parameters: (name,
                      shape,
                      dtype,
                      initializer=None,
                      partition_info=None,
                      **kwargs)
docstring: A pared-down version of get_variable which does not reuse variables.
docstring_summary: A pared-down version of get_variable which does not reuse variables.
docstring_tokens: A pared - down version of get_variable which does not reuse variables .
function: def _default_getter(name,
                      shape,
                      dtype,
                      initializer=None,
                      partition_info=None,
                      **kwargs):
    """A pared-down version of get_variable which does not reuse variables."""
    dtype = dtypes.as_dtype(dtype)
    shape_object = tensor_shape.as_shape(shape)
    with ops.init_scope():
      if initializer is None:
        initializer, initializing_from_value = (
            variable_scope._get_default_variable_store()._get_default_initializer(  # pylint: disable=protected-access
                name=name,
                shape=shape_object,
                dtype=dtype))
      else:
        initializing_from_value = not callable(initializer)
      # Same logic as get_variable
      variable_dtype = dtype.base_dtype
      if initializing_from_value:
        if shape is not None:
          raise ValueError("If initializer is a constant, do not specify shape.")
        initial_value = initializer
      else:
        # Instantiate initializer if provided initializer is a type object.
        if isinstance(initializer, type(init_ops.Initializer)):
          initializer = initializer(dtype=dtype)
        shape_list = None if shape is None else shape_object.as_list()
        if "partition_info" in tf_inspect.getargspec(initializer).args:
          initial_value = functools.partial(initializer,
                                            shape_list,
                                            dtype=dtype,
                                            partition_info=partition_info)
        else:
          initial_value = functools.partial(initializer,
                                            shape_list,
                                            dtype=dtype)
  
      return variables.VariableV1(
          initial_value=initial_value,
          name=name,
          dtype=variable_dtype,
          use_resource=True,
          **kwargs)
function_tokens: def _default_getter ( name , shape , dtype , initializer = None , partition_info = None , * * kwargs ) : dtype = dtypes . as_dtype ( dtype ) shape_object = tensor_shape . as_shape ( shape ) with ops . init_scope ( ) : if initializer is None : initializer , initializing_from_value = ( variable_scope . _get_default_variable_store ( ) . _get_default_initializer ( # pylint: disable=protected-access name = name , shape = shape_object , dtype = dtype ) ) else : initializing_from_value = not callable ( initializer ) # Same logic as get_variable variable_dtype = dtype . base_dtype if initializing_from_value : if shape is not None : raise ValueError ( "If initializer is a constant, do not specify shape." ) initial_value = initializer else : # Instantiate initializer if provided initializer is a type object. if isinstance ( initializer , type ( init_ops . Initializer ) ) : initializer = initializer ( dtype = dtype ) shape_list = None if shape is None else shape_object . as_list ( ) if "partition_info" in tf_inspect . getargspec ( initializer ) . args : initial_value = functools . partial ( initializer , shape_list , dtype = dtype , partition_info = partition_info ) else : initial_value = functools . partial ( initializer , shape_list , dtype = dtype ) return variables . VariableV1 ( initial_value = initial_value , name = name , dtype = variable_dtype , use_resource = True , * * kwargs )