from omegaconf import OmegaConf _ATTENTION_DICT = { "num_heads": 8, "attn_dropout": 0.0, "bias_qkv": False, "N": 0, "rel_pos_num_buckets": 32, "rel_pos_max_distance": 64, "use_rel_pos": True, "Nproj": 8, } _BLIND_BWE_OPTIMIZATION = { "max_iter": 100, "grad_clip": 1, "tol": [1e-1, 1e-1], "clamp_fc": True, "clamp_A": True, "block_low_freq": False, "only_negative_Ap": False, "last_slope_fixed": True, "first_slope_fixed": True, } _BLIND_BWE_INITIAL_CONDITIONS = { "fref": 1000, "fc_p": [1500, 2000], "A_p": [0, 0, -80], "fc_m": [500, 50], "A_m": [0, 0, 80], } _COLLAPSE_REGULARIZATION = { "use": True, "beta": 0.1, "gamma": 1, "lambda_reg": 10, } PIANO_CONFIG = OmegaConf.create({ "architecture": "piano", "exp": { "sample_rate": 22050, "audio_len": 184184, }, "network": { "emb_dim": 256, "use_norm": True, "use_fencoding": False, "Ns": [64, 96, 96, 128, 128, 256, 256], "Ss": [2, 2, 2, 2, 2, 2, 2], "num_dils": [2, 3, 4, 5, 6, 7, 7], "attention_layers": [0, 0, 0, 0, 0, 0, 0, 0], "bottleneck_type": "res_dil_convs", "num_bottleneck_layers": 1, "cqt": {"num_octs": 7, "bins_per_oct": 64, "window": "kaiser", "beta": 1}, "attention_dict": _ATTENTION_DICT, }, "diff_params": { "sigma_data": 0.063, "sigma_min": 1e-5, "sigma_max": 10, "P_mean": -1.2, "P_std": 1.2, "ro": 13, "ro_train": 10, "Schurn": 5, "Snoise": 1, "Stmin": 0, "Stmax": 50, }, "tester": { "T": 51, "order": 2, "filter_out_cqt_DC_Nyq": True, "posterior_sampling": { "xi": 1.0, "data_consistency": False, "annealing_y": {"use": True, "mode": "fixed", "sigma_min": 0.25}, "SNR_observations": "None", "start_sigma": 0.5, "normalization": "grad_norm", "freq_weighting_filter": "sqrt", }, "diff_params": { "same_as_training": False, "sigma_data": 0.063, "sigma_min": 4e-5, "sigma_max": 10, "P_mean": -1.2, "P_std": 1.2, "ro": 13, "ro_train": 13, "Schurn": 10, "Snoise": 1.0, "Stmin": 0, "Stmax": 50, }, "blind_bwe": { "lr_filter": 10, "NFFT": 4096, "LTAS_fft": 2048, "sigma_norm": 0.07, "fcmin": 11, "fcmax": "nyquist", "Amin": -40, "Amax": 40, "Alim": 80, "initial_conditions": _BLIND_BWE_INITIAL_CONDITIONS, "optimization": _BLIND_BWE_OPTIMIZATION, }, "collapse_regularization": _COLLAPSE_REGULARIZATION, "evaluation": { "segment_length": 184184, "segment_placement": "middle", "num_segments_batch": 1, "LTAS_init": True, "LTAS_as_y": True, "overlap": 0.1, "process_complete_mode": "Block-Autoregressive", }, }, }) SINGING_CONFIG = OmegaConf.create({ "architecture": "singing", "exp": { "sample_rate": 44100, "audio_len": 262144, }, "network": { "emb_dim": 256, "use_norm": True, "use_fencoding": False, "Ns": [32, 32, 64, 64, 128, 128, 256, 256], "Ss": [2, 2, 2, 2, 2, 2, 2, 2], "num_dils": [1, 3, 4, 5, 5, 6, 6, 7], "attention_layers": [0, 0, 0, 0, 0, 0, 0, 0], "bottleneck_type": "res_dil_convs", "num_bottleneck_layers": 1, "cqt": {"num_octs": 8, "bins_per_oct": 32, "window": "kaiser", "beta": 1}, "attention_dict": _ATTENTION_DICT, }, "diff_params": { "sigma_data": 1, "sigma_min": 1e-3, "sigma_max": 100, "P_mean": -1.2, "P_std": 1.2, "ro": 10, "ro_train": 10, "Schurn": 5, "Snoise": 1, "Stmin": 0, "Stmax": 50, }, "tester": { "T": 51, "order": 2, "filter_out_cqt_DC_Nyq": True, "posterior_sampling": { "xi": 0.5, "data_consistency": False, "annealing_y": {"use": True, "mode": "fixed", "sigma_min": 1}, "SNR_observations": "None", "start_sigma": 10, "normalization": "grad_norm", "freq_weighting_filter": "sqrt", }, "diff_params": { "same_as_training": False, "sigma_data": 1, "sigma_min": 1e-3, "sigma_max": 100, "P_mean": -1.2, "P_std": 1.2, "ro": 13, "ro_train": 13, "Schurn": 10, "Snoise": 1.0, "Stmin": 0, "Stmax": 50, }, "blind_bwe": { "lr_filter": 10, "NFFT": 4096, "LTAS_fft": 4096, "sigma_norm": 1, "fcmin": 11, "fcmax": "nyquist", "Amin": -40, "Amax": 40, "Alim": 80, "initial_conditions": _BLIND_BWE_INITIAL_CONDITIONS, "optimization": _BLIND_BWE_OPTIMIZATION, }, "collapse_regularization": _COLLAPSE_REGULARIZATION, "evaluation": { "segment_length": 262144, "segment_placement": "middle", "num_segments_batch": 1, "LTAS_init": True, "LTAS_as_y": True, "overlap": 0.1, "process_complete_mode": "Block-Autoregressive", }, }, }) # display label -> (checkpoint filename on the HF Hub, architecture name) CHECKPOINTS = { "Piano (MAESTRO)": ("MAESTRO_22kHz_8s-850kits.pt", PIANO_CONFIG), "Singing Voice — Generic": ("singing_voice_pretrain_44kHz_6s-325kits.pt", SINGING_CONFIG), "Singing Voice — Enrico Caruso": ("VocalSet_male2_44kHz_6s-8kits.pt", SINGING_CONFIG), "Singing Voice — Beniamino Gigli": ("VocalSet_male11_44kHz_6s-5kits.pt", SINGING_CONFIG), "Singing Voice — Nellie Melba": ("VocalSet_female1_44kHz_6s-8kits.pt", SINGING_CONFIG), "Singing Voice — Adelina Patti": ("VocalSet_female5_44kHz_6s-8kits.pt", SINGING_CONFIG), } CHECKPOINTS_REPO = "teamup-tech/BABE2-checkpoints"