def get_optional_params(): return dict(DataLayer.get_optional_params(), **{ 'repeat': int, 'num_cpu_cores': int, 'tgt_vocab_file': str, 'm_padding': bool, })
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'], 'vocab_file': str, 'dataset_files': list, })
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, 'style_input': [None, 'wav'], 'n_samples_eval': int, 'n_fft': int, 'fmax': float, 'max_normalization': bool, 'use_cache': bool, "save_embeddings": bool, "use_npy_wavs": bool, "use_phonemes": bool, "use_saved_embedding": bool, "saved_embedding_location": str, })
def get_optional_params(): return dict( DataLayer.get_optional_params(), **{ 'augmentation': dict, 'pad_to': int, 'max_duration': float, })
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(), **{ # 'content_file': str, # 'vocab_file': str, 'shuffle': bool, 'repeat': bool, 'bptt': int, })
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(), **{ "dataset_files": list, "dataset_location": str, "num_audio_features": int, "num_labels": int })
def get_optional_params(): return dict(DataLayer.get_optional_params(), **{ 'delimiter': str, 'map_parallel_calls': int, 'prefetch_buffer_size': int, 'pad_lengths_to_eight': bool, 'pad_vocab_to_eight': bool, 'seed_file': 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(), **{ '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_location': str, 'mel_feature_num': None, 'vocab_file': str, 'dataset_files': list, "minimal_vocabulary": bool, })
def get_optional_params(): return dict( DataLayer.get_optional_params(), **{ 'pad_to': int, 'mag_power': int, 'pad_EOS': bool, 'feature_normalize_mean': float, 'feature_normalize_std': float })
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, '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(), **{ '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, })
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(), **{ '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(), **{ '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(), **{ 'backend': ['psf', 'librosa'], 'augmentation': dict, 'pad_to': int, 'max_duration': float, 'min_duration': float, 'bpe': bool, 'autoregressive': bool, 'syn_enable': bool, 'syn_subdirs': list, 'window_size': float, 'window_stride': float, 'dither': float, 'norm_per_feature': bool, 'window': ['hanning', 'hamming', 'none'], 'num_fft': int, 'precompute_mel_basis': bool, 'sample_freq': int, })
def get_required_params(): return dict(DataLayer.get_required_params(), **{ 'vocab_file': str, 'bptt': int, })
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_required_params(): return dict(DataLayer.get_required_params(), **{ "num_audio_features": int, "dataset_files": list })
def get_optional_params(): return dict(DataLayer.get_optional_params(), **{ 'augmentation': dict, 'pad_to': int, })
def get_optional_params(): return dict(DataLayer.get_optional_params(), **{"dataset_location": str})
def get_optional_params(): return dict(DataLayer.get_optional_params(), **{ "cache_data": bool, "augment_data": bool })
def get_optional_params(): return dict(DataLayer.get_optional_params(), **{ 'num_parallel_calls': int, 'shuffle_buffer': int, })