def get_optional_params():
return dict(DataLayer.get_optional_params(), **{
'num_parallel_calls': int,
'shuffle_buffer': int,
'image_size': int,
'num_classes': int,
})
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_optional_params():
return dict(
DataLayer.get_optional_params(), **{
'repeat': int,
'num_cpu_cores': int,
'tgt_vocab_file': str,
'pad_data_to_eight': bool,
'batch_in_tokens': bool,
})
def get_optional_params():
return dict(
DataLayer.get_optional_params(), **{
'augmentation': dict,
'pad_to': int,
'max_duration': float,
'bpe': bool,
'autoregressive': bool,
})
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(), **{
"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(), **{
'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_optional_params():
return dict(DataLayer.get_optional_params(), **{
'augmentation': dict,
'pad_to': int,
'max_duration': float,
'bpe': bool,
'autoregressive': bool,
'syn_enable': bool,
'syn_subdirs': list,
'window_size': float,
'window_stride': float,
})
def get_optional_params():
return dict(
DataLayer.get_optional_params(), **{
'use_targets': bool,
'delimiter': str,
'target_file': str,
'map_parallel_calls': int,
'prefetch_buffer_size': int,
'pad_lengths_to_eight': bool,
'pad_vocab_to_eight': bool,
'shuffle_buffer_size': int,
'special_tokens_already_in_vocab': bool,
'use_start_token': bool,
})
def get_optional_params():
return dict(DataLayer.get_optional_params(), **{
'data_root': str,
'rand_start': bool,
'small': bool,
'use_targets': bool,
'delimiter': str,
'map_parallel_calls': int,
'prefetch_buffer_size': int,
'pad_lengths_to_eight': bool,
'pad_vocab_to_eight': bool,
'seed_tokens': str,
'shuffle_buffer_size': int,
'processed_data_folder': str,
})
def get_optional_params():
return dict(DataLayer.get_optional_params(), **{
'rand_start': bool,
'small': bool,
'use_targets': bool,
'delimiter': str,
'map_parallel_calls': int,
'prefetch_buffer_size': int,
'pad_lengths_to_eight': bool,
'pad_vocab_to_eight': bool,
'shuffle_buffer_size': int,
'data_root': str,
'binary': bool,
'num_classes': int,
'get_stats': bool,
})
def get_optional_params():
return dict(
DataLayer.get_optional_params(), **{
'pad_to': int,
'mag_power': int,
'pad_EOS': bool,
'pad_value': float,
'feature_normalize_mean': float,
'feature_normalize_std': float,
'trim': bool,
'data_min': None,
'duration_min': int,
'duration_max': int,
'mel_type': ['slaney', 'htk'],
"exp_mag": bool
}
)
def get_optional_params():
return dict(DataLayer.get_optional_params(),
**{"dataset_location": str})
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(), **{
'data_dir': str,
})
def get_required_params():
return dict(DataLayer.get_required_params(), **{
'repeat': bool,
'bptt': int,
})
def get_optional_params():
return dict(DataLayer.get_optional_params(), **{
"cache_data": bool,
"augment_data": bool
})