text_featurizer=text_featurizer,
**vars(config.learning_config.eval_dataset_config))
else:
train_dataset = ASRSliceDataset(
speech_featurizer=speech_featurizer,
text_featurizer=text_featurizer,
**vars(config.learning_config.train_dataset_config))
eval_dataset = ASRSliceDataset(
speech_featurizer=speech_featurizer,
text_featurizer=text_featurizer,
**vars(config.learning_config.eval_dataset_config))
ctc_trainer = CTCTrainerGA(text_featurizer,
config.learning_config.running_config)
# Build DS2 model
with ctc_trainer.strategy.scope():
jasper = Jasper(**config.model_config,
vocabulary_size=text_featurizer.num_classes)
jasper._build(speech_featurizer.shape)
jasper.summary(line_length=120)
# Compile
ctc_trainer.compile(jasper,
config.learning_config.optimizer_config,
max_to_keep=args.max_ckpts)
ctc_trainer.fit(train_dataset,
eval_dataset,
train_bs=args.tbs,
eval_bs=args.ebs,
train_acs=args.acs)
from tensorflow_asr.configs.user_config import UserConfig
from tensorflow_asr.datasets.asr_dataset import ASRTFRecordDataset, ASRSliceDataset
from tensorflow_asr.featurizers.speech_featurizers import TFSpeechFeaturizer
from tensorflow_asr.featurizers.text_featurizers import CharFeaturizer
from tensorflow_asr.runners.base_runners import BaseTester
from tensorflow_asr.models.jasper import Jasper
tf.random.set_seed(0)
assert args.export
config = UserConfig(DEFAULT_YAML, args.config, learning=True)
speech_featurizer = TFSpeechFeaturizer(config["speech_config"])
text_featurizer = CharFeaturizer(config["decoder_config"])
# Build DS2 model
jasper = Jasper(**config["model_config"], vocabulary_size=text_featurizer.num_classes)
jasper._build(speech_featurizer.shape)
jasper.load_weights(args.saved, by_name=True)
jasper.summary(line_length=120)
jasper.add_featurizers(speech_featurizer, text_featurizer)
if args.tfrecords:
test_dataset = ASRTFRecordDataset(
data_paths=config["learning_config"]["dataset_config"]["test_paths"],
tfrecords_dir=config["learning_config"]["dataset_config"]["tfrecords_dir"],
speech_featurizer=speech_featurizer,
text_featurizer=text_featurizer,
stage="test", shuffle=False
)
else:
test_dataset = ASRSliceDataset(