Returns a given flattened sequence packed into a given structure.
tf.nest.pack_sequence_as(
structure, flat_sequence, expand_composites=False
)
If structure
is a scalar, flat_sequence
must be a single-element list;
in this case the return value is flat_sequence[0]
.
If structure
is or contains a dict instance, the keys will be sorted to
pack the flat sequence in deterministic order. This is true also for
OrderedDict
instances: their sequence order is ignored, the sorting order of
keys is used instead. The same convention is followed in flatten
.
This correctly repacks dicts and OrderedDict
s after they have been
flattened, and also allows flattening an OrderedDict
and then repacking it
back using a corresponding plain dict, or vice-versa.
Dictionaries with non-sortable keys cannot be flattened.
Args |
structure
|
Nested structure, whose structure is given by nested lists,
tuples, and dicts. Note: numpy arrays and strings are considered
scalars.
|
flat_sequence
|
flat sequence to pack.
|
expand_composites
|
If true, then composite tensors such as tf.SparseTensor
and tf.RaggedTensor are expanded into their component tensors.
|
Returns |
packed
|
flat_sequence converted to have the same recursive structure as
structure .
|
Raises |
ValueError
|
If flat_sequence and structure have different
element counts.
|
TypeError
|
structure is or contains a dict with non-sortable keys.
|