framework.py enhancement (#8471)

* framework.py enhancement

* polish

* clean up

* enforce the inputs of Operator __init__ of type Variable

* python2 assert

* reverse assert

python/paddle/v2/fluid/framework.py

@@ -152,7 +152,7 @@ class Variable(object):
         shape(tuple|list|None): The shape of variable. -1 means the batch size.
             Some kinds of variable do not contain shape, just set it to None.
         dtype(np.dtype|core.VarDesc.VarType|str): The data type of variable.
-        lod_level(int): The level of lod tensor. 0 means there is not a time
+        lod_level(int): The level of lod tensor. 0 means it is not a time
             series data.
         persistable(bool): True if the variable should be saved as check point.
             Defaults to False.
@@ -346,7 +346,7 @@ class OpProtoHolder(object):
     def __init__(self):
         assert not hasattr(
             self.__class__,
-            '_instance'), 'Please use `instance()` to get OpProtoHolder opject!'
+            '_instance'), 'Please use `instance()` to get OpProtoHolder object!'
         op_protos = get_all_op_protos()
         self.op_proto_map = {}
         for proto in op_protos:
@@ -368,8 +368,8 @@ class OpProtoHolder(object):
 
 class Operator(object):
     """
-    Python Operator class. The operator represents the build in instructs in a
-    Block. Users can use the build in instructs to describe their neural
+    Python Operator class. The operator represents the build in instructions in a
+    Block. Users can use the build in instructions to describe their neural
     network.
     """
 
@@ -478,7 +478,7 @@ class Operator(object):
                 raise TypeError("'attrs' should be a dict.")
             for attr in proto.attrs:
                 attr_name = attr.name
-                if (not attr_name in attrs) or (attrs[attr_name] is None):
+                if (attr_name not in attrs) or (attrs[attr_name] is None):
                     continue
                 if isinstance(attrs[attr_name], Block):
                     self.desc.set_block_attr(attr_name, attrs[attr_name].desc)
@@ -751,7 +751,7 @@ class Block(object):
                 if isinstance(item[1], Parameter))
 
     def create_var(self, *args, **kwargs):
-        var = Variable(self, *args, **kwargs)
+        var = Variable(block=self, *args, **kwargs)
         if 'initializer' in kwargs:
             kwargs['initializer'](var, self)
         return var
@@ -822,13 +822,13 @@ class Block(object):
 
     def append_op(self, *args, **kwargs):
         op_desc = self.desc.append_op()
-        op = Operator(self, op_desc, *args, **kwargs)
+        op = Operator(block=self, desc=op_desc, *args, **kwargs)
         self.ops.append(op)
         return op
 
     def delete_ops(self, ops):
         # remove from cpp
-        # FIXME(typhoonzero): remove only the first occuracy.
+        # FIXME(typhoonzero): remove only the first occurrence.
         try:
             start = list(self.ops).index(ops[0])
             end = list(self.ops).index(ops[-1])
@@ -846,6 +846,11 @@ class Block(object):
         return op
 
     def sync_with_cpp(self):
+        """
+        Sync with the desc on the c++ end.
+
+        This method is used to synchronize the c++ desc instance generated by backward.
+        """
         # sync variables from cpp
         for var in self.desc.all_vars():
             if not self.has_var(var.name()):
@@ -891,9 +896,9 @@ class Block(object):
 
     def copy_param_info_from(self, other):
         """
-        Copy the information of parameters from other block
+        Copy the information of parameters from the other block
         Args:
-            other(Block): other block
+            other(Block): the other block
 
         Returns:
             None
@@ -1239,6 +1244,6 @@ def get_var(name, program=None):
     if program is None:
         program = default_main_program()
     assert isinstance(name, str)
-    assert isinstance(name, Program)
+    assert isinstance(program, Program)
 
     return program.global_block().var(name)

python/paddle/v2/fluid/layers/nn.py

@@ -104,7 +104,7 @@ def fc(input,
     * :math:`X_i`: The input tensor.
     * :math:`W`: The weights created by this layer.
     * :math:`b`: The bias parameter created by this layer (if needed).
-    * :math:`Act`: The activation funtion.
+    * :math:`Act`: The activation function.
     * :math:`Out`: The output tensor.
 
     Args: