Applies func
to each entry in structure
and returns a new structure.
tf.nest.map_structure(
func, *structure, **kwargs
)
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:
- 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}
Args |
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.
|
Returns |
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.
|
Raises |
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.
|