mirror of
https://github.com/FunAudioLLM/CosyVoice.git
synced 2026-02-04 17:39:25 +08:00
add train cfg in flow matching
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@@ -131,8 +131,10 @@ you can run following steps. Otherwise, you can just ignore this step.
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cd runtime/python
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docker build -t cosyvoice:v1.0 .
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# change iic/CosyVoice-300M to iic/CosyVoice-300M-Instruct if you want to use instruct inference
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docker run -d --runtime=nvidia -p 50000:50000 cosyvoice:v1.0 /bin/bash -c "cd /opt/CosyVoice/CosyVoice/runtime/python && python3 server.py --port 50000 --max_conc 4 --model_dir iic/CosyVoice-300M && sleep infinity"
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python3 client.py --port 50000 --mode <sft|zero_shot|cross_lingual|instruct>
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# for grpc usage
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docker run -d --runtime=nvidia -p 50000:50000 cosyvoice:v1.0 /bin/bash -c "cd /opt/CosyVoice/CosyVoice/runtime/python/grpc && python3 server.py --port 50000 --max_conc 4 --model_dir iic/CosyVoice-300M && sleep infinity"
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python3 grpc/client.py --port 50000 --mode <sft|zero_shot|cross_lingual|instruct>
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# for fastapi usage
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```
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## Discussion & Communication
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@@ -126,6 +126,13 @@ class ConditionalCFM(BASECFM):
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y = (1 - (1 - self.sigma_min) * t) * z + t * x1
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u = x1 - (1 - self.sigma_min) * z
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# during training, we randomly drop condition to trade off mode coverage and sample fidelity
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if self.training_cfg_rate > 0:
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cfg_mask = torch.rand(b, device=x1.device) > self.training_cfg_rate
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mu = mu * cfg_mask.view(-1, 1, 1)
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spks = spks * cfg_mask.view(-1, 1)
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cond = cond * cfg_mask.view(-1, 1, 1)
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pred = self.estimator(y, mask, mu, t.squeeze(), spks, cond)
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loss = F.mse_loss(pred * mask, u * mask, reduction="sum") / (torch.sum(mask) * u.shape[1])
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return loss, y
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@@ -10,5 +10,4 @@ RUN git lfs install
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RUN git clone --recursive https://github.com/FunAudioLLM/CosyVoice.git
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# here we use python==3.10 because we cannot find an image which have both python3.8 and torch2.0.1-cu118 installed
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RUN cd CosyVoice && pip3 install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com
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RUN cd CosyVoice/runtime/python && python3 -m grpc_tools.protoc -I. --python_out=. --grpc_python_out=. cosyvoice.proto
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CMD ["/bin/bash", "-c", "cd /opt/CosyVoice/CosyVoice/runtime/python && python3 server.py --port 50000 --max_conc 4 --model_dir iic/CosyVoice-300M && sleep infinity"]
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RUN cd CosyVoice/runtime/python/grpc && python3 -m grpc_tools.protoc -I. --python_out=. --grpc_python_out=. cosyvoice.proto
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@@ -14,8 +14,8 @@
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import os
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import sys
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ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
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sys.path.append('{}/../..'.format(ROOT_DIR))
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sys.path.append('{}/../../third_party/Matcha-TTS'.format(ROOT_DIR))
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sys.path.append('{}/../../..'.format(ROOT_DIR))
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sys.path.append('{}/../../../third_party/Matcha-TTS'.format(ROOT_DIR))
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import logging
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import argparse
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import torchaudio
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@@ -90,7 +90,7 @@ if __name__ == "__main__":
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default='希望你以后能够做的比我还好呦。')
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parser.add_argument('--prompt_wav',
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type=str,
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default='../../zero_shot_prompt.wav')
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default='../../../zero_shot_prompt.wav')
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parser.add_argument('--instruct_text',
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type=str,
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default='Theo \'Crimson\', is a fiery, passionate rebel leader. Fights with fervor for justice, but struggles with impulsiveness.')
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@@ -14,8 +14,8 @@
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import os
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import sys
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ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
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sys.path.append('{}/../..'.format(ROOT_DIR))
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sys.path.append('{}/../../third_party/Matcha-TTS'.format(ROOT_DIR))
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sys.path.append('{}/../../..'.format(ROOT_DIR))
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sys.path.append('{}/../../../third_party/Matcha-TTS'.format(ROOT_DIR))
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from concurrent import futures
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import argparse
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import cosyvoice_pb2
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@@ -77,7 +77,6 @@ if __name__ == '__main__':
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default=4)
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parser.add_argument('--model_dir',
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type=str,
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required=True,
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default='iic/CosyVoice-300M',
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help='local path or modelscope repo id')
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args = parser.parse_args()
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