Can use either greedy search (also known as best path) or a constrained dictionary search.

k_ctc_decode(y_pred, input_length, greedy = TRUE, beam_width = 100L,
  top_paths = 1)



tensor (samples, time_steps, num_categories) containing the prediction, or output of the softmax.


tensor (samples, ) containing the sequence length for each batch item in y_pred.


perform much faster best-path search if TRUE. This does not use a dictionary.


if greedy is FALSE: a beam search decoder will be used with a beam of this width.


if greedy is FALSE, how many of the most probable paths will be returned.


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. Important: blank labels are returned as -1. Tensor (top_paths) that contains the log probability of each decoded sequence.

Keras Backend

This function is part of a set of Keras backend functions that enable lower level access to the core operations of the backend tensor engine (e.g. TensorFlow, CNTK, Theano, etc.).

You can see a list of all available backend functions here: