mirror of
https://github.com/wassname/TTS.git
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Update glowtts docstrings and docs
This commit is contained in:
Eren Gölge
@@ -1,25 +0,0 @@
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# AudioProcessor
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`TTS.utils.audio.AudioProcessor` is the core class for all the audio processing routines. It provides an API for
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- Feature extraction.
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- Sound normalization.
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- Reading and writing audio files.
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- Sampling audio signals.
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- Normalizing and denormalizing audio signals.
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- Griffin-Lim vocoder.
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The `AudioProcessor` needs to be initialized with `TTS.config.shared_configs.BaseAudioConfig`. Any model config
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also must inherit or initiate `BaseAudioConfig`.
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## AudioProcessor
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```{eval-rst}
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.. autoclass:: TTS.utils.audio.AudioProcessor
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:members:
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```
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## BaseAudioConfig
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```{eval-rst}
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.. autoclass:: TTS.config.shared_configs.BaseAudioConfig
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:members:
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```
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+37
-20
@@ -50,6 +50,43 @@ exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', 'TODO/*']
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source_suffix = [".rst", ".md"]
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# extensions
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.autosummary',
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'sphinx.ext.doctest',
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'sphinx.ext.intersphinx',
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'sphinx.ext.todo',
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'sphinx.ext.coverage',
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'sphinx.ext.napoleon',
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'sphinx.ext.viewcode',
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'sphinx.ext.autosectionlabel',
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'myst_parser',
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"sphinx_copybutton",
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"sphinx_inline_tabs",
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]
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# 'sphinxcontrib.katex',
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# 'sphinx.ext.autosectionlabel',
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# autosectionlabel throws warnings if section names are duplicated.
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# The following tells autosectionlabel to not throw a warning for
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# duplicated section names that are in different documents.
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autosectionlabel_prefix_document = True
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language = None
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autodoc_inherit_docstrings = False
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# Disable displaying type annotations, these can be very verbose
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autodoc_typehints = 'none'
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# Enable overriding of function signatures in the first line of the docstring.
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autodoc_docstring_signature = True
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napoleon_custom_sections = [('Shapes', 'shape')]
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# -- Options for HTML output -------------------------------------------------
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@@ -80,23 +117,3 @@ html_sidebars = {
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']
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# using markdown
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.autosummary',
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'sphinx.ext.doctest',
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'sphinx.ext.intersphinx',
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'sphinx.ext.todo',
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'sphinx.ext.coverage',
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'sphinx.ext.napoleon',
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'sphinx.ext.viewcode',
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'sphinx.ext.autosectionlabel',
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'myst_parser',
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"sphinx_copybutton",
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"sphinx_inline_tabs",
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]
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# 'sphinxcontrib.katex',
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# 'sphinx.ext.autosectionlabel',
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@@ -1,4 +1,4 @@
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# Converting Torch Tacotron to TF 2
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# Converting Torch to TF 2
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Currently, 🐸TTS supports the vanilla Tacotron2 and MelGAN models in TF 2.It does not support advanced attention methods and other small tricks used by the Torch models. You can convert any Torch model trained after v0.0.2.
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@@ -1,25 +0,0 @@
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# Datasets
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## TTS Dataset
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```{eval-rst}
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.. autoclass:: TTS.tts.datasets.TTSDataset
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:members:
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```
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## Vocoder Dataset
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```{eval-rst}
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.. autoclass:: TTS.vocoder.datasets.gan_dataset.GANDataset
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:members:
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```
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```{eval-rst}
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.. autoclass:: TTS.vocoder.datasets.wavegrad_dataset.WaveGradDataset
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:members:
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```
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```{eval-rst}
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.. autoclass:: TTS.vocoder.datasets.wavernn_dataset.WaveRNNDataset
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:members:
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```
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+1
-1
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- Check the 4th step under "How can I check model performance?"
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## How can I test a trained model?
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- The best way is to use `tts` or `tts-server` commands. For details check {ref}`here <Synthesizing Speech>`.
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- The best way is to use `tts` or `tts-server` commands. For details check {ref}`here <synthesizing_speech>`.
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- If you need to code your own ```TTS.utils.synthesizer.Synthesizer``` class.
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## My Tacotron model does not stop - I see "Decoder stopped with 'max_decoder_steps" - Stopnet does not work.
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@@ -36,7 +36,7 @@
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There is also the `callback` interface by which you can manipulate both the model and the `Trainer` states. Callbacks give you
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the infinite flexibility to add custom behaviours for your model and training routines.
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For more details, see {ref}`BaseTTS <Base TTS Model>` and `TTS/utils/callbacks.py`.
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For more details, see {ref}`BaseTTS <Base TTS Model>` and :obj:`TTS.utils.callbacks`.
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6. Optionally, define `MyModelArgs`.
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+20
-7
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```{include} ../../README.md
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:relative-images:
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```
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----
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# Documentation Content
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@@ -27,14 +26,28 @@
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formatting_your_dataset
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what_makes_a_good_dataset
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tts_datasets
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converting_torch_to_tf
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.. toctree::
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:maxdepth: 2
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:caption: Main Classes
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trainer_api
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audio_processor
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model_api
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configuration
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dataset
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```
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main_classes/trainer_api
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main_classes/audio_processor
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main_classes/model_api
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main_classes/dataset
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main_classes/gan
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.. toctree::
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:maxdepth: 2
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:caption: `tts` Models
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models/glow_tts.md
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.. toctree::
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:maxdepth: 2
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:caption: `vocoder` Models
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main_classes/gan
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```
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@@ -1,4 +1,4 @@
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# AudioProcessor
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# AudioProcessor API
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`TTS.utils.audio.AudioProcessor` is the core class for all the audio processing routines. It provides an API for
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@@ -19,6 +19,6 @@ Model API provides you a set of functions that easily make your model compatible
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## Base `vocoder` Model
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```{eval-rst}
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.. autoclass:: TTS.tts.models.base_vocoder.BaseVocoder`
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.. autoclass:: TTS.vocoder.models.base_vocoder.BaseVocoder
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:members:
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```
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@@ -1,24 +0,0 @@
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# Model API
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Model API provides you a set of functions that easily make your model compatible with the `Trainer`,
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`Synthesizer` and `ModelZoo`.
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## Base TTS Model
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```{eval-rst}
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.. autoclass:: TTS.model.BaseModel
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:members:
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```
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## Base `tts` Model
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```{eval-rst}
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.. autoclass:: TTS.tts.models.base_tts.BaseTTS
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:members:
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```
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## Base `vocoder` Model
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```{eval-rst}
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.. autoclass:: TTS.tts.models.base_vocoder.BaseVocoder`
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:members:
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```
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@@ -1,17 +0,0 @@
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# Trainer API
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The {class}`TTS.trainer.Trainer` provides a lightweight, extensible, and feature-complete training run-time. We optimized it for 🐸 but
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can also be used for any DL training in different domains. It supports distributed multi-gpu, mixed-precision (apex or torch.amp) training.
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## Trainer
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```{eval-rst}
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.. autoclass:: TTS.trainer.Trainer
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:members:
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```
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## TrainingArgs
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```{eval-rst}
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.. autoclass:: TTS.trainer.TrainingArgs
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:members:
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```
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