Modify the names of parameter check

mindspore/nn/layer/math.py

@@ -245,7 +245,7 @@ class LGamma(Cell):
 
     def construct(self, x):
         input_dtype = self.dtype(x)
-        _check_input_dtype("input", input_dtype, [mstype.float16, mstype.float32], self.cls_name)
+        _check_input_dtype("x", input_dtype, [mstype.float16, mstype.float32], self.cls_name)
         infinity = self.fill(input_dtype, self.shape(x), self.inf)
 
         need_to_reflect = self.less(x, 0.5)
@@ -352,7 +352,7 @@ class DiGamma(Cell):
 
     def construct(self, x):
         input_dtype = self.dtype(x)
-        _check_input_dtype("input_x", input_dtype, [mstype.float16, mstype.float32], self.cls_name)
+        _check_input_dtype("x", input_dtype, [mstype.float16, mstype.float32], self.cls_name)
         need_to_reflect = self.less(x, 0.5)
         neg_input = -x
         z = self.select(need_to_reflect, neg_input, x - 1)
@@ -612,8 +612,8 @@ class IGamma(Cell):
     def construct(self, a, x):
         a_dtype = self.dtype(a)
         x_dtype = self.dtype(x)
-        _check_input_dtype("input_a", a_dtype, [mstype.float32], self.cls_name)
-        _check_input_dtype("input_x", x_dtype, a_dtype, self.cls_name)
+        _check_input_dtype("a", a_dtype, [mstype.float32], self.cls_name)
+        _check_input_dtype("x", x_dtype, a_dtype, self.cls_name)
         domain_error = self.logicalor(self.less(x, 0), self.less(a, 0))
         use_igammac = self.logicaland(self.greater(x, 1), self.greater(x, a))
         ax = a * self.log(x) - x - self.lgamma(a)
@@ -688,8 +688,8 @@ class LBeta(Cell):
     def construct(self, x, y):
         x_dtype = self.dtype(x)
         y_dtype = self.dtype(y)
-        _check_input_dtype("input_x", x_dtype, [mstype.float16, mstype.float32], self.cls_name)
-        _check_input_dtype("input_y", y_dtype, x_dtype, self.cls_name)
+        _check_input_dtype("x", x_dtype, [mstype.float16, mstype.float32], self.cls_name)
+        _check_input_dtype("y", y_dtype, x_dtype, self.cls_name)
         x_plus_y = x + y
         para_shape = self.shape(x_plus_y)
         broadcastto = P.BroadcastTo(para_shape)