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: Synchronously obtains a :class:`tensor` from the
  :class:`FeatureStore`.
  
  Args:
      *args: Arguments passed to :class:`TensorAttr`.
      convert_type (bool, optional): Whether to convert the type of the
          output tensor to the type of the attribute index.
          (default: :obj:`False`)
      **kwargs: Keyword arguments passed to :class:`TensorAttr`.
  
  Raises:
      ValueError: If the input :class:`TensorAttr` is not fully
          specified.
      KeyError: If the tensor corresponding to the input
          :class:`TensorAttr` was not found.
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code: def get_tensor(
      self,
      *args,
      convert_type: bool = False,
      **kwargs,
  ) -> FeatureTensorType:
      r"""Synchronously obtains a :class:`tensor` from the
      :class:`FeatureStore`.
  
      Args:
          *args: Arguments passed to :class:`TensorAttr`.
          convert_type (bool, optional): Whether to convert the type of the
              output tensor to the type of the attribute index.
              (default: :obj:`False`)
          **kwargs: Keyword arguments passed to :class:`TensorAttr`.
  
      Raises:
          ValueError: If the input :class:`TensorAttr` is not fully
              specified.
          KeyError: If the tensor corresponding to the input
              :class:`TensorAttr` was not found.
      """
      attr = self._tensor_attr_cls.cast(*args, **kwargs)
      if not attr.is_fully_specified():
          raise ValueError(
              f"The input TensorAttr '{attr}' is not fully "
              f"specified. Please fully-specify the input by "
              f"specifying all 'UNSET' fields."
          )
  
      tensor = self._get_tensor(attr)
      if tensor is None:
          raise KeyError(
              f"A tensor corresponding to '{attr}' was not found"
          )
      return self._to_type(attr, tensor) if convert_type else tensor
  
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 5 for calling the FeatureStore obj's underlying member method code with example usage: obj.get_tensor() and returns: unknown