tf.nest.map_structure
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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.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2021-02-18 UTC.
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