class_docstr: Defines a view of a :class:`FeatureStore` that is obtained from a
  specification of attributes on the feature store. The view stores a
  reference to the backing feature store as well as a :class:`TensorAttr`
  object that represents the view's state.
  
  Users can create views either using the :class:`AttrView` constructor,
  :meth:`FeatureStore.view`, or by incompletely indexing a feature store.
  For example, the following calls all create views:
  
  .. code-block:: python
  
      store[group_name]
      store[group_name].feat
      store[group_name, feat]
  
  While the following calls all materialize those views and produce tensors
  by either calling the view or fully-specifying the view:
  
  .. code-block:: python
  
      store[group_name]()
      store[group_name].feat[index]
      store[group_name, feat][index]
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docstr: Supports :class:`AttrView` as a callable to force retrieval from
  the currently specified attributes.
  
  In particular, this passes the current :class:`TensorAttr` object to a
  GET call, regardless of whether all attributes have been specified.
  It returns the result of this call.
  In particular, the following operation returns a tensor by performing a
  GET operation on the backing feature store:
  
  .. code-block:: python
  
      store[group_name, attr_name]()
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code: def __call__(self) -> FeatureTensorType:
      r"""Supports :class:`AttrView` as a callable to force retrieval from
      the currently specified attributes.
  
      In particular, this passes the current :class:`TensorAttr` object to a
      GET call, regardless of whether all attributes have been specified.
      It returns the result of this call.
      In particular, the following operation returns a tensor by performing a
      GET operation on the backing feature store:
  
      .. code-block:: python
  
          store[group_name, attr_name]()
      """
      # Set all UNSET values to None:
      out = copy.copy(self)
      out._attr.fully_specify()
      return out._store.get_tensor(out._attr)
  
imports: import copy
  from abc import abstractmethod
  from dataclasses import dataclass
  from enum import Enum
  from typing import Any, List, Optional, Tuple, Union
  import numpy
  import torch
  from torch_geometric.typing import FeatureTensorType, NodeType
  from torch_geometric.utils.mixin import CastMixin
label_desc: Use image node_id 6 for calling the AttrView obj's underlying member method code with example usage: obj.__call__() and returns: out