* Replaced PyTorch weight_norm With parametrizations.weight_norm
* TorchAudio: Migrating The I/O Functions To Use The Dispatcher Mechanism
* Corrected Code Style
---------
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Implement most similar ref training approach
* Use non-enhanced hifigan for test samples
* Add Perceiver
* Update GPT Trainer for perceiver support
* Update XTTS docs
* Bug fix masking with XTTS perceiver
* Bug fix on gpt forward
* Bug Fix on XTTS v2.0 training
* Add XTTS v2.0 unit tests
* Add XTTS v2.0 inference unit tests
* Bug Fix on diffusion inference
* Add XTTS v2.0 training recipe
* Placeholder model entry
* Add cloning params to config
* Make prompt embedding configurable
* Make cloning configurable
* Cheap fix for a cheaper fix
* Prevent resampling
* Update model entry
* Update docs
* Update requirements
* Code linting
* Add xtts v2 to sep tests
* Bug fix on XTTS get_gpt_cond_latents
* Bug fix on rebase
* Make style
* Bug fix in Japenese tokenizer
* Add num2words to deps
* Remove unused kwarg and added num_beams=1 as default
---------
Co-authored-by: Eren G??lge <egolge@coqui.ai>
* initial commit
* Tortoise inference
* revert path change
* style fix
* remove accidental remove
* style fixes
* style fixes
* removed unwanted assests and deps
* remove changes
* remove cvvp
* style fix black
* added tortoise config and updated config and args, refactoring the code
* added tortoise to api
* Pull mel_norm from url
* Use TTS cleaners
* Let download model files
* add ability to pass tortoise presets through coqui api
* fix tests
* fix style and tests
* fix tts commandline for tortoise
* Add config.json to tortoise
* Use kwargs
* Use regular model api for loading tortoise
* Add load from dir to synthesizer
* Fix Tortoise floats
* Use model_dir when there are multiple urls
* Use `synthesize` when exists
* lint fixes and resolve preset bug
* resolve a download bug and update model link
* fix json
* do tortoise inference from voice dir
* fix
* fix test
* fix speaker id and remove assests
* update inference_tests.yml
* replace inference_test.yml
* fix extra dir as None
* fix tests
* remove space
* Reformat docstring
* Add docs
* Update docs
* lint fixes
---------
Co-authored-by: Eren Gölge <egolge@coqui.ai>
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Use packaging.version for version comparisons
The distutils package is deprecated¹ and relies on PEP 386² version
comparisons, which have been superseded by PEP 440³ which is implemented
through the packaging module.
With more recent distutils versions, provided through setuptools
vendoring, we are seeing the following exception during version
comparisons:
> TypeError: '<' not supported between instances of 'str' and 'int'
This is fixed by this migration.
[1] https://docs.python.org/3/library/distutils.html
[2] https://peps.python.org/pep-0386/
[3] https://peps.python.org/pep-0440/
* Improve espeak version detection robustness
On many modern systems espeak is just a symlink to espeak-ng. In that
case looking for the 3rd word in the version output will break the
version comparison, when it finds `text-to-speech:`, instead of a proper
version.
This will not break during runtime, where espeak-ng would be
prioritized, but the phonemizer and tokenizer tests force the backend
to `espeak`, which exhibits this breakage.
This improves the version detection by simply looking for the version
after the "text-to-speech:" token.
* Replace distuils.copy_tree with shutil.copytree
The distutils module is deprecated and slated for removal in Python
3.12. Its usage should be replaced, in this case by a compatible method
from shutil.
* Adding neural HMM TTS
* Adding tests
* Adding neural hmm on readme
* renaming training recipe
* Removing overflow\s decoder parameters from the config
* Update the Trainer requirement version for a compatible one (#2276)
* Bump up to v0.10.2
* Adding neural HMM TTS
* Adding tests
* Adding neural hmm on readme
* renaming training recipe
* Removing overflow\s decoder parameters from the config
* fixing documentation
Co-authored-by: Edresson Casanova <edresson1@gmail.com>
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Adding pretrained Overflow model
* Stabilize HMM
* Fixup model manager
* Return `audio_unique_name` by default
* Distribute max split size over datasets
* Fixup eval_split_size
* Make style
* Adding encoder
* currently modifying hmm
* Adding hmm
* Adding overflow
* Adding overflow setting up flat start
* Removing runs
* adding normalization parameters
* Fixing models on same device
* Training overflow and plotting evaluations
* Adding inference
* At the end of epoch the test sentences are coming on cpu instead of gpu
* Adding figures from model during training to monitor
* reverting tacotron2 training recipe
* fixing inference on gpu for test sentences on config
* moving helpers and texts within overflows source code
* renaming to overflow
* moving loss to the model file
* Fixing the rename
* Model training but not plotting the test config sentences's audios
* Formatting logs
* Changing model name to camelcase
* Fixing test log
* Fixing plotting bug
* Adding some tests
* Adding more tests to overflow
* Adding all tests for overflow
* making changes to camel case in config
* Adding information about parameters and docstring
* removing compute_mel_statistics moved statistic computation to the model instead
* Added overflow in readme
* Adding more test cases, now it doesn't saves transition_p like tensor and can be dumped as json
* Update wavenet.py
Current version does not use "in_channels" argument.
