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Returns a flat list from a given nested structure.
tf.nest.flatten( structure, expand_composites=False )
If nest is not a structure , tuple (or a namedtuple), dict, or an attrs class, then returns a single-element list: [nest].
In the case of dict instances, the sequence consists of the values, sorted by key to ensure deterministic behavior. 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 pack_sequence_as. This correctly repacks dicts and OrderedDicts 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.
Users must not modify any collections used in nest while this function is running.
dict = { "key3": "value3", "key1": "value1", "key2": "value2" } tf.nest.flatten(dict) ['value1', 'value2', 'value3']
tuple = ((1.0, 2.0), (3.0, 4.0, 5.0), (6.0)) tf.nest.flatten(tuple) [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]
array = np.array([[1, 2], [3, 4]]) tf.nest.flatten(array) [array([[1, 2], [3, 4]])]
tf.Tensor
(will not flatten):tensor = tf.constant([[1., 2., 3.], [4., 5., 6.], [7., 8., 9.]]) tf.nest.flatten(tensor) [<tf.Tensor: shape=(3, 3), dtype=float32, numpy= array([[1., 2., 3.], [4., 5., 6.], [7., 8., 9.]], dtype=float32)>]
Args | |
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structure | an arbitrarily nested structure. Note, numpy arrays are considered atoms and are not flattened. |
expand_composites | If true, then composite tensors such as tf.sparse.SparseTensor and tf.RaggedTensor are expanded into their component tensors. |
Returns | |
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A Python list, the flattened version of the input. |
Raises | |
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TypeError | The nest is or contains a dict with non-sortable keys. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/nest/flatten