vad

funasr/runtime/python/utils/test_rtf_gpu.py

@@ -0,0 +1,58 @@
+
+import time
+import sys
+import librosa
+from funasr.utils.types import str2bool
+
+import argparse
+parser = argparse.ArgumentParser()
+parser.add_argument('--model_dir', type=str, required=True)
+parser.add_argument('--backend', type=str, default='onnx', help='["onnx", "torch"]')
+parser.add_argument('--wav_file', type=str, default=None, help='amp fallback number')
+parser.add_argument('--quantize', type=str2bool, default=False, help='quantized model')
+parser.add_argument('--intra_op_num_threads', type=int, default=1, help='intra_op_num_threads for onnx')
+parser.add_argument('--batch_size', type=int, default=1, help='batch_size for onnx')
+args = parser.parse_args()
+
+
+from funasr.runtime.python.libtorch.funasr_torch import Paraformer
+if args.backend == "onnx":
+	from funasr.runtime.python.onnxruntime.funasr_onnx import Paraformer
+	
+model = Paraformer(args.model_dir, batch_size=args.batch_size, quantize=args.quantize, intra_op_num_threads=args.intra_op_num_threads)
+
+wav_file_f = open(args.wav_file, 'r')
+wav_files = wav_file_f.readlines()
+
+# warm-up
+total = 0.0
+num = 30
+wav_path = wav_files[0].split("\t")[1].strip() if "\t" in wav_files[0] else wav_files[0].split(" ")[1].strip()
+for i in range(num):
+	beg_time = time.time()
+	result = model(wav_path)
+	end_time = time.time()
+	duration = end_time-beg_time
+	total += duration
+	print(result)
+	print("num: {}, time, {}, avg: {}, rtf: {}".format(len(wav_path), duration, total/(i+1), (total/(i+1))/5.53))
+
+# infer time
+wav_path = []
+beg_time = time.time()
+for i, wav_path_i in enumerate(wav_files):
+	wav_path_i = wav_path_i.split("\t")[1].strip() if "\t" in wav_path_i else wav_path_i.split(" ")[1].strip()
+	wav_path += [wav_path_i]
+result = model(wav_path)
+end_time = time.time()
+duration = (end_time-beg_time)*1000
+print("total_time_comput_ms: {}".format(int(duration)))
+
+duration_time = 0.0
+for i, wav_path_i in enumerate(wav_files):
+	wav_path = wav_path_i.split("\t")[1].strip() if "\t" in wav_path_i else wav_path_i.split(" ")[1].strip()
+	waveform, _ = librosa.load(wav_path, sr=16000)
+	duration_time += len(waveform)/16.0
+print("total_time_wav_ms: {}".format(int(duration_time)))
+
+print("total_rtf: {:.5}".format(duration/duration_time))

funasr/tasks/vad.py

@@ -319,8 +319,8 @@ class VADTask(AbsTask):
             cls,
             config_file: Union[Path, str] = None,
             model_file: Union[Path, str] = None,
-            cmvn_file: Union[Path, str] = None,
             device: str = "cpu",
+            cmvn_file: Union[Path, str] = None,
     ):
         """Build model from the files.