| View source on GitHub |
Decodes the output of a softmax.
tf.keras.backend.ctc_decode(
y_pred, input_length, greedy=True, beam_width=100, top_paths=1
)
Can use either greedy search (also known as best path) or a constrained dictionary search.
| Arguments | |
|---|---|
y_pred | tensor (samples, time_steps, num_categories) containing the prediction, or output of the softmax. |
input_length | tensor (samples, ) containing the sequence length for each batch item in y_pred. |
greedy | perform much faster best-path search if true. This does not use a dictionary. |
beam_width | if greedy is false: a beam search decoder will be used with a beam of this width. |
top_paths | if greedy is false, how many of the most probable paths will be returned. |
| Returns | |
|---|---|
Tuple | List: if greedy is true, returns a list of one element that contains the decoded sequence. If false, returns the top_paths most probable decoded sequences. Each decoded sequence has shape (samples, time_steps). Important: blank labels are returned as -1. Tensor (top_paths, ) that contains the log probability of each decoded sequence. |
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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/keras/backend/ctc_decode