tf.nn.crelu

TensorFlow 1 version

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Performs greedy decoding on the logits given in input (best path).

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.nn.ctc_greedy_decoder

tf.nn.ctc_greedy_decoder(
    inputs, sequence_length, merge_repeated=True
)

If merge_repeated is True, merge repeated classes in output. This means that if consecutive logits' maximum indices are the same, only the first of these is emitted. The sequence A B B * B * B (where '*' is the blank label) becomes

A B B B if merge_repeated=True.
A B B B B if merge_repeated=False.

Args
`inputs`	3-D `float` `Tensor` sized `[max_time, batch_size, num_classes]`. The logits.
`sequence_length`	1-D `int32` vector containing sequence lengths, having size `[batch_size]`.
`merge_repeated`	Boolean. Default: True.

Returns
A tuple `(decoded, neg_sum_logits)` where
`decoded`	A single-element list. `decoded[0]` is an `SparseTensor` containing the decoded outputs s.t.: `decoded.indices`: Indices matrix `(total_decoded_outputs, 2)`. The rows store: `[batch, time]`. `decoded.values`: Values vector, size `(total_decoded_outputs)`. The vector stores the decoded classes. `decoded.dense_shape`: Shape vector, size `(2)`. The shape values are: `[batch_size, max_decoded_length]`
`neg_sum_logits`	A `float` matrix `(batch_size x 1)` containing, for the sequence found, the negative of the sum of the greatest logit at each timeframe.

Returns

A tuple (decoded, neg_sum_logits) where

decoded

A single-element list. decoded[0] is an SparseTensor containing the decoded outputs s.t.:

decoded.indices: Indices matrix (total_decoded_outputs, 2). The rows store: [batch, time].

decoded.values: Values vector, size (total_decoded_outputs). The vector stores the decoded classes.

decoded.dense_shape: Shape vector, size (2). The shape values are: [batch_size, max_decoded_length]

neg_sum_logits A float matrix (batch_size x 1) containing, for the sequence found, the negative of the sum of the greatest logit at each timeframe.

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tf.nn / crelu

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Args

Returns