# Copyright 2022-2023 Xiaomi Corp. (authors: Fangjun Kuang) # # See LICENSE for clarification regarding multiple authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from functools import lru_cache import sherpa_onnx from huggingface_hub import hf_hub_download def get_file( repo_id: str, filename: str, subfolder: str = ".", ) -> str: model_filename = hf_hub_download( repo_id=repo_id, filename=filename, subfolder=subfolder, ) return model_filename @lru_cache(maxsize=10) def _get_vits_vctk(repo_id: str, speed: float) -> sherpa_onnx.OfflineTts: assert repo_id == "csukuangfj/vits-vctk" model = get_file( repo_id=repo_id, filename="vits-vctk.onnx", subfolder=".", ) lexicon = get_file( repo_id=repo_id, filename="lexicon.txt", subfolder=".", ) tokens = get_file( repo_id=repo_id, filename="tokens.txt", subfolder=".", ) tts_config = sherpa_onnx.OfflineTtsConfig( model=sherpa_onnx.OfflineTtsModelConfig( vits=sherpa_onnx.OfflineTtsVitsModelConfig( model=model, lexicon=lexicon, tokens=tokens, length_scale=1.0 / speed, ), provider="cpu", debug=True, num_threads=2, ) ) tts = sherpa_onnx.OfflineTts(tts_config) return tts @lru_cache(maxsize=10) def _get_vits_ljs(repo_id: str, speed: float) -> sherpa_onnx.OfflineTts: assert repo_id == "csukuangfj/vits-ljs" model = get_file( repo_id=repo_id, filename="vits-ljs.onnx", subfolder=".", ) lexicon = get_file( repo_id=repo_id, filename="lexicon.txt", subfolder=".", ) tokens = get_file( repo_id=repo_id, filename="tokens.txt", subfolder=".", ) tts_config = sherpa_onnx.OfflineTtsConfig( model=sherpa_onnx.OfflineTtsModelConfig( vits=sherpa_onnx.OfflineTtsVitsModelConfig( model=model, lexicon=lexicon, tokens=tokens, length_scale=1.0 / speed, ), provider="cpu", debug=True, num_threads=2, ) ) tts = sherpa_onnx.OfflineTts(tts_config) return tts @lru_cache(maxsize=10) def _get_vits_piper(repo_id: str, speed: float) -> sherpa_onnx.OfflineTts: data_dir = "/tmp/espeak-ng-data" if "coqui" in repo_id or "vits-mms" in repo_id: name = "model" elif "piper" in repo_id: n = len("vits-piper-") name = repo_id.split("/")[1][n:] elif "mimic3" in repo_id: n = len("vits-mimic3-") name = repo_id.split("/")[1][n:] else: raise ValueError(f"Unsupported {repo_id}") if "vits-coqui-uk-mai" in repo_id or "vits-mms" in repo_id: data_dir = "" model = get_file( repo_id=repo_id, filename=f"{name}.onnx", subfolder=".", ) tokens = get_file( repo_id=repo_id, filename="tokens.txt", subfolder=".", ) tts_config = sherpa_onnx.OfflineTtsConfig( model=sherpa_onnx.OfflineTtsModelConfig( vits=sherpa_onnx.OfflineTtsVitsModelConfig( model=model, lexicon="", data_dir=data_dir, tokens=tokens, length_scale=1.0 / speed, ), provider="cpu", debug=True, num_threads=2, ) ) tts = sherpa_onnx.OfflineTts(tts_config) return tts @lru_cache(maxsize=10) def _get_vits_mms(repo_id: str, speed: float) -> sherpa_onnx.OfflineTts: return _get_vits_piper(repo_id, speed) @lru_cache(maxsize=10) def _get_vits_zh_aishell3(repo_id: str, speed: float) -> sherpa_onnx.OfflineTts: assert repo_id == "csukuangfj/vits-zh-aishell3" model = get_file( repo_id=repo_id, filename="vits-aishell3.onnx", subfolder=".", ) lexicon = get_file( repo_id=repo_id, filename="lexicon.txt", subfolder=".", ) tokens = get_file( repo_id=repo_id, filename="tokens.txt", subfolder=".", ) rule_fst = get_file( repo_id=repo_id, filename="rule.fst", subfolder=".", ) tts_config = sherpa_onnx.OfflineTtsConfig( model=sherpa_onnx.OfflineTtsModelConfig( vits=sherpa_onnx.OfflineTtsVitsModelConfig( model=model, lexicon=lexicon, tokens=tokens, length_scale=1.0 / speed, ), provider="cpu", debug=True, num_threads=2, ), rule_fsts=rule_fst, ) tts = sherpa_onnx.OfflineTts(tts_config) return tts @lru_cache(maxsize=10) def _get_vits_hf(repo_id: str, speed: float) -> sherpa_onnx.OfflineTts: if "fanchen" in repo_id or "vits-cantonese-hf-xiaomaiiwn" in repo_id: model = repo_id.split("/")[-1] else: model = repo_id.split("-")[-1] model = get_file( repo_id=repo_id, filename=f"{model}.onnx", subfolder=".", ) lexicon = get_file( repo_id=repo_id, filename="lexicon.txt", subfolder=".", ) tokens = get_file( repo_id=repo_id, filename="tokens.txt", subfolder=".", ) rule_fst = get_file( repo_id=repo_id, filename="rule.fst", subfolder=".", ) tts_config = sherpa_onnx.OfflineTtsConfig( model=sherpa_onnx.OfflineTtsModelConfig( vits=sherpa_onnx.OfflineTtsVitsModelConfig( model=model, lexicon=lexicon, tokens=tokens, length_scale=1.0 / speed, ), provider="cpu", debug=True, num_threads=2, ), rule_fsts=rule_fst, ) tts = sherpa_onnx.OfflineTts(tts_config) return tts @lru_cache(maxsize=10) def get_pretrained_model(repo_id: str, speed: float) -> sherpa_onnx.OfflineTts: if repo_id in spanish_models: return spanish_models[repo_id](repo_id, speed) else: raise ValueError(f"Unsupported repo_id: {repo_id}") spanish_models = { "csukuangfj/vits-piper-es_ES-sharvard-medium": _get_vits_piper, # 2 speakers } language_to_models = { "Spanish": list(spanish_models.keys()), }