Medix-AI/coqui-tts
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coqui-tts
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Remove redundant dataset import

This commit is contained in:
Eren Golge 2018-04-17 10:05:50 -07:00
parent 78ad7021c5
commit dbfc489775
1 changed files with 29 additions and 30 deletions
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59
train.py
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@ -23,7 +23,6 @@ from utils.generic_utils import (Progbar, remove_experiment_folder,
count_parameters, check_update, get_commit_hash)
from utils.model import get_param_size
from utils.visual import plot_alignment, plot_spectrogram
from datasets.LJSpeech import LJSpeechDataset
from models.tacotron import Tacotron
from layers.losses import L1LossMasked
@ -296,41 +295,41 @@ def main(args):
Dataset = getattr(mod, c.dataset+"Dataset")
# Setup the dataset
train_dataset = LJSpeechDataset(os.path.join(c.data_path, c.meta_file_train),
os.path.join(c.data_path, 'wavs'),
c.r,
c.sample_rate,
c.text_cleaner,
c.num_mels,
c.min_level_db,
c.frame_shift_ms,
c.frame_length_ms,
c.preemphasis,
c.ref_level_db,
c.num_freq,
c.power,
min_seq_len=c.min_seq_len
)
train_dataset = Dataset(os.path.join(c.data_path, c.meta_file_train),
os.path.join(c.data_path, 'wavs'),
c.r,
c.sample_rate,
c.text_cleaner,
c.num_mels,
c.min_level_db,
c.frame_shift_ms,
c.frame_length_ms,
c.preemphasis,
c.ref_level_db,
c.num_freq,
c.power,
min_seq_len=c.min_seq_len
)
train_loader = DataLoader(train_dataset, batch_size=c.batch_size,
shuffle=False, collate_fn=train_dataset.collate_fn,
drop_last=False, num_workers=c.num_loader_workers,
pin_memory=True)
val_dataset = LJSpeechDataset(os.path.join(c.data_path, c.meta_file_val),
os.path.join(c.data_path, 'wavs'),
c.r,
c.sample_rate,
c.text_cleaner,
c.num_mels,
c.min_level_db,
c.frame_shift_ms,
c.frame_length_ms,
c.preemphasis,
c.ref_level_db,
c.num_freq,
c.power
)
val_dataset = Dataset(os.path.join(c.data_path, c.meta_file_val),
os.path.join(c.data_path, 'wavs'),
c.r,
c.sample_rate,
c.text_cleaner,
c.num_mels,
c.min_level_db,
c.frame_shift_ms,
c.frame_length_ms,
c.preemphasis,
c.ref_level_db,
c.num_freq,
c.power
)
val_loader = DataLoader(val_dataset, batch_size=c.eval_batch_size,
shuffle=False, collate_fn=val_dataset.collate_fn,