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游雁 2023-04-21 17:13:39 +08:00
parent 289e62ef4a
commit 41b5d06e51
1 changed files with 0 additions and 29 deletions
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egs/aishell/transformer/utils/prepare_checkpoint.py
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@ -5,35 +5,6 @@ from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.hub.snapshot_download import snapshot_download
def modelscope_infer_after_finetune(params):
# prepare for decoding
try:
pretrained_model_path = snapshot_download(params["modelscope_model_name"], cache_dir=params["output_dir"])
except BaseException:
raise BaseException(f"Please download pretrain model from ModelScope firstly.")
shutil.copy(os.path.join(params["output_dir"], params["decoding_model_name"]), os.path.join(pretrained_model_path, "model.pb"))
decoding_path = os.path.join(params["output_dir"], "decode_results")
if os.path.exists(decoding_path):
shutil.rmtree(decoding_path)
os.mkdir(decoding_path)
# decoding
inference_pipeline = pipeline(
task=Tasks.auto_speech_recognition,
model=pretrained_model_path,
output_dir=decoding_path,
batch_size=params["batch_size"]
)
audio_in = os.path.join(params["data_dir"], "wav.scp")
inference_pipeline(audio_in=audio_in)
# computer CER if GT text is set
text_in = os.path.join(params["data_dir"], "text")
if os.path.exists(text_in):
text_proc_file = os.path.join(decoding_path, "1best_recog/text")
compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))
if __name__ == '__main__':
import sys