def get_infer_dir(train_dir: str, wav_path: str, iteration: int):
input_name = get_basename(wav_path)
subdir_name = f"{datetime.datetime.now():%Y-%m-%d,%H-%M-%S},wav={input_name},it={iteration}"
return get_subdir(get_inference_root_dir(train_dir), subdir_name, create=True)
def get_analysis_root_dir(train_dir: str): return get_subdir(train_dir, "analysis", create=True)
def get_text_dir(ds_dir: str, text_name: str, create: bool = False):
return get_subdir(_get_text_root_dir(ds_dir, create), text_name, create)
def get_checkpoints_dir(train_dir: str):
return get_subdir(train_dir, "checkpoints", create=True)
def get_ds_dir(base_dir: str, ds_name: str, create: bool = False):
return get_subdir(_get_ds_root_dir(base_dir, create), ds_name, create)
def _get_prepared_root_dir(base_dir: str, create: bool = False):
return get_subdir(get_pre_dir(base_dir, create), 'prepared', create)
def get_inference_root_dir(train_dir: str):
return get_subdir(train_dir, "inference", create=True)
def get_infer_dir(train_dir: str, input_name: str, iteration: int, speaker_name: str):
subdir_name = f"{datetime.datetime.now():%Y-%m-%d,%H-%M-%S},text={input_name},speaker={speaker_name},it={iteration}"
return get_subdir(get_inference_root_dir(train_dir), subdir_name, create=True)
def _get_plots_root_dir(ds_dir: str, create: bool = False):
return get_subdir(ds_dir, "plots", create)
def get_plots_dir(ds_dir: str, mel_name: str, create: bool = False):
return get_subdir(_get_plots_root_dir(ds_dir, create), mel_name, create)
def _get_mel_root_dir(ds_dir: str, create: bool = False): return get_subdir(ds_dir, "mel", create)
def get_wav_dir(ds_dir: str, wav_name: str, create: bool = False):
return get_subdir(_get_wav_root_dir(ds_dir, create), wav_name, create)
def _get_wav_root_dir(ds_dir: str, create: bool = False):
return get_subdir(ds_dir, "wav", create)
def _get_trim_root_dir(wav_dir: str):
return get_subdir(wav_dir, "trim", create=True)
def _get_validation_root_dir(train_dir: str):
return get_subdir(train_dir, "validation", create=True)
def get_train_dir(base_dir: str, train_name: str, create: bool):
return get_subdir(get_train_root_dir(base_dir, "waveglow", create),
train_name, create)
def get_val_dir(train_dir: str, entry: PreparedData, iteration: int):
subdir_name = f"{datetime.datetime.now():%Y-%m-%d,%H-%M-%S},id={entry.entry_id},speaker={entry.speaker_id},it={iteration}"
return get_subdir(_get_validation_root_dir(train_dir),
subdir_name,
create=True)
def _get_ds_root_dir(base_dir: str, create: bool = False):
return get_subdir(get_pre_dir(base_dir, create), "ds", create)
def get_train_root_dir(base_dir: str, model_name: str, create: bool):
return get_subdir(base_dir, model_name, create)
def get_ds_examples_dir(ds_dir: str, create: bool = False):
return get_subdir(ds_dir, "examples", create)
def get_train_logs_dir(train_dir: str):
return get_subdir(train_dir, "logs", create=True)
def get_prepared_dir(base_dir: str, prep_name: str, create: bool = False):
return get_subdir(_get_prepared_root_dir(base_dir, create), prep_name,
create)
def _get_text_root_dir(ds_dir: str, create: bool = False):
return get_subdir(ds_dir, "text", create)