In glowTTS, we use normalizing flows and so "input dim" == "ouput dim" (channels and length). So, the existing code just uses hidden_channel sized tensor as input to first layer as well as outputs hidden_channel sized tensor.
However, since it is a generic implementation, I believe it is better to update it for a more general use.
* "in_channels -> hidden_channels"
* new CI config
* initial Capacitron implementation
* delete old unused file
* fix empty formatting changes
* update losses and training script
* fix previous commit
* fix commit
* Add Capacitron test and first round of test fixes
* revert formatter change
* add changes to the synthesizer
* add stepwise gradual lr scheduler and changes to the recipe
* add inference script for dev use
* feat: add posterior inference arguments to synth methods
- added reference wav and text args for posterior inference
- some formatting
* fix: add espeak flag to base_tts and dataset APIs
- use_espeak_phonemes flag was not implemented in those APIs
- espeak is now able to be utilised for phoneme generation
- necessary phonemizer for the Capacitron model
* chore: update training script and style
- training script includes the espeak flag and other hyperparams
- made style
* chore: fix linting
* feat: add Tacotron 2 support
* leftover from dev
* chore:rename parser args
* feat: extract optimizers
- created a separate optimizer class to merge the two optimizers
* chore: revert arbitrary trainer changes
* fmt: revert formatting bug
* formatting again
* formatting fixed
* fix: log func
* fix: update optimizer
- Implemented load_state_dict for continuing training
* fix: clean optimizer init for standard models
* improvement: purge espeak flags and add training scripts
* Delete capacitronT2.py
delete old training script, new one is pushed
* feat: capacitron trainer methods
- extracted capacitron specific training operations from the trainer into custom
methods in taco1 and taco2 models
* chore: renaming and merging capacitron and gst style args
* fix: bug fixes from the previous commit
* fix: implement state_dict method on CapacitronOptimizer
* fix: call method
* fix: inference naming
* Delete train_capacitron.py
* fix: synthesize
* feat: update tests
* chore: fix style
* Delete capacitron_inference.py
* fix: fix train tts t2 capacitron tests
* fix: double forward in T2 train step
* fix: double forward in T1 train step
* fix: run make style
* fix: remove unused import
* fix: test for T1 capacitron
* fix: make lint
* feat: add blizzard2013 recipes
* make style
* fix: update recipes
* chore: make style
* Plot test sentences in Tacotron
* chore: make style and fix import
* fix: call forward first before problematic floordiv op
* fix: update recipes
* feat: add min_audio_len to recipes
* aux_input["style_mel"]
* chore: make style
* Make capacitron T2 recipe more stable
* Remove T1 capacitron Ljspeech
* feat: implement new grad clipping routine and update configs
* make style
* Add pretrained checkpoints
* Add default vocoder
* Change trainer package
* Fix grad clip issue for tacotron
* Fix scheduler issue with tacotron
Co-authored-by: Eren Gölge <egolge@coqui.ai>
Co-authored-by: WeberJulian <julian.weber@hotmail.fr>
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Add upsample VITS support
* Fix the bug in inference
* Fix lint checks
* Add RMS based norm in save_wav method
* Style fix
* Add the period for VITS multi-period discriminator in model_args
* Bug fix in speaker encoder load in inference time
* Add unit tests
* Remove useless detach_z_vocoder parameter
* Add docs for VITS upsampling
* Fix the docs
* Rename TTS_part_sample_rate to encoder_sample_rate
* Add upsampling_init and upsampling_z methods
* Add asserts for encoder_sample_rate part
* Move upsampling tests to test_vits.py
Eren Gölge
WeberJulian
Aaron-Li
Edresson Casanova
Eren G??lge
Aarni Koskela
Matthew Boakes
logan hart
Tsai Meng-Ting
manmay nakhashi
Yingzhi WANG
Martin Weinelt
Shivam Mehta
Shivam Mehta
p0p4k
a-froghyar
code-review-doctor