| | |
|---|
| | | from funasr.models.transformer.utils.subsampling import Conv2dSubsamplingPad |
|---|
| | | from funasr.models.transformer.utils.subsampling import StreamingConvInput |
|---|
| | | from funasr.register import tables |
|---|
| | | |
|---|
| | | import pdb |
|---|
| | | |
|---|
| | | class ConvolutionModule(nn.Module): |
|---|
| | | """ConvolutionModule in Conformer model. |
|---|
| | |
|---|
| | | xs_pad, masks = self.embed(xs_pad, masks) |
|---|
| | | else: |
|---|
| | | xs_pad = self.embed(xs_pad) |
|---|
| | | |
|---|
| | | pdb.set_trace() |
|---|
| | | intermediate_outs = [] |
|---|
| | | if len(self.interctc_layer_idx) == 0: |
|---|
| | | xs_pad, masks = self.encoders(xs_pad, masks) |
|---|
| | |
|---|
| | | xs_pad = (x, pos_emb) |
|---|
| | | else: |
|---|
| | | xs_pad = xs_pad + self.conditioning_layer(ctc_out) |
|---|
| | | |
|---|
| | | pdb.set_trace() |
|---|
| | | if isinstance(xs_pad, tuple): |
|---|
| | | xs_pad = xs_pad[0] |
|---|
| | | if self.normalize_before: |
|---|
| | | xs_pad = self.after_norm(xs_pad) |
|---|
| | | |
|---|
| | | pdb.set_trace() |
|---|
| | | olens = masks.squeeze(1).sum(1) |
|---|
| | | if len(intermediate_outs) > 0: |
|---|
| | | return (xs_pad, intermediate_outs), olens, None |
|---|
