tsukumi
d397a58874
Fix: errors during ONNX CPU inference
2024-10-06 16:18:21 +09:00
tsukumi
c4b6c169fc
Fix: Inference failure with some ExecutionProviders
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length_scale, etc. were passed as one-dimensional arrays when they should have been passed as scalar values.
2024-09-28 17:36:26 +09:00
tsukumi
7793e9da43
Remove: Unused import
2024-09-28 13:50:10 +09:00
tsukumi
d935d30e4c
Add: test code for CoreMLExecutionProvider on a trial basis
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Currently ONNXRuntime's CoreML support is not very good, and on my environment, I get errors like “coreml_execution_provider.cc:192 operator() Input (/sdp/flows.3/GatherND_2_output_0) has a dynamic shape ({-1,-1}) but the runtime shape ({0,10}) has zero elements. This is not supported by the CoreML EP.” and inference fails.
I hope this will be fixed in a future version of ONNXRuntime, and leave the test code as it is.
2024-09-23 21:07:27 +09:00
tsukumi
b67e50fd8d
Improve: DirectML inference performance
2024-09-23 20:20:46 +09:00
tsukumi
e91b69862c
Fix: ONNX inference with DirectML fails
2024-09-23 15:06:19 +09:00
tsukumi
758696c59c
Fix: Device ID specified in ExecutionProvider options is respected when moving input tensors
2024-09-23 12:57:14 +09:00
tsukumi
c792bf9a0d
Improve: Make ONNX inference tests more rigorous
2024-09-23 12:27:29 +09:00
tsukumi
2cdb5844cb
Fix: ONNX inference fails in Windows environments
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ref: https://qiita.com/gomasa/items/f6337087988685d00ebb
2024-09-23 11:55:50 +09:00
tsukumi
5ca6e184d7
Fix: ONNX inference of BERT models fails in some Windows environments
2024-09-23 11:33:17 +09:00
tsukumi
eb5d245903
Add: Test for ONNX inference code (without PyTorch dependency)
2024-09-23 10:04:02 +09:00
tsukumi
faddb0a8a8
Fix: Don't list hidden files as models
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Copying files from macOS to Linux would produce files starting with . _ that were incorrectly identified as model files.
2024-09-23 08:51:31 +09:00
tsukumi
245bfe54ae
Fix: In the “Merge” tab of the Web UI, re-create the TTSModelHolder using the passed TTSModelHolder instance variable so that ONNX models do not get mixed up
2024-09-23 08:13:16 +09:00
tsukumi
b7cd512978
Fix: During ONNX inference, the tensor of the return value of the tokenizer is now obtained in Numpy's NDArray format to eliminate the dependency on PyTorch
2024-09-23 07:40:17 +09:00
tsukumi
dcca37b9a8
Add: Support for speech synthesis in English and Chinese for ONNX inference in Non-JP-Extra models
2024-09-23 07:14:44 +09:00
tsukumi
db0acd7b5f
Add: Support for ONNX inference and ONNX conversion of Non-JP-Extra models
2024-09-23 05:59:12 +09:00
tsukumi
cc1d6120fe
Fix: Default value of False for compatibility with older models where the HyperParameters.data.use_jp_extra field does not exist
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JP-Extra models always have use_jp_extra=True, but non-JP-Extra models do not always.
2024-09-23 05:26:19 +09:00
tsukumi
0e0b4bea31
Fix: Disable optimization on InferenceSession initialization to speed up loading of ONNX models
2024-09-22 23:08:00 +09:00
tsukumi
291e635e9e
Improve: ONNX conversion logic improved, and support for noise_scale(_w) model argument
2024-09-22 16:14:25 +09:00
tsukumi
9b27ba9777
Improve: Graphical display of ONNX conversion script logs
2024-09-18 06:11:10 +09:00
tsukumi
449927616a
Fix: Suppress many warning logs
2024-09-18 05:48:37 +09:00
tsukumi
fa7123c422
Fix: ONNX BERT model/tokenizer is not preloaded by default to avoid wasting VRAM
2024-09-18 05:11:15 +09:00
tsukumi
327e038977
Improve: I/O binding during ONNX inference
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I honestly don't see a big difference...
