context& dev_ctx,
-                       int rows,
-                       int cols,
+                       int row,
+                       int col,
                        int offset,
                        DataType dtype,
                        DenseTensor* out);

python/paddle/fluid/tests/unittests/test_triu_indices_op.py

@@ -36,26 +36,26 @@ def test_check_output(self):
         self.check_output()
 
     def init_config(self):
-        self.attrs = {'rows': 4, 'cols': 4, 'offset': -1}
-        self.target = np.triu_indices(self.attrs['rows'], self.attrs['offset'],
-                                      self.attrs['cols'])
+        self.attrs = {'row': 4, 'col': 4, 'offset': -1}
+        self.target = np.triu_indices(self.attrs['row'], self.attrs['offset'],
+                                      self.attrs['col'])
         self.target = np.array(self.target)
 
 
 class TestTriuIndicesOpCase1(TestTriuIndicesOp):
 
     def init_config(self):
-        self.attrs = {'rows': 0, 'cols': 0, 'offset': 0}
+        self.attrs = {'row': 0, 'col': 0, 'offset': 0}
         self.target = np.triu_indices(0, 0, 0)
         self.target = np.array(self.target)
 
 
 class TestTriuIndicesOpCase2(TestTriuIndicesOp):
 
     def init_config(self):
-        self.attrs = {'rows': 4, 'cols': 4, 'offset': 2}
-        self.target = np.triu_indices(self.attrs['rows'], self.attrs['offset'],
-                                      self.attrs['cols'])
+        self.attrs = {'row': 4, 'col': 4, 'offset': 2}
+        self.target = np.triu_indices(self.attrs['row'], self.attrs['offset'],
+                                      self.attrs['col'])
         self.target = np.array(self.target)
 
 

python/paddle/tensor/creation.py

@@ -1989,7 +1989,7 @@ def triu_indices(row, col=None, offset=0, dtype='int64'):
         return out
 
     if _in_legacy_dygraph():
-        out = _C_ops.triu_indices('rows', row, 'cols', col, 'offset', offset,
+        out = _C_ops.triu_indices('row', row, 'col', col, 'offset', offset,
                                   "dtype", dtype)
         return out
 
@@ -2002,8 +2002,8 @@ def triu_indices(row, col=None, offset=0, dtype='int64'):
                          inputs={},
                          outputs={'out': [out]},
                          attrs={
-                             'rows': row,
-                             'cols': col,
+                             'row': row,
+                             'col': col,
                              'offset': offset,
                              'dtype': dtype
                          })