| New file |
| | |
| | | import onnxruntime |
| | | import numpy as np |
| | | |
| | | |
| | | if __name__ == '__main__': |
| | | onnx_path = "/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/torchscripts/model.onnx" |
| | | sess = onnxruntime.InferenceSession(onnx_path) |
| | | input_name = [nd.name for nd in sess.get_inputs()] |
| | | output_name = [nd.name for nd in sess.get_outputs()] |
| | | |
| | | def _get_feed_dict(feats_length): |
| | | return {'speech': np.zeros((1, feats_length, 560), dtype=np.float32), 'speech_lengths': [feats_length,]} |
| | | |
| | | def _run(feed_dict): |
| | | output = sess.run(output_name, input_feed=feed_dict) |
| | | for name, value in zip(output_name, output): |
| | | print('{}: {}'.format(name, value.shape)) |
| | | |
| | | _run(_get_feed_dict(100)) |
| | | _run(_get_feed_dict(200)) |