class_docstr: A manager class to manipulate the tensors in chunks.
  
  Args:
      chunk_configuration (Dict[int, Dict]): the configuration dictionary of this chunk manager.
      init_device (torch.device): optional, the device on which the chunk is initialized. The default is None.
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code: def init_grad_chunk(self, chunk: Chunk) -> Chunk:
      if chunk.grad_chunk is not None:
          self.__sub_memory_usage(chunk.grad_chunk.memory_usage)
      grad_chunk = chunk.init_grad_chunk()
      self.__add_memory_usage(grad_chunk.memory_usage)
      if grad_chunk not in self.accessed_chunks:
          self.accessed_chunks.add(grad_chunk)
          self.accessed_mem += grad_chunk.chunk_mem
      return grad_chunk
  
imports: from collections import deque
  from typing import Deque, Dict, Iterable, List, Optional, Set, Tuple
  import torch
  import torch.distributed
  from torch.distributed import ProcessGroup
  from colossalai.utils import free_storage, get_current_device
  from .chunk import Chunk, ChunkFullError, TensorState
label_desc: Use image node_id 22 for calling the ChunkManager obj's underlying member method code with example usage: obj.init_grad_chunk(chunk) and returns: grad_chunk