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mkdocs.yml
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site_name: TTS-Framework
docs_dir: docs-md
site_dir: docs
nav:
- Home: index.md
- Dev docs:
- References: dev/readme.md
- Change Log: dev/change_log.md
- Problems and Fixes: dev/problems_and_fixes.md
- Training: dev/training.md
- Lightning docs:
- References: dev/lightning/readme.md
- Basic:
- Argparse and Hyperparams: dev/lightning/basic/argparse_and_cli.md
- Debug: dev/lightning/basic/debug.md
- Early Stopping: dev/lightning/basic/early_stopping.md
- Find Bottlenecks: dev/lightning/basic/find_bottlenecks.md
- Saving Loading checkpoints: dev/lightning/basic/saving_loading_checkpoints.md
- Visualize Experiments: dev/lightning/basic/visualize_experiments.md
- Intermediate:
- Hardware-Agnostic training: dev/lightning/intermediate/hardware_agnostic_training.md
- GPU training: dev/lightning/intermediate/gpu_training.md
- Lightning Data Module: dev/lightning/intermediate/lightning_data_module.md
- Configure hyperparameters from the CLI: dev/lightning/intermediate/configure_hyperparameters_from_the_cli.md
- Customize checkpointing behavior: dev/lightning/intermediate/customize_checkpointing_behavior.md
- Track and Visualize Experiments: dev/lightning/intermediate/track_and_visualize_experiments.md
- SOTA scaling techniques (N-Bit Precision): dev/lightning/intermediate/sota_scaling_techniques.md
- Important! Effective Training Techniques (Acc grad,cliping): dev/lightning/intermediate/effective_training_techniques.md
- Deploy Models into Production: dev/lightning/intermediate/deploy_models_into_production.md
- Advanced:
- Configure hyperparameters from the CLI: dev/lightning/advanced/hyperparameters_from_the_cli.md
- Customize training loop: dev/lightning/advanced/own_your_loop.md
- Models:
- Config:
- References: models/config/readme.md
- Langs: models/config/langs.md
- Enhancer:
- Gaussian Diffusion:
- Gaussian Diffusion: models/enhancer/gaussian_diffusion/gaussian_diffusion.md
- Denoiser: models/enhancer/gaussian_diffusion/denoiser.md
- Layers: models/enhancer/gaussian_diffusion/layers.md
- Utils: models/enhancer/gaussian_diffusion/utils.md
- TTS:
- Delightful TTS:
- References: models/tts/delightful_tts/readme.md
- DelightfulTTS: models/tts/delightful_tts/delightful_tts.md
- Convolution Blocks:
- References: models/tts/delightful_tts/conv_blocks/readme.md
- Activation: models/tts/delightful_tts/conv_blocks/activation.md
- Conv1d: models/tts/delightful_tts/conv_blocks/conv1d.md
- BSConv: models/tts/delightful_tts/conv_blocks/bsconv.md
- Conv1dGLU: models/tts/delightful_tts/conv_blocks/conv1d_glu.md
- ConvTransposed: models/tts/delightful_tts/conv_blocks/conv_transposed.md
- CoordConv1d: models/tts/delightful_tts/conv_blocks/coord_conv1d.md
- AddCoords: models/tts/delightful_tts/conv_blocks/add_coords.md
- Attention:
- References: models/tts/delightful_tts/attention/readme.md
- Conformer: models/tts/delightful_tts/attention/conformer.md
- Feed Forward: models/tts/delightful_tts/attention/feed_forward.md
- Style Embed Attention: models/tts/delightful_tts/attention/style_embed_attention.md
- Multi-Head Attention: models/tts/delightful_tts/attention/multi_head_attention.md
- Relative Multi-Head Attention: models/tts/delightful_tts/attention/relative_multi_head_attention.md
- Conformer Multi-Headed Self Attention: models/tts/delightful_tts/attention/conformer_multi_headed_self_attention.md
- Conformer Convolution Module: models/tts/delightful_tts/attention/conformer_conv_module.md
- Conformer Block: models/tts/delightful_tts/attention/conformer_block.md
- Acoustic Model:
- Aligner: models/tts/delightful_tts/acoustic_model/aligner.md
- References: models/tts/delightful_tts/acoustic_model/readme.md
- Accoustic Model: models/tts/delightful_tts/acoustic_model/acoustic_model.md
- Embedding: models/tts/delightful_tts/acoustic_model/embedding.md
- Helpers: models/tts/delightful_tts/acoustic_model/helpers.md
- Variance Predictor: models/tts/delightful_tts/acoustic_model/variance_predictor.md
- Pitch Adaptor Conv: models/tts/delightful_tts/acoustic_model/pitch_adaptor_conv.md
