code: def chunk_and_pad(
      tensor: torch.Tensor, num_chunks: int
  ) -> List[torch.Tensor]:
      """Chunk a given Tensor into num_chunks parts and add any necessary padding."""
      chunks = list(torch.flatten(tensor).chunk(num_chunks))
      # torch.chunk may return fewer than num_chunks chunks, pad accordingly.
      num_pad_for_partial_chunk = chunks[0].numel() - chunks[-1].numel()
      if num_pad_for_partial_chunk > 0:
          chunks[-1] = F.pad(chunks[-1], [0, num_pad_for_partial_chunk])
      if len(chunks) < num_chunks:
          chunks.extend(
              [
                  torch.zeros_like(chunks[0])
                  for _ in range(num_chunks - len(chunks))
              ]
          )
      return chunks
  
file_path: colossalai/colossalai/legacy/zero/sharded_model/_utils.py
imports: from typing import Any, Callable, List, Tuple, Union
  import torch
  import torch.nn.functional
  from colossalai.legacy.zero.gemini.stateful_tensor import StatefulTensor
label_desc: Use image node_id 9 for calling a global function with example usage: chunk_and_pad(tensor, num_chunks) and returns: chunks