class_docstr: A transform which maps image data from tuple to dict.
  
  This transform has a list of keys (key1, key2, ...),
  takes a sample of the form (data1, data2, ...) and
  returns a sample of the form {key1: data1, key2: data2, ...}
  If duplicate keys are used, the corresponding values are merged into a list.
  
  It is useful for mapping output from datasets like the `PyTorch
  ImageFolder <https://github.com/pytorch/vision/blob/master/torchvision/
  datasets/folder.py#L177>`_ dataset (tuple) to dict with named data fields.
  
  If sample is already a dict with the required keys, pass sample through.
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docstr: The constructor method of TupleToMapTransform class.
  
  Args:
      list_of_map_keys: a list of dict keys that in order will be mapped
          to items in the input data sample list
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code: def __init__(self, list_of_map_keys: List[str]):
      """The constructor method of TupleToMapTransform class.
  
      Args:
          list_of_map_keys: a list of dict keys that in order will be mapped
              to items in the input data sample list
  
      """
      self._map_keys = list_of_map_keys
  
imports: import collections
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import torchvision.transforms
  from .None import build_transforms, ClassyTransform, register_transform
label_desc: Use image node_id 1 to create a new TupleToMapTransform object from inherited base classes: ClassyTransform with example: obj = TupleToMapTransform(list_of_map_keys)