2024-09-18 04:49:56 +09:00
tsukumi
7d721fdf2b
Fix: CUDAExecutionProvider was not being used to infer Style-Bert-VITS2 ONNX models even though CUDA was available
2024-09-18 04:37:23 +09:00
tsukumi
e5a05a30cb
Improve: Outputs model load time and inference time
2024-09-17 18:37:00 +09:00
tsukumi
5e2c83c6c7
Improve: Support ONNX inference, add ONNX conversion script
2024-09-17 16:55:03 +09:00
tsukumi
9de6e04ad7
Add: Preparation for ONNX inference support ④
2024-09-17 13:25:17 +09:00
tsukumi
ebd4551d1e
Add: Preparation for ONNX inference support ③
2024-09-17 09:16:16 +09:00
tsukumi
b9fdeb4492
Add: Preparation for ONNX inference support ②
2024-09-17 09:02:14 +09:00
tsukumi
eede796c4e
Add: Preparation for ONNX inference support ①
2024-09-17 06:53:11 +09:00
tsukumi
7c5e839e82
Fix: Converts the given “N” phoneme to “n” when use_jp_extra=False
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Non-JP-Extra pre-trained models (based on Bert-VITS2 v2.1) do not distinguish between “ん” and consonant “n” due to an implementation miss.
2024-09-17 05:24:16 +09:00
tsukumi
c140c0612a
Fix: Old comment
2024-09-17 05:23:57 +09:00
tsukumi
cfd6bd5bb6
Improve: Models can now be loaded directly onto NVIDIA GPUs
2024-09-17 05:23:02 +09:00
tsukumi
0e71d7ef7c
Fix: Specifying the device_map option in extract_bert_feature()
2024-09-17 05:22:30 +09:00
tsukumi
80dd6dbc22
Improve: Use the device_map option in transformers to load BERT models directly to the GPU
2024-09-17 05:22:06 +09:00
tsukumi
bdf20e8911
Refactor: Use bert_models.transfer_model()
2024-09-17 05:21:03 +09:00
tsukumi
f84d2ed48b
Add: Implement bert_models.transfer_model()
2024-09-17 05:19:44 +09:00
litagin02
38adf43924
Fix: colab torchvision bug, explicit torchaudio version
2024-09-09 15:31:30 +09:00
litagin02
048d0b6c42
Change zero_model to null_model, docs
2024-06-16 17:24:50 +09:00
litagin02
b1970aa287
Bump ver
2024-06-14 15:45:53 +09:00
litagin02
1b656b37fa
Feat: koharune-ami
2024-05-26 17:17:32 +09:00
litagin02
2274087da4
Fmt only (maybe)
2024-05-25 18:15:36 +09:00
litagin02
8976a3ed2f
Refactor: Use PathConfig and pathlib instead of paths.yml loading
2024-05-25 10:25:22 +09:00
litagin02
053a6bf785
Fix gradio Path serialize error
2024-05-19 18:31:45 +09:00
litagin02
0a3b57528b
Fix gradio import type annotation bug (temp solution)
2024-05-15 20:39:22 +09:00
litagin02
837c4397db
Merge pull request #118 from tsukumijima/dev
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音声合成時に読み上げテキストの読みを表す音素列を指定する機能を追加 + 様々な改善
2024-05-15 07:37:46 +09:00
tsukumi
44693e7d6b
Refactor: improve regular expression performance during NLP
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Improve performance by pre-compiling regular expressions that are executed many times.
2024-05-12 17:53:30 +09:00
gordon0414
7de367b76f
moved tokenizer loading inside of g2p function for code integrity.
2024-05-10 11:55:38 +09:00
gordon0414
3018309199
Optimize g2p function for improved speed and efficiency
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- Moved global variables (ARPA, _g2p, eng_dict, tokenizer) to top-level scope to avoid redundant initialization.
- Simplified conditions for words with apostrophes.
- Streamlined __post_replace_ph function by removing redundant checks.
- Optimized __refine_syllables function with direct iteration.
- Avoided re-initialization of tokenizer in __text_to_words by moving it to global scope.
- Added performance test in __main__ to validate improvements.
- Resolves issue #104 .
2024-05-09 16:12:15 +09:00
tsukumi
2d6baa3928
Fix: changed the substitute phoneme from「ん」to 「'」 when the pronunciation can't be obtained
2024-05-06 22:17:34 +09:00
