code: def split_tensor_along_last_dim(
      tensor: torch.Tensor,
      num_partitions: int,
      contiguous_split_chunks: bool = False,
  ) -> List[torch.Tensor]:
      """Split a tensor along its last dimension.
      Arguments:
          tensor: input tensor.
          num_partitions: number of partitions to split the tensor
          contiguous_split_chunks: If True, make each chunk contiguous
                                   in memory.
      """
      # Get the size and dimension.
      last_dim = tensor.dim() - 1
      last_dim_size = divide(tensor.size()[last_dim], num_partitions)
      # Split.
      tensor_list = torch.split(tensor, last_dim_size, dim=last_dim)
      # Note: torch.split does not create contiguous tensors by default.
      if contiguous_split_chunks:
          return tuple(chunk.contiguous() for chunk in tensor_list)
  
      return tensor_list
  
imports: from typing import List, Sequence
  import torch
  from apex.transformer.utils import divide
label_desc: Use image node_id 1 for calling a global function with example usage: split_tensor_along_last_dim(tensor, num_partitions, contiguous_split_chunks) and returns: tensor_list, tuple