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
)
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.
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.
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: https://tensorflow.rstudio.com/reference/keras/index.html#backend.