tf.nn.ctc_beam_search_decoder
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Performs beam search decoding on the logits given in input.
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tf.compat.v1.nn.ctc_beam_search_decoder_v2
tf . nn . ctc_beam_search_decoder (
inputs , sequence_length , beam_width = 100 , top_paths = 1
)
Note: Although in general greedy search is a special case of beam-search
with top_paths=1
and beam_width=1
, ctc_beam_search_decoder
differs
from ctc_greedy_decoder
in the treatment of blanks when computing the
probability of a sequence:
ctc_beam_search_decoder
treats blanks as sequence termination
ctc_greedy_decoder
treats blanks as regular elements
Args
inputs
3-D float
Tensor
, size [max_time, batch_size, num_classes]
.
The logits.
sequence_length
1-D int32
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, where decoded[j]
is a SparseTensor
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 beam j
.
decoded[j].dense_shape
: Shape vector, size (2)
.
The shape values are: [batch_size, max_decoded_length[j]]
.
log_probability
A float
matrix [batch_size, top_paths]
containing
sequence log-probabilities.
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Last updated 2023-03-17 UTC.
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