From e1d535e697279e3e80f15888141ebf3ec0b9179c Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期五, 05 五月 2023 11:53:39 +0800
Subject: [PATCH] update neat contextual paraformer
---
funasr/models/e2e_asr_contextual_paraformer.py | 27 +--------------------------
1 files changed, 1 insertions(+), 26 deletions(-)
diff --git a/funasr/models/e2e_asr_contextual_paraformer.py b/funasr/models/e2e_asr_contextual_paraformer.py
index aced11e..dc820db 100644
--- a/funasr/models/e2e_asr_contextual_paraformer.py
+++ b/funasr/models/e2e_asr_contextual_paraformer.py
@@ -291,7 +291,7 @@
loss_ideal = None
'''
loss_ideal = None
-
+
if decoder_out_1st is None:
decoder_out_1st = decoder_out
# 2. Compute attention loss
@@ -362,11 +362,6 @@
hw_embed = torch.nn.utils.rnn.pack_padded_sequence(hw_embed, hw_lengths, batch_first=True,
enforce_sorted=False)
_, (h_n, _) = self.bias_encoder(hw_embed)
- # hw_embed, _ = torch.nn.utils.rnn.pad_packed_sequence(hw_embed, batch_first=True)
- if h_n.shape[1] > 2000: # large hotword list
- _h_n = self.pick_hwlist_group(h_n.squeeze(0), encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens)
- if _h_n is not None:
- h_n = _h_n
hw_embed = h_n.repeat(encoder_out.shape[0], 1, 1)
decoder_outs = self.decoder(
@@ -375,23 +370,3 @@
decoder_out = decoder_outs[0]
decoder_out = torch.log_softmax(decoder_out, dim=-1)
return decoder_out, ys_pad_lens
-
- def pick_hwlist_group(self, hw_embed, encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens):
- max_attn_score = 0.0
- # max_attn_index = 0
- argmax_g = None
- non_blank = hw_embed[-1]
- hw_embed_groups = hw_embed[:-1].split(2000)
- for i, g in enumerate(hw_embed_groups):
- g = torch.cat([g, non_blank.unsqueeze(0)], dim=0)
- _ = self.decoder(
- encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens, contextual_info=g.unsqueeze(0)
- )
- attn = self.decoder.bias_decoder.src_attn.attn[0]
- _max_attn_score = attn.max(0)[0][:,:-1].max()
- if _max_attn_score > max_attn_score:
- max_attn_score = _max_attn_score
- # max_attn_index = i
- argmax_g = g
- # import pdb; pdb.set_trace()
- return argmax_g
\ No newline at end of file
--
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