Performs beam search decoding on the logits given in input.
tf.nn.ctc_beam_search_decoder(
inputs, sequence_length, beam_width=100, top_paths=1
)
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.
|