from malaya.supervised import t2t
from malaya.supervised.settings import phoneme_left, phoneme_right
from malaya.supervised.settings import phoneme_ipa_left, phoneme_ipa_right
from malaya.text.function import phoneme_textcleaning
from herpetologist import check_type
from typing import List
[docs]@check_type
def deep_model_dbp(quantized: bool = False, **kwargs):
"""
Load LSTM + Bahdanau Attention phonetic model,
256 filter size, 2 layers, character level.
original data from https://prpm.dbp.gov.my/ Glosari Dialek.
Original size 10.4MB, quantized size 2.77MB .
Parameters
----------
quantized : bool, optional (default=False)
if True, will load 8-bit quantized model.
Quantized model not necessary faster, totally depends on the machine.
Returns
-------
result: malaya.model.tf.Seq2SeqLSTM class
"""
return t2t.load_lstm(
module='phoneme',
left_dict=phoneme_left,
right_dict=phoneme_right,
cleaning=phoneme_textcleaning,
quantized=quantized,
**kwargs,
)
[docs]def deep_model_ipa(quantized: bool = False, **kwargs):
"""
Load LSTM + Bahdanau Attention phonetic model,
256 filter size, 2 layers, character level.
Original data from https://github.com/open-dict-data/ipa-dict/blob/master/data/ma.txt
Original size 10.4MB, quantized size 2.77MB .
Parameters
----------
quantized : bool, optional (default=False)
if True, will load 8-bit quantized model.
Quantized model not necessary faster, totally depends on the machine.
Returns
-------
result: malaya.model.tf.Seq2SeqLSTM_Split class
"""
return t2t.load_lstm(
module='phoneme-ipa',
left_dict=phoneme_ipa_left,
right_dict=phoneme_ipa_right,
cleaning=phoneme_textcleaning,
split=True,
quantized=quantized,
**kwargs,
)
