| | |
|---|
| | | if cache["cif_alphas"] is not None:
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|---|
| | | alphas = torch.cat((cache["cif_alphas"], alphas), -1)
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|---|
| | |
|
|---|
| | | #if cache["is_final"]:
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|---|
| | | # tail_threshold = torch.tensor([self.tail_threshold], dtype=alphas.dtype).to(alphas.device)
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|---|
| | | # tail_threshold = torch.reshape(tail_threshold, (1, 1))
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|---|
| | | # alphas = torch.cat([alphas, tail_threshold], dim=1)
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|---|
| | | # zeros_hidden = torch.zeros((b, 1, d), dtype=hidden.dtype).to(hidden.device)
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|---|
| | | # hidden = torch.cat([hidden, zeros_hidden], dim=1)
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|---|
| | |
|
|---|
| | | token_num = alphas.sum(-1)
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|---|
| | | acoustic_embeds, cif_peak = cif(hidden, alphas, self.threshold)
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|---|
| | | len_time = alphas.size(-1)
|
|---|
