class_docstr: Summary class for a single layer in a :class:`~lightning.pytorch.core.LightningModule`. It collects the
  following information:
  
  - Type of the layer (e.g. Linear, BatchNorm1d, ...)
  - Input shape
  - Output shape
  - Number of parameters
  
  The input and output shapes are only known after the example input array was
  passed through the model.
  
  Example::
  
      >>> model = torch.nn.Conv2d(3, 8, 3)
      >>> summary = LayerSummary(model)
      >>> summary.num_parameters
      224
      >>> summary.layer_type
      'Conv2d'
      >>> output = model(torch.rand(1, 3, 5, 5))
      >>> summary.in_size
      [1, 3, 5, 5]
      >>> summary.out_size
      [1, 8, 3, 3]
  
  Args:
      module: A module to summarize
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code: def in_size(self) -> Union[str, List]:
      return self._in_size or UNKNOWN_SIZE
  
imports: import contextlib
  import logging
  import math
  from collections import OrderedDict
  from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn
  from torch import Tensor
  from torch.utils.hooks import RemovableHandle
  import lightning.pytorch
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.pytorch.utilities.model_helpers import _ModuleMode
  from lightning.pytorch.utilities.rank_zero import WarningCache
label_desc: Use image node_id 5 for calling the LayerSummary obj's underlying member method code with example usage: obj.in_size() and returns: unknown