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# 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()),
}
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