class_docstr: An abstraction representing a microbatch in the pipeline.
class_docstr_tok: ["An","abstraction","representing","a","microbatch","in","the","pipeline","."]
code: def __init__(self, values: Union[List[Any], Tensor]) -> None:
      self._values = values
      self.atomic = torch.is_tensor(values)
  
      # Verify at least on tensor
      if not self.atomic:
          if not any(torch.is_tensor(value) for value in self._values):
              raise TypeError(
                  f"No tensors found in batch: {self._values}"
              )
  
imports: import typing
  from typing import Any, Callable, List, Union, cast, Sequence
  import torch
  from torch import Tensor
  import torch.cuda.comm
label_desc: Use image node_id 1 to create a new Batch object  with example: obj = Batch(values)