parser.add_argument("--nfx",
default=False,
action="store_true",
help="Choose numpy features extractor")
parser.add_argument("--device",
type=int,
default=0,
help="Device's id to run test on")
args = parser.parse_args()
tf.config.optimizer.set_experimental_options(
{"auto_mixed_precision": args.mxp})
setup_devices([args.device])
from sasegan.runners.tester import SeganTester
from sasegan.datasets.test_dataset import SeganTestDataset
from tensorflow_asr.configs.config import Config
from sasegan.models.sasegan import Generator
from sasegan.featurizers.speech_featurizer import NumpySpeechFeaturizer, TFSpeechFeaturizer
config = Config(args.config)
speech_featurizer = NumpySpeechFeaturizer(config.speech_config) if args.nfx \
else TFSpeechFeaturizer(config.speech_config)
tf.random.set_seed(0)
assert args.saved
parser.add_argument("--subwords",
type=str,
default=None,
help="Path to file that stores generated subwords")
parser.add_argument("--output_name",
type=str,
default="test",
help="Result filename name prefix")
args = parser.parse_args()
tf.config.optimizer.set_experimental_options(
{"auto_mixed_precision": args.mxp})
setup_devices([args.device], cpu=args.cpu)
from tensorflow_asr.configs.config import Config
from tensorflow_asr.datasets.asr_dataset import ASRTFRecordDataset, ASRSliceDataset
from tensorflow_asr.featurizers.speech_featurizers import TFSpeechFeaturizer
from tensorflow_asr.featurizers.text_featurizers import SubwordFeaturizer
from tensorflow_asr.runners.base_runners import BaseTester
from tensorflow_asr.models.conformer import Conformer
config = Config(args.config, learning=True)
speech_featurizer = TFSpeechFeaturizer(config.speech_config)
if args.subwords and os.path.exists(args.subwords):
print("Loading subwords ...")
text_featurizer = SubwordFeaturizer.load_from_file(config.decoder_config,
args.subwords)
import torch.nn as nn
import soundfile as sf
import torch.nn.functional as F
from tamil_tech.torch.utils import *
from tamil_tech.torch.models import *
import numpy as np
import tensorflow as tf
from tensorflow_asr.utils import setup_environment, setup_devices
setup_environment()
tf.config.optimizer.set_experimental_options({"auto_mixed_precision": False})
setup_devices([0], cpu=False)
from tensorflow_asr.configs.config import Config
from tensorflow_asr.featurizers.speech_featurizers import TFSpeechFeaturizer
from tensorflow_asr.featurizers.text_featurizers import CharFeaturizer, SubwordFeaturizer
from tensorflow_asr.models.conformer import Conformer
class ConformerTamilASR(object):
"""
Conformer S based ASR model
"""
def __init__(self, path='ConformerS.h5'):
# fetch and load the config of the model
config = Config('tamil_tech/configs/conformer_new_config.yml', learning=True)
# load speech and text featurizers
