`athena.utils.misc`¶

misc

Module Contents¶

`mask_index_from_labels`(labels, index)
`insert_sos_in_labels`(labels, sos)
`remove_eos_in_labels`(input_labels, labels_length)	remove eos in labels, batch size should be larger than 1
`insert_eos_in_labels`(input_labels, eos, labels_length)	insert eos in labels, batch size should be larger than 1
`generate_square_subsequent_mask`(size)	Generate a square mask for the sequence. The masked positions are filled with float(1.0).
`validate_seqs`(seqs, eos)	Discard end symbol and elements after end symbol
`get_wave_file_length`(wave_file)	get the wave file length(duration) in ms
`splice_numpy`(x, context)	Splice a tensor along the last dimension with context.
`set_default_summary_writer`(summary_directory=None)
`tensor_shape`(tensor)	Return a list with tensor shape. For each dimension,

athena.utils.misc.remove_eos_in_labels(input_labels, labels_length)¶: remove eos in labels, batch size should be larger than 1 assuming 0 as the padding and the last one is the eos

athena.utils.misc.insert_eos_in_labels(input_labels, eos, labels_length)¶: insert eos in labels, batch size should be larger than 1 assuming 0 as the padding,

athena.utils.misc.generate_square_subsequent_mask(size)¶: Generate a square mask for the sequence. The masked positions are filled with float(1.0). Unmasked positions are filled with float(0.0).

athena.utils.misc.validate_seqs(seqs, eos)¶

Discard end symbol and elements after end symbol :param seqs: tf.Tensor shape=(batch_size, seq_length)

Returns:	tf.SparseTensor
Return type:	validated_preds

athena.utils.misc.get_wave_file_length(wave_file)¶

get the wave file length(duration) in ms

Parameters:	wave_file – the path of wave file
Returns:	the length(ms) of the wave file

athena.utils.misc.splice_numpy(x, context)¶

Splice a tensor along the last dimension with context. e.g.: t = [[[1, 2, 3],

[4, 5, 6], [7, 8, 9]]]

splice_tensor(t, [0, 1]) =

Parameters:	tensor – a tf.Tensor with shape (B, T, D) a.k.a. (N, H, W) context – a list of context offsets
Returns:	spliced tensor with shape (…, D * len(context))

athena.utils.misc.tensor_shape(tensor)¶: Return a list with tensor shape. For each dimension, use tensor.get_shape() first. If not available, use tf.shape().