禾息 commited on
Commit
18599be
1 Parent(s): 2940836

mirror modify

Browse files
cosyvoice/bin/export_trt.py CHANGED
@@ -1,3 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  import argparse
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  import logging
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  import os
 
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+ # Copyright (c) 2024 Antgroup Inc (authors: Zhoubofan, [email protected])
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+
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  import argparse
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  import logging
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  import os
cosyvoice/cli/model.py CHANGED
@@ -20,11 +20,6 @@ from contextlib import nullcontext
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  import uuid
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  from cosyvoice.utils.common import fade_in_out
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- try:
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- import tensorrt as trt
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- except ImportError:
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- ...
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-
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  class CosyVoiceModel:
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  def __init__(self,
@@ -72,6 +67,7 @@ class CosyVoiceModel:
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  self.llm.llm = llm_llm
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  def load_trt(self, model_dir, use_fp16):
 
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  trt_file_name = 'estimator_fp16.plan' if use_fp16 else 'estimator_fp32.plan'
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  trt_file_path = os.path.join(model_dir, trt_file_name)
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  if not os.path.isfile(trt_file_path):
 
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  import uuid
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  from cosyvoice.utils.common import fade_in_out
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  class CosyVoiceModel:
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  def __init__(self,
 
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  self.llm.llm = llm_llm
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  def load_trt(self, model_dir, use_fp16):
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+ import tensorrt as trt
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  trt_file_name = 'estimator_fp16.plan' if use_fp16 else 'estimator_fp32.plan'
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  trt_file_path = os.path.join(model_dir, trt_file_name)
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  if not os.path.isfile(trt_file_path):
cosyvoice/flow/flow_matching.py CHANGED
@@ -102,7 +102,6 @@ class ConditionalCFM(BASECFM):
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  if self.estimator is not None:
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  return self.estimator.forward(x, mask, mu, t, spks, cond)
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  else:
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- print("-----------")
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  assert self.training is False, 'tensorrt cannot be used in training'
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  bs = x.shape[0]
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  hs = x.shape[1]
 
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  if self.estimator is not None:
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  return self.estimator.forward(x, mask, mu, t, spks, cond)
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  else:
 
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  assert self.training is False, 'tensorrt cannot be used in training'
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  bs = x.shape[0]
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  hs = x.shape[1]