fix BatchNorm for fp16 (#36376) (#36691)

* fix BatchNorm for fp16

python/paddle/nn/layer/norm.py

@@ -564,32 +564,42 @@ def __init__(self,
         self._use_global_stats = use_global_stats
 
         if get_default_dtype() == 'float16':
-            set_default_dtype('float32')
+            self._dtype = 'float32'
+        else:
+            self._dtype = get_default_dtype()
 
         param_shape = [num_features]
 
         # create parameter
         if weight_attr == False:
             self.weight = self.create_parameter(
-                attr=None, shape=param_shape, default_initializer=Constant(1.0))
+                attr=None,
+                shape=param_shape,
+                dtype=self._dtype,
+                default_initializer=Constant(1.0))
             self.weight.stop_gradient = True
         else:
             self.weight = self.create_parameter(
                 attr=self._weight_attr,
                 shape=param_shape,
+                dtype=self._dtype,
                 default_initializer=Constant(1.0))
             self.weight.stop_gradient = self._weight_attr != None and self._weight_attr.learning_rate == 0.
 
         if bias_attr == False:
             self.bias = self.create_parameter(
                 attr=None,
                 shape=param_shape,
+                dtype=self._dtype,
                 default_initializer=Constant(0.0),
                 is_bias=True)
             self.bias.stop_gradient = True
         else:
             self.bias = self.create_parameter(
-                attr=self._bias_attr, shape=param_shape, is_bias=True)
+                attr=self._bias_attr,
+                shape=param_shape,
+                dtype=self._dtype,
+                is_bias=True)
             self.bias.stop_gradient = self._bias_attr != None and self._bias_attr.learning_rate == 0.
 
         moving_mean_name = None
@@ -600,6 +610,7 @@ def __init__(self,
             moving_variance_name = name + "_variance"
 
         self._mean = self.create_parameter(
+            dtype=self._dtype,
             attr=ParamAttr(
                 name=moving_mean_name,
                 initializer=Constant(0.0),
@@ -609,6 +620,7 @@ def __init__(self,
         self._mean.stop_gradient = True
 
         self._variance = self.create_parameter(
+            dtype=self._dtype,
             attr=ParamAttr(
                 name=moving_variance_name,
                 initializer=Constant(1.0),