tsukumi
08c439e88e
Refactor: Use I/O Binding during BERT inference and always release memory after inference
2024-12-22 06:49:43 +09:00
tsukumi
7793e9da43
Remove: Unused import
2024-09-28 13:50:10 +09:00
tsukumi
c792bf9a0d
Improve: Make ONNX inference tests more rigorous
2024-09-23 12:27:29 +09:00
tsukumi
5ca6e184d7
Fix: ONNX inference of BERT models fails in some Windows environments
2024-09-23 11:33:17 +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
0e71d7ef7c
Fix: Specifying the device_map option in extract_bert_feature()
2024-09-17 05:22:30 +09:00
tsukumi
bdf20e8911
Refactor: Use bert_models.transfer_model()
2024-09-17 05:21:03 +09:00
tsukumi
9c233630ef
Refactor: don't keep models in bert_feature module for each language
...
BERT models and tokenizers are already stored and managed in the bert_models module and should not be stored here.
In addition, since there may be situations where the user would like to use cpu instead of mps for inference when using it as a library, the automatic switching process to mps was removed.
2024-03-10 14:18:57 +00:00
tsukumi
e2daa55000
Refactor: split style_bert_vits2.nlp.english package
2024-03-08 08:43:54 +00:00
tsukumi
fac4f9a8ab
Refactor: rename text_processing to nlp
...
"text_processing" is clearer, but the import statement is longer.
"nlp" is shorter and makes it clear that it is natural language processing.
2024-03-08 06:20:44 +00:00
