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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 | |
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`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 | |
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`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