- Energy Adaptor: models/tts/delightful_tts/acoustic_model/energy_adaptor.md
- Length Adaptor: models/tts/delightful_tts/acoustic_model/length_adaptor.md
- Phoneme Prosody Predictor: models/tts/delightful_tts/acoustic_model/phoneme_prosody_predictor.md
- Aligner:
- Monotonic Alignments Shrink: models/tts/delightful_tts/acoustic_model/mas.md
- Reference Encoder:
- References: models/tts/delightful_tts/reference_encoder/readme.md
- Style Token Layer (STL): models/tts/delightful_tts/reference_encoder/STL.md
- Reference Encoder: models/tts/delightful_tts/reference_encoder/reference_encoder.md
- Utterance Level Prosody Encoder: models/tts/delightful_tts/reference_encoder/utterance_level_prosody_encoder.md
- Phoneme Level Prosody Encoder: models/tts/delightful_tts/reference_encoder/phoneme_level_prosody_encoder.md
- StyledTTS 2:
- References: models/tts/styledtts2/readme.md
- Diffusion:
- Diffusion: models/tts/styledtts2/diffusion/diffusion.md
- Distributions: models/tts/styledtts2/diffusion/distributions.md
- Embeddings: models/tts/styledtts2/diffusion/embeddings.md
- Attention: models/tts/styledtts2/diffusion/attention.md
- AdaLayerNorm: models/tts/styledtts2/diffusion/ada_layer_norm.md
- Utils: models/tts/styledtts2/diffusion/utils.md
- Vocoder:
- Univnet:
- References: models/vocoder/univnet/readme.md
- Univnet: models/vocoder/univnet/univnet.md
- Generator: models/vocoder/univnet/generator.md
- Traced Generator: models/vocoder/univnet/traced_generator.md
- Kernel Predictor: models/vocoder/univnet/kernel_predictor.md
- LVC Block: models/vocoder/univnet/lvc_block.md
- Discriminator: models/vocoder/univnet/discriminator.md
- DiscriminatorP: models/vocoder/univnet/discriminator_p.md
- DiscriminatorR: models/vocoder/univnet/discriminator_r.md
- Multi Period Discriminator: models/vocoder/univnet/multi_period_discriminator.md
- Multi Resolution Discriminator: models/vocoder/univnet/multi_resolution_discriminator.md
- Helpers:
- References: models/helpers/readme.md
- Initializer: models/helpers/initializer.md
- Acoustic: models/helpers/acoustic.md
- Tools: models/helpers/tools.md
- Training:
- References: training/readme.md
- Loss:
- References: training/loss/readme.md
- Acoustic Losses:
- Binary Cross Entropy Loss: training/loss/bin_loss.md
- Forward Sum Loss: training/loss/forward_sum_loss.md
- FastSpeech 2 Loss: training/loss/fast_speech_2_loss_gen.md
- Voicoder Losses:
- STFT: training/loss/stft.md
- STFT Loss: training/loss/stft_loss.md
- Log STFT Magnitude Loss: training/loss/log_stft_magnitude_loss.md
- Spectral Convergence Loss: training/loss/spectral_convergence_loss.md
- Multi Resolution STFT Loss: training/loss/multi_resolution_stft_loss.md
- Univnet loss: training/loss/univnet_loss.md
- Datasets:
- References: training/dataset/readme.md
- Libri TTS dataset acoustic: training/dataset/libritts_dataset_acoustic.md
- Libri TTS dataset vocoder: training/dataset/libritts_dataset_vocoder.md
- Preprocess:
- References: training/preprocess/readme.md
- Audio: training/preprocess/audio.md
- Audio Processor: training/preprocess/audio_processor.md
- compute_yin: training/preprocess/compute_yin.md
- Normalize Text: training/preprocess/normalize_text.md
- Preprocess LibriTTS: training/preprocess/preprocess_libritts.md
- TacotronSTFT: training/preprocess/tacotron_stft.md
- Wav2Vec Aligner: training/preprocess/wav2vec_aligner.md
- Tools: training/tools.md
- Experiments:
- References: experiments/readme.md
- MAS torch: experiments/mas_torch.md
- Conv Leaky ReLU: experiments/conv_leaky_relu.md
- Tokenization: experiments/tokenization.md
- Optimizer:
- References: experiments/optimizer/readme.md
- Scheduled Optim Pretraining: experiments/optimizer/scheduled_optim_pretraining.md
- Scheduled Optim Finetuning: experiments/optimizer/scheduled_optim_finetuning.md
- About mkdocs-material: readme.md
theme:
name: material
features:
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markdown_extensions:
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plugins:
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- mkdocstrings:
default_handler: python
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