class_docstr: _CollectionIOTensor
  
  `CollectionIOTensor` is different from `TableIOTensor` in that each
  component could have different shapes. While additional table-wide
  operations are planned to be supported for `TableIOTensor` so that
  the same operations could be applied to every column, there is no plan
  to support the same in `CollectionIOTensor`. In other words,
  `CollectionIOTensor` is only a dictionary with values consisting
  of `BaseIOTensor`.
class_docstr_tok: ["_CollectionIOTensor","`","CollectionIOTensor","`","is","different","from","`","TableIOTensor","`","in","that","each","component","could","have","different","shapes",".","While","additional","table-wide","operations","are","planned","to","be","supported","for","`","TableIOTensor","`","so","that","the","same","operations","could","be","applied","to","every","column",",","there","is","no","plan","to","support","the","same","in","`","CollectionIOTensor","`",".","In","other","words",",","`","CollectionIOTensor","`","is","only","a","dictionary","with","values","consisting","of","`","BaseIOTensor","`","."]
code: def __init__(self, spec, keys, values, internal=False):
      self._keys = keys
      self._values = values
      super().__init__(spec, internal=internal)
  
imports: import tensorflow
label_desc: Use image node_id 1 to create a new _CollectionIOTensor object from inherited base classes: _IOTensor with example: obj = _CollectionIOTensor(spec, keys, values, internal)