Modify the supported dtype of IGamma to align with TensorFlow

mindspore/nn/layer/math.py

@@ -428,7 +428,7 @@ class DiGamma(Cell):
                            nan, real_result)
 
 
-eps_fp16 = Tensor(np.finfo(np.float16).eps, mstype.float16)
+eps_fp64 = Tensor(np.finfo(np.float64).eps, mstype.float64)
 eps_fp32 = Tensor(np.finfo(np.float32).eps, mstype.float32)
 
 def _while_helper_func(cond, body, vals):
@@ -447,8 +447,8 @@ def _IgammaSeries(ax, x, a, enabled):
     dtype = P.DType()
     select = P.Select()
 
-    if dtype(ax) == mstype.float16:
-        epsilon = eps_fp16
+    if dtype(ax) == mstype.float64:
+        epsilon = eps_fp64
     else:
         epsilon = eps_fp32
 
@@ -499,8 +499,8 @@ def _IgammacContinuedFraction(ax, x, a, enabled):
     dtype = P.DType()
     select = P.Select()
 
-    if dtype(ax) == mstype.float16:
-        epsilon = eps_fp16
+    if dtype(ax) == mstype.float64:
+        epsilon = eps_fp64
     else:
         epsilon = eps_fp32
 
@@ -619,9 +619,9 @@ class IGamma(Cell):
         ``Ascend``
 
     Inputs:
-        - **a** (Tensor) - The input tensor. With float16 or float32 data type. `a` should have
+        - **a** (Tensor) - The input tensor. With float32 or float64 data type. `a` should have
           the same dtype with `x`.
-        - **x** (Tensor) - The input tensor. With float16 or float32 data type. `x` should have
+        - **x** (Tensor) - The input tensor. With float32 or float64 data type. `x` should have
           the same dtype with `a`.
 
     Outputs:
@@ -639,7 +639,7 @@ class IGamma(Cell):
     def __init__(self):
         super(IGamma, self).__init__()
         # const numbers
-        self.log_maxfloat16 = Tensor(np.log(np.finfo(np.float16).max), mstype.float16)
+        self.log_maxfloat64 = Tensor(np.log(np.finfo(np.float64).max), mstype.float64)
         self.log_maxfloat32 = Tensor(np.log(np.finfo(np.float32).max), mstype.float32)
 
         # operations
@@ -664,7 +664,7 @@ 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.float16, mstype.float32], self.cls_name)
+        _check_input_dtype("input_a", a_dtype, [mstype.float32, mstype.float64], self.cls_name)
         _check_input_dtype("input_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))
@@ -673,8 +673,8 @@ class IGamma(Cell):
         a = boradcastto(a)
         x = boradcastto(x)
         x_is_zero = self.equal(x, 0)
-        if a_dtype == mstype.float16:
-            log_maxfloat = self.log_maxfloat16
+        if a_dtype == mstype.float64:
+            log_maxfloat = self.log_maxfloat64
         else:
             log_maxfloat = self.log_maxfloat32
         underflow = self.less(ax, self.neg(log_maxfloat))