add alias for fluid.initializer.set_global_initializer, alias is nn.initializer.set_global_initializer (#28690)

python/paddle/fluid/initializer.py

@@ -955,7 +955,7 @@ def set_global_initializer(weight_init, bias_init=None):
     After this API is invoked, the global initializer will takes effect in subsequent code.
 
     The model parameters include ``weight`` and ``bias`` . In the framework, they correspond 
-    to ``fluid.Parameter`` , which is inherited from ``fluid.Variable`` , and is a persistable Variable.
+    to ``paddle.ParamAttr`` , which is inherited from ``paddle.Tensor`` , and is a persistable Variable.
     This API only takes effect for model parameters, not for variables created through apis such as 
     :ref:`api_fluid_layers_create_global_var` , :ref:`api_fluid_layers_create_tensor`.
     
@@ -974,27 +974,30 @@ def set_global_initializer(weight_init, bias_init=None):
 
     Examples:
         .. code-block:: python
-            import paddle.fluid as fluid
 
-            fluid.set_global_initializer(fluid.initializer.Uniform(), fluid.initializer.Constant())
-            x = fluid.data(name="x", shape=[1, 3, 32, 32])
+            import paddle
+            import paddle.nn as nn
+
+            nn.initializer.set_global_initializer(nn.initializer.Uniform(), nn.initializer.Constant())
+            x_var = paddle.uniform((2, 4, 8, 8), dtype='float32', min=-1., max=1.)
 
             # The weight of conv1 is initialized by Uniform
             # The bias of conv1 is initialized by Constant
-            conv1 = fluid.layers.conv2d(x, 5, 3)
+            conv1 = nn.Conv2D(4, 6, (3, 3))
+            y_var1 = conv1(x_var)
 
             # If set param_attr/bias_attr too, global initializer will not take effect
             # The weight of conv2 is initialized by Xavier
             # The bias of conv2 is initialized by Normal
-            conv2 = fluid.layers.conv2d(conv1, 5, 3, 
-                param_attr=fluid.initializer.Xavier(), 
-                bias_attr=fluid.initializer.Normal())
+            conv2 = nn.Conv2D(4, 6, (3, 3), 
+                weight_attr=nn.initializer.XavierUniform(),
+                bias_attr=nn.initializer.Normal())
+            y_var2 = conv2(x_var)
 
             # Cancel the global initializer in framework, it will takes effect in subsequent code
-            fluid.set_global_initializer(None)
-
-
+            nn.initializer.set_global_initializer(None)
     """
+
     check_type(weight_init, 'weight_init', (Initializer, type(None)),
                'set_global_initializer')
     global _global_weight_initializer_

python/paddle/nn/initializer/__init__.py

@@ -14,6 +14,7 @@
 
 # TODO: define the initializers to create a Parameter in neural network
 from ...fluid.initializer import Bilinear  #DEFINE_ALIAS
+from ...fluid.initializer import set_global_initializer  #DEFINE_ALIAS
 
 from . import constant
 from .constant import Constant  #DEFINE_ALIAS
@@ -22,7 +23,7 @@ from . import kaiming
 from .kaiming import KaimingNormal  #DEFINE_ALIAS
 from .kaiming import KaimingUniform  #DEFINE_ALIAS
 
-__all__ = ['Bilinear', ]
+__all__ = ['Bilinear', 'set_global_initializer']
 
 __all__ += constant.__all__
 __all__ += kaiming.__all__