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models/synthesizer/hparams.py
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babysor00
Fix issue for training and preprocessing
10 фев 2023, 15:34
10 фев 2023, 15:34
3ce874a
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from utils.hparams import HParams hparams = HParams( ### Signal Processing (used in both synthesizer and vocoder) sample_rate = 16000, n_fft = 1024, # filter_length num_mels = 80, hop_size = 256, # Tacotron uses 12.5 ms frame shift (set to sample_rate * 0.0125) win_size = 1024, # Tacotron uses 50 ms frame length (set to sample_rate * 0.050) fmin = 55, min_level_db = -100, ref_level_db = 20, max_abs_value = 4., # Gradient explodes if too big, premature convergence if too small. preemphasis = 0.97, # Filter coefficient to use if preemphasize is True preemphasize = True, ### Tacotron Text-to-Speech (TTS) tts_embed_dims = 512, # Embedding dimension for the graphemes/phoneme inputs tts_encoder_dims = 256, tts_decoder_dims = 128, tts_postnet_dims = 512, tts_encoder_K = 5, tts_lstm_dims = 1024, tts_postnet_K = 5, tts_num_highways = 4, tts_dropout = 0.5, tts_cleaner_names = ["basic_cleaners"], tts_stop_threshold = -3.4, # Value below which audio generation ends. # For example, for a range of [-4, 4], this # will terminate the sequence at the first # frame that has all values < -3.4 ### Tacotron Training tts_schedule = [(2, 1e-3, 10_000, 12), # Progressive training schedule (2, 5e-4, 15_000, 12), # (r, lr, step, batch_size) (2, 2e-4, 20_000, 12), # (r, lr, step, batch_size) (2, 1e-4, 30_000, 12), # (2, 5e-5, 40_000, 12), # (2, 1e-5, 60_000, 12), # (2, 5e-6, 160_000, 12), # r = reduction factor (# of mel frames (2, 3e-6, 320_000, 12), # synthesized for each decoder iteration) (2, 1e-6, 640_000, 12)], # lr = learning rate tts_clip_grad_norm = 1.0, # clips the gradient norm to prevent explosion - set to None if not needed tts_eval_interval = 500, # Number of steps between model evaluation (sample generation) # Set to -1 to generate after completing epoch, or 0 to disable tts_eval_num_samples = 1, # Makes this number of samples ## For finetune usage, if set, only selected layers will be trained, available: encoder,encoder_proj,gst,decoder,postnet,post_proj tts_finetune_layers = [], ### Data Preprocessing max_mel_frames = 900, rescale = True, rescaling_max = 0.9, synthesis_batch_size = 16, # For vocoder preprocessing and inference. ### Mel Visualization and Griffin-Lim signal_normalization = True, power = 1.5, griffin_lim_iters = 60, ### Audio processing options fmax = 7600, # Should not exceed (sample_rate // 2) allow_clipping_in_normalization = True, # Used when signal_normalization = True clip_mels_length = True, # If true, discards samples exceeding max_mel_frames use_lws = False, # "Fast spectrogram phase recovery using local weighted sums" symmetric_mels = True, # Sets mel range to [-max_abs_value, max_abs_value] if True, # and [0, max_abs_value] if False trim_silence = False, # Use with sample_rate of 16000 for best results ### SV2TTS speaker_embedding_size = 256, # Dimension for the speaker embedding silence_min_duration_split = 0.4, # Duration in seconds of a silence for an utterance to be split utterance_min_duration = 0.5, # Duration in seconds below which utterances are discarded use_gst = True, # Whether to use global style token use_ser_for_gst = True, # Whether to use speaker embedding referenced for global style token )