class_docstr: Represent a single graph with additional attributes.
class_docstr_tok: ["Represent","a","single","graph","with","additional","attributes","."]
docstr: Set node features in batch view.
  
  Parameters
  ----------
  key : str
      The name of the feature.
  value : torch.Tensor
      The values to be written, in the shape of (B, N, D)
code: def _set_batch_node_features(self, key: str, value: torch.Tensor):
      """
      Set node features in batch view.
  
      Parameters
      ----------
      key : str
          The name of the feature.
      value : torch.Tensor
          The values to be written, in the shape of (B, N, D)
      """
      individual_features = [
          value[i, : self._batch_num_nodes[i]]
          for i in range(len(self._batch_num_nodes))
      ]
      self.set_node_features(
          slice(None, None, None), {key: torch.cat(individual_features)}
      )
  
imports: import os
  import warnings
  from collections import namedtuple
  from typing import Any, Callable, Dict, List, Tuple, Union
  import dgl
  import scipy.sparse
  import torch
  from torch.nn.utils.rnn import pad_sequence
  from .utils import EdgeNotFoundException, SizeMismatchException, check_and_expand, entail_zero_padding, int_to_list, slice_to_list
  from .views import BatchEdgeFeatView, BatchNodeFeatView, EdgeView, NodeFeatView, NodeView
label_desc: Use image node_id 34 for calling the GraphData obj's underlying member method code with example usage: obj._set_batch_node_features(key, value) without return types