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Creates a new structure by applying func to each atom in structure.
tf.nest.map_structure(
func, *structure, **kwargs
)
Refer to tf.nest for the definition of a structure.
Applies func(x[0], x[1], ...) where x[i] enumerates all atoms in
structure[i]. All items in structure must have the same arity,
and the return value will contain results with the same structure layout.
Examples:
- A single Python dict:
a = {"hello": 24, "world": 76}tf.nest.map_structure(lambda p: p * 2, a){'hello': 48, 'world': 152}
- 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}
- A single Python list:
a = [24, 76, "ab"]tf.nest.map_structure(lambda p: p * 2, a)[48, 152, 'abab']
- Scalars:
tf.nest.map_structure(lambda x, y: x + y, 3, 4)7
- Empty structures:
tf.nest.map_structure(lambda x: x + 1, ())()
- Check the types of iterables:
s1 = (((1, 2), 3), 4, (5, 6))s1_list = [[[1, 2], 3], 4, [5, 6]]tf.nest.map_structure(lambda x, y: None, s1, s1_list)Traceback (most recent call last):TypeError: The two structures don't have the same nested structure
- Type check is set to False:
s1 = (((1, 2), 3), 4, (5, 6))s1_list = [[[1, 2], 3], 4, [5, 6]]tf.nest.map_structure(lambda x, y: None, s1, s1_list, check_types=False)(((None, None), None), None, (None, None))
Args | |
|---|---|
func
|
A callable that accepts as many arguments as there are structures. |
*structure
|
atom or nested structure. |
**kwargs
|
Valid keyword args are:
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Returns | |
|---|---|
A new structure with the same arity as structure[0], whose atoms
correspond to func(x[0], x[1], ...) where x[i] is the atom in the
corresponding location in structure[i]. If there are different structure
types and check_types is False the structure types of the first
structure will be used.
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View source on GitHub