code: def memory_snapshot():
      r"""Return a snapshot of the CUDA memory allocator state across all devices.
  
      Interpreting the output of this function requires familiarity with the
      memory allocator internals.
  
      .. note::
          See :ref:`cuda-memory-management` for more details about GPU memory
          management.
      """
      return torch._C._cuda_memorySnapshot()["segments"]
  
imports: import collections
  import contextlib
  import ctypes
  import pickle
  import sys
  import warnings
  from inspect import signature
  from typing import Any, Dict, Optional, Tuple, Union
  import torch
  from torch import _C
  from torch.types import Device
  from .None import _get_device_index, _get_nvml_device_index, _lazy_init, is_initialized
  from ._memory_viz import memory, segments
  from ._utils import _dummy_type
label_desc: Use image node_id 19 for calling a global function with example usage: memory_snapshot() and returns: torch