def get_required_params():
return dict(DataLayer.get_required_params(), **{
'num_audio_features': int,
'input_type': ['spectrogram', 'mfcc', 'logfbank'],
'vocab_file': str,
'dataset_files': list,
})
def get_required_params():
return dict(DataLayer.get_required_params(), **{
'lm_vocab_file': str,
'shuffle': bool,
'repeat': bool,
'max_length': int,
'processed_data_folder': str,
})
def get_required_params():
return dict(
DataLayer.get_required_params(), **{
"dataset_files": list,
"dataset_location": str,
"num_audio_features": int,
"audio_length": int,
"num_labels": int,
"model_format": str
})
def get_required_params():
return dict(
DataLayer.get_required_params(), **{
'source_file': str,
'src_vocab_file': str,
'tgt_vocab_file': str,
'max_length': int,
'shuffle': bool,
'repeat': bool,
})
def get_required_params():
return dict(
DataLayer.get_required_params(), **{
'data_dir': str,
'file_pattern': str,
'src_vocab_file': str,
'batch_size': int,
'max_length': int,
'shuffle': bool,
"delimiter": str,
})
def get_required_params():
return dict(
DataLayer.get_required_params(), **{
'dataset_location': str,
'dataset': ['LJ', 'MAILABS'],
'num_audio_features': None,
'output_type': ['magnitude', 'mel', 'both'],
'vocab_file': str,
'dataset_files': list,
'feature_normalize': bool,
}
)
def get_required_params():
return dict(DataLayer.get_required_params(), **{
"num_audio_features": int,
"dataset_files": list
})
def get_required_params():
return dict(DataLayer.get_required_params(), **{
'repeat': bool,
'bptt': int,
})
def get_required_params():
return dict(DataLayer.get_required_params(), **{
'data_dir': str,
})