class_docstr: An abstract base class to access features from a remote feature store.
  
  Args:
      tensor_attr_cls (TensorAttr, optional): A user-defined
          :class:`TensorAttr` class to customize the required attributes and
          their ordering to unique identify tensor values.
          (default: :obj:`None`)
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docstr: Returns a view of the :class:`FeatureStore` given a not yet
  fully-specified :class:`TensorAttr`.
docstr_tok: ["Returns","a","view","of","the",":","class",":","`","FeatureStore","`","given","a","not","yet","fully-specified",":","class",":","`","TensorAttr","`","."]
code: def view(self, *args, **kwargs) -> AttrView:
      r"""Returns a view of the :class:`FeatureStore` given a not yet
      fully-specified :class:`TensorAttr`.
      """
      attr = self._tensor_attr_cls.cast(*args, **kwargs)
      return AttrView(self, 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 14 for calling the FeatureStore obj's underlying member method code with example usage: obj.view() and returns: AttrView