| | |
| | | from funasr.layers.label_aggregation import LabelAggregate |
| | | from funasr.models.ctc import CTC |
| | | from funasr.models.encoder.resnet34_encoder import ResNet34Diar |
| | | from funasr.models.encoder.ecapa_tdnn_encoder import ECAPA_TDNN |
| | | from funasr.models.encoder.opennmt_encoders.conv_encoder import ConvEncoder |
| | | from funasr.models.encoder.opennmt_encoders.fsmn_encoder import FsmnEncoder |
| | | from funasr.models.encoder.opennmt_encoders.self_attention_encoder import SelfAttentionEncoder |
| | |
| | | resnet34=ResNet34Diar, |
| | | sanm_chunk_opt=SANMEncoderChunkOpt, |
| | | data2vec_encoder=Data2VecEncoder, |
| | | epaca_dtnn=ECAPA_TDNN, |
| | | ), |
| | | type_check=AbsEncoder, |
| | | default="resnet34", |
| | |
| | | cls, train: bool = True, inference: bool = False |
| | | ) -> Tuple[str, ...]: |
| | | if not inference: |
| | | retval = ("speech", "profile", "label") |
| | | retval = ("speech", "profile", "binary_labels") |
| | | else: |
| | | # Recognition mode |
| | | retval = ("speech", "profile") |