tf.nn.ctc_beam_search_decoder_v2(
inputs,
sequence_length,
beam_width=100,
top_paths=1
)
Defined in tensorflow/python/ops/ctc_ops.py
.
Performs beam search decoding on the logits given in input.
Note The ctc_greedy_decoder
is a special case of the
ctc_beam_search_decoder
with top_paths=1
and beam_width=1
(but
that decoder is faster for this special case).
Args:
inputs
: 3-Dfloat
Tensor
, size[max_time, batch_size, num_classes]
. The logits.sequence_length
: 1-Dint32
vector containing sequence lengths, having size[batch_size]
.beam_width
: An int scalar >= 0 (beam search beam width).top_paths
: An int scalar >= 0, <= beam_width (controls output size).
Returns:
A tuple (decoded, log_probabilities)
where
decoded
: A list of length top_paths, wheredecoded[j]
is aSparseTensor
containing the decoded outputs:decoded[j].indices
: Indices matrix[total_decoded_outputs[j], 2]
; The rows store:[batch, time]
.decoded[j].values
: Values vector, size[total_decoded_outputs[j]]
. The vector stores the decoded classes for beamj
.decoded[j].dense_shape
: Shape vector, size(2)
. The shape values are:[batch_size, max_decoded_length[j]]
.log_probability
: Afloat
matrix[batch_size, top_paths]
containing sequence log-probabilities.