fix initalization and regularization docs (#23492)

python/paddle/fluid/initializer.py

@@ -133,14 +133,16 @@ class ConstantInitializer(Initializer):
 
     Args:
         value (float32): constant value to initialize the variable 
+        force_cpu (bool): place for initialization, if set true, initialization will
+            be forced on CPU even if executor is set on CUDA. default false.
 
     Examples:
         .. code-block:: python
 
     	    import paddle.fluid as fluid
-            x = fluid.data(name="data", shape=[8, 32, 32], dtype="float32")
+            x = fluid.data(name="data", shape=[32, 32], dtype="float32")
 	    fc = fluid.layers.fc(input=x, size=10,
-    		param_attr=fluid.initializer.Constant(value=2.0))
+    		param_attr=fluid.initializer.ConstantInitializer(value=2.0))
 
     """
 
@@ -744,6 +746,7 @@ class BilinearInitializer(Initializer):
         .. code-block:: python
 
             import paddle.fluid as fluid
+            import math
             factor = 2
             C = 2
             B = 8

python/paddle/fluid/regularizer.py

@@ -134,8 +134,8 @@ class L2DecayRegularizer(WeightDecayRegularizer):
             main_prog = fluid.Program()
             startup_prog = fluid.Program()
             with fluid.program_guard(main_prog, startup_prog):
-                data = fluid.layers.data(name='image', shape=[3, 28, 28], dtype='float32')
-                label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+                data = fluid.data(name='image', shape=[256, 3, 28, 28], dtype='float32')
+                label = fluid.data(name='label', shape=[256, 1], dtype='int64')
                 hidden = fluid.layers.fc(input=data, size=128, act='relu')
                 prediction = fluid.layers.fc(input=hidden, size=10, act='softmax')
                 loss = fluid.layers.cross_entropy(input=prediction, label=label)
@@ -213,8 +213,8 @@ class L1DecayRegularizer(WeightDecayRegularizer):
             main_prog = fluid.Program()
             startup_prog = fluid.Program()
             with fluid.program_guard(main_prog, startup_prog):
-                data = fluid.layers.data(name='image', shape=[3, 28, 28], dtype='float32')
-                label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+                data = fluid.data(name='image', shape=[256, 3, 28, 28], dtype='float32')
+                label = fluid.data(name='label', shape=[256, 1], dtype='int64')
                 hidden = fluid.layers.fc(input=data, size=128, act='relu')
                 prediction = fluid.layers.fc(input=hidden, size=10, act='softmax')
                 loss = fluid.layers.cross_entropy(input=prediction, label=label)