TensorFlow

API

 tf.nest / flatten


Applies func to each entry in structure and returns a new structure.

Used in the notebooks

Used in the guide Used in the tutorials

Applies func(x[0], x[1], ...) where x[i] is an entry in structure[i]. All structures in structure must have the same arity, and the return value will contain results with the same structure layout.

Examples:

  1. A single Python dict:
a = {"hello": 24, "world": 76}
tf.nest.map_structure(lambda p: p * 2, a)
{'hello': 48, 'world': 152}
  1. Multiple Python dictionaries:
d1 = {"hello": 24, "world": 76}
d2 = {"hello": 36, "world": 14}
tf.nest.map_structure(lambda p1, p2: p1 + p2, d1, d2)
{'hello': 60, 'world': 90}

func A callable that accepts as many arguments as there are structures.
*structure scalar, or tuple or dict or list of constructed scalars and/or other tuples/lists, or scalars. Note: numpy arrays are considered as scalars.
**kwargs Valid keyword args are:
  • check_types: If set to True (default) the types of iterables within the structures have to be same (e.g. map_structure(func, [1], (1,)) raises a TypeError exception). To allow this set this argument to False. Note that namedtuples with identical name and fields are always considered to have the same shallow structure.
  • expand_composites: If set to True, then composite tensors such as tf.sparse.SparseTensor and tf.RaggedTensor are expanded into their component tensors. If False (the default), then composite tensors are not expanded.

A new structure with the same arity as structure, whose values correspond to func(x[0], x[1], ...) where x[i] is a value in the corresponding location in structure[i]. If there are different sequence types and check_types is False the sequence types of the first structure will be used.

TypeError If func is not callable or if the structures do not match each other by depth tree.
ValueError If no structure is provided or if the structures do not match each other by type.
ValueError If wrong keyword arguments are provided.

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