docstr: Return the Tensor containing all block IDs for this sequence in the specified cache group.
  
  Arguments:
      cache_group (int): The cache group to query.
docstr_tok: ["Return","the","Tensor","containing","all","block","IDs","for","this","sequence","in","the","specified","cache","group",".","Arguments",":","cache_group","(","int",")",":","The","cache","group","to","query","."]
code: def all_block_ids(self, cache_group: int = 0) -> torch.Tensor:
      """
      Return the Tensor containing all block IDs for this sequence in the specified cache group.
  
      Arguments:
          cache_group (int): The cache group to query.
      """
      block_ids = []
      for allocation_group, num_blocks in zip(
          self._kv_cache_ids[cache_group],
          self._blocks_per_allocation_group[cache_group],
      ):
          block_ids.append(allocation_group[:num_blocks])
      return torch.cat(block_ids)
  
imports: from typing import List, Tuple, Union
  import torch
label_desc: Use image node_id 9 for calling the DSSequenceDescriptor obj's underlying member method code with example usage: obj.all_block_ids(cache_group) and returns: torch