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| import torch
| import numpy as np
|
| if __name__ == '__main__':
| onnx_path = "/mnt/workspace/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/model.torchscripts"
| loaded = torch.jit.load(onnx_path)
|
| x = torch.rand([2, 21, 560])
| x_len = torch.IntTensor([6, 21])
| res = loaded(x, x_len)
| print(res[0].size(), res[1])
|
| x = torch.rand([5, 50, 560])
| x_len = torch.IntTensor([6, 21, 10, 30, 50])
| res = loaded(x, x_len)
| print(res[0].size(), res[1])
|
|
|
