From c73d1a8e81582b91a9bdd6e82fce2e84f8d9d94b Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期一, 14 八月 2023 19:31:55 +0800
Subject: [PATCH] update func cif_wo_hidden

---
 funasr/export/models/predictor/cif.py |    2 +-
 funasr/utils/timestamp_tools.py       |    2 +-
 funasr/models/predictor/cif.py        |    2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/funasr/export/models/predictor/cif.py b/funasr/export/models/predictor/cif.py
index dd5dd36..03c4433 100644
--- a/funasr/export/models/predictor/cif.py
+++ b/funasr/export/models/predictor/cif.py
@@ -288,7 +288,7 @@
 
         fire_place = integrate >= threshold
         integrate = torch.where(fire_place,
-                                integrate - torch.ones([batch_size], device=alphas.device),
+                                integrate - torch.ones([batch_size], device=alphas.device)*threshold,
                                 integrate)
 
     fires = torch.stack(list_fires, 1)
diff --git a/funasr/models/predictor/cif.py b/funasr/models/predictor/cif.py
index c66af94..5f18c4d 100644
--- a/funasr/models/predictor/cif.py
+++ b/funasr/models/predictor/cif.py
@@ -499,7 +499,7 @@
 
         fire_place = integrate >= threshold
         integrate = torch.where(fire_place,
-                                integrate - torch.ones([batch_size], device=alphas.device),
+                                integrate - torch.ones([batch_size], device=alphas.device)*threshold,
                                 integrate)
 
     fires = torch.stack(list_fires, 1)
diff --git a/funasr/utils/timestamp_tools.py b/funasr/utils/timestamp_tools.py
index c194179..6594273 100644
--- a/funasr/utils/timestamp_tools.py
+++ b/funasr/utils/timestamp_tools.py
@@ -19,7 +19,7 @@
         list_fires.append(integrate)
         fire_place = integrate >= threshold
         integrate = torch.where(fire_place,
-                                integrate - torch.ones([batch_size], device=alphas.device),
+                                integrate - torch.ones([batch_size], device=alphas.device)*threshold,
                                 integrate)
     fires = torch.stack(list_fires, 1)
     return fires

--
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