| | |
| | | |
| | | return x, mask |
| | | |
| | | |
| | | @tables.register("encoder_classes", "SANMEncoderChunkOptExport") |
| | | @tables.register("encoder_classes", "SANMEncoderExport") |
| | | class SANMEncoderExport(nn.Module): |
| | | def __init__( |
| | |
| | | self.feats_dim = feats_dim |
| | | self._output_size = model._output_size |
| | | |
| | | from funasr.utils.torch_function import MakePadMask |
| | | |
| | | from funasr.utils.torch_function import sequence_mask |
| | | |
| | | if onnx: |
| | | self.make_pad_mask = MakePadMask(max_seq_len, flip=False) |
| | | else: |
| | | self.make_pad_mask = sequence_mask(max_seq_len, flip=False) |
| | | |
| | | |
| | | self.make_pad_mask = sequence_mask(max_seq_len, flip=False) |
| | | |
| | | from funasr.models.sanm.attention import MultiHeadedAttentionSANMExport |
| | | if hasattr(model, 'encoders0'): |