parameters: (name, shape=None, collections=None, dtype=dtypes.float32)
return_statement: return variables.Variable(
        initial_value=array_ops.zeros(shape, dtype=dtype),
        name=name,
        trainable=False,
        collections=collections)
docstring: Creates a new local variable.
  
    Args:
      name: The name of the new or existing variable.
      shape: Shape of the new or existing variable.
      collections: A list of collection names to which the Variable will be added.
      dtype: Data type of the variables.
  
    Returns:
      The created variable.
docstring_summary: Creates a new local variable.
docstring_tokens: Creates a new local variable .
function: def _create_local(name, shape=None, collections=None, dtype=dtypes.float32):
    """Creates a new local variable.
  
    Args:
      name: The name of the new or existing variable.
      shape: Shape of the new or existing variable.
      collections: A list of collection names to which the Variable will be added.
      dtype: Data type of the variables.
  
    Returns:
      The created variable.
    """
    # Make sure local variables are added to tf.GraphKeys.LOCAL_VARIABLES
    collections = list(collections or [])
    collections += [ops.GraphKeys.LOCAL_VARIABLES]
    return variables.Variable(
        initial_value=array_ops.zeros(shape, dtype=dtype),
        name=name,
        trainable=False,
        collections=collections)
function_tokens: def _create_local ( name , shape = None , collections = None , dtype = dtypes . float32 ) : # Make sure local variables are added to tf.GraphKeys.LOCAL_VARIABLES collections = list ( collections or [ ] ) collections += [ ops . GraphKeys . LOCAL_VARIABLES ] return variables . Variable ( initial_value = array_ops . zeros ( shape , dtype = dtype ) , name = name , trainable = False , collections = collections )