update scripts

R1ckShi

2024-06-11 0f1247d7a8d481a7b5825c903e819dc543224740

update scripts

 examples/industrial_data_pretraining/bicif_paraformer/export.py

@@ -12,17 +12,17 @@
    device="cpu",
)

res = model.export(type="onnx", quantize=False)
res = model.export(type="torchscripts", quantize=False)
print(res)


# method2, inference from local path
from funasr import AutoModel
# # method2, inference from local path
# from funasr import AutoModel

model = AutoModel(
    model="/Users/zhifu/.cache/modelscope/hub/iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
    device="cpu",
)
# model = AutoModel(
#     model="/Users/zhifu/.cache/modelscope/hub/iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
#     device="cpu",
# )

res = model.export(type="onnx", quantize=False)
print(res)
# res = model.export(type="onnx", quantize=False)
# print(res)

 funasr/utils/export_utils.py

@@ -22,6 +22,7 @@
            )
        elif type == 'torchscripts':
            device = 'cuda' if torch.cuda.is_available() else 'cpu'
            print("Exporting torchscripts on device {}".format(device))
            _torchscripts(
                m,
                path=export_dir,

 runtime/python/libtorch/funasr_torch/utils/timestamp_utils.py

@@ -7,7 +7,7 @@
    START_END_THRESHOLD = 5
    MAX_TOKEN_DURATION = 30
    TIME_RATE = 10.0 * 6 / 1000 / 3  #  3 times upsampled
    cif_peak = us_cif_peak.reshape(-1)
    cif_peak = us_cif_peak.reshape(-1).cpu()
    num_frames = cif_peak.shape[-1]
    if char_list[-1] == "</s>":
        char_list = char_list[:-1]