From b1e980d501f0e6132c76e977a459cf07f3794c56 Mon Sep 17 00:00:00 2001
From: haoneng.lhn <haoneng.lhn@alibaba-inc.com>
Date: 星期四, 10 八月 2023 14:40:07 +0800
Subject: [PATCH] add mossformer code
---
funasr/bin/ss_inference_launch.py | 2 +-
funasr/build_utils/build_model_from_file.py | 17 ++---------------
2 files changed, 3 insertions(+), 16 deletions(-)
diff --git a/funasr/bin/ss_inference_launch.py b/funasr/bin/ss_inference_launch.py
index bab68ad..64503a0 100644
--- a/funasr/bin/ss_inference_launch.py
+++ b/funasr/bin/ss_inference_launch.py
@@ -104,7 +104,7 @@
ss_results = speech_separator(**batch)
for spk in range(num_spks):
- sf.write(os.path.join(output_path, keys[0].replace('.wav', '_s'+str(spk+1)+'.wav')), ss_results[spk], sample_rate)
+ sf.write(os.path.join(output_path, keys[0] + '_s' + str(spk+1)+'.wav'), ss_results[spk], sample_rate)
torch.cuda.empty_cache()
return ss_results
diff --git a/funasr/build_utils/build_model_from_file.py b/funasr/build_utils/build_model_from_file.py
index 6130e71..65e0d5f 100644
--- a/funasr/build_utils/build_model_from_file.py
+++ b/funasr/build_utils/build_model_from_file.py
@@ -11,18 +11,6 @@
from funasr.models.base_model import FunASRModel
-def load_checkpoint(checkpoint_path, use_cuda=1):
- if use_cuda:
- checkpoint = torch.load(checkpoint_path)
- else:
- checkpoint = torch.load(
- checkpoint_path, map_location=lambda storage, loc: storage)
- return checkpoint
-
-def reload_ss_for_eval(model, checkpoint_path, use_cuda=False):
- checkpoint = load_checkpoint(checkpoint_path, use_cuda)
- model.load_state_dict(checkpoint['model'], strict=False)
-
def build_model_from_file(
config_file: Union[Path, str] = None,
model_file: Union[Path, str] = None,
@@ -82,9 +70,8 @@
model.load_state_dict(model_dict)
else:
model_dict = torch.load(model_file, map_location=device)
- if task_name == 'ss':
- reload_ss_for_eval(model, model_file, use_cuda=True)
- logging.info("model is loaded from path: {}".format(model_file))
+ if task_name == "ss":
+ model_dict = model_dict['model']
if task_name == "diar" and mode == "sond":
model_dict = fileter_model_dict(model_dict, model.state_dict())
if task_name == "vad":
--
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