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| | | from funasr.runtime.python.libtorch.funasr_torch import Paraformer |
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| | | if args.backend == "onnx": |
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| | | from funasr.runtime.python.onnxruntime.funasr_onnx import Paraformer |
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| | | |
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| | | from funasr.runtime.python.onnxruntime.funasr_onnx import Paraformer |
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| | | |
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| | | model = Paraformer(args.model_dir, batch_size=args.batch_size, quantize=args.quantize, intra_op_num_threads=args.intra_op_num_threads) |
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| | | |
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| | | wav_file_f = open(args.wav_file, 'r') |
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| | |
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| | | num = 30 |
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| | | wav_path = wav_files[0].split("\t")[1].strip() if "\t" in wav_files[0] else wav_files[0].split(" ")[1].strip() |
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| | | for i in range(num): |
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| | | beg_time = time.time() |
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| | | result = model(wav_path) |
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| | | end_time = time.time() |
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| | | duration = end_time-beg_time |
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| | | total += duration |
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| | | print(result) |
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| | | print("num: {}, time, {}, avg: {}, rtf: {}".format(len(wav_path), duration, total/(i+1), (total/(i+1))/5.53)) |
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| | | beg_time = time.time() |
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| | | result = model(wav_path) |
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| | | end_time = time.time() |
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| | | duration = end_time-beg_time |
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| | | total += duration |
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| | | print(result) |
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| | | print("num: {}, time, {}, avg: {}, rtf: {}".format(len(wav_path), duration, total/(i+1), (total/(i+1))/5.53)) |
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| | | |
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| | | # infer time |
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| | | wav_path = [] |
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| | | beg_time = time.time() |
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| | | for i, wav_path_i in enumerate(wav_files): |
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| | | wav_path_i = wav_path_i.split("\t")[1].strip() if "\t" in wav_path_i else wav_path_i.split(" ")[1].strip() |
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| | | wav_path += [wav_path_i] |
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| | | wav_path_i = wav_path_i.split("\t")[1].strip() if "\t" in wav_path_i else wav_path_i.split(" ")[1].strip() |
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| | | wav_path += [wav_path_i] |
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| | | result = model(wav_path) |
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| | | end_time = time.time() |
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| | | duration = (end_time-beg_time)*1000 |
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| | | |
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| | | duration_time = 0.0 |
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| | | for i, wav_path_i in enumerate(wav_files): |
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| | | wav_path = wav_path_i.split("\t")[1].strip() if "\t" in wav_path_i else wav_path_i.split(" ")[1].strip() |
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| | | waveform, _ = librosa.load(wav_path, sr=16000) |
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| | | duration_time += len(waveform)/16.0 |
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| | | wav_path = wav_path_i.split("\t")[1].strip() if "\t" in wav_path_i else wav_path_i.split(" ")[1].strip() |
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| | | waveform, _ = librosa.load(wav_path, sr=16000) |
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| | | duration_time += len(waveform)/16.0 |
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| | | print("total_time_wav_ms: {}".format(int(duration_time))) |
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| | | |
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| | | print("total_rtf: {:.5}".format(duration/duration_time)) |
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