From 85cabd30a9185cf5bebde4a6415a122142ea3b43 Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 11 十二月 2023 10:10:54 +0800
Subject: [PATCH] update with main (#1163)

---
 funasr/models/e2e_asr.py                       |    3 ++-
 funasr/models/e2e_asr_paraformer.py            |   15 ++++++++++-----
 funasr/models/e2e_asr_contextual_paraformer.py |    3 ++-
 funasr/models/e2e_uni_asr.py                   |    3 ++-
 4 files changed, 16 insertions(+), 8 deletions(-)

diff --git a/funasr/models/e2e_asr.py b/funasr/models/e2e_asr.py
index 162bfba..c1eb003 100644
--- a/funasr/models/e2e_asr.py
+++ b/funasr/models/e2e_asr.py
@@ -222,7 +222,8 @@
 
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + 1).sum().type_as(batch_size)
+            batch_size = int((text_lengths + 1).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
 
diff --git a/funasr/models/e2e_asr_contextual_paraformer.py b/funasr/models/e2e_asr_contextual_paraformer.py
index d4dc784..598d5ac 100644
--- a/funasr/models/e2e_asr_contextual_paraformer.py
+++ b/funasr/models/e2e_asr_contextual_paraformer.py
@@ -233,7 +233,8 @@
         stats["loss"] = torch.clone(loss.detach())
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + self.predictor_bias).sum().type_as(batch_size)
+            batch_size = int((text_lengths + self.predictor_bias).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
     
diff --git a/funasr/models/e2e_asr_paraformer.py b/funasr/models/e2e_asr_paraformer.py
index b793d52..6b1d824 100644
--- a/funasr/models/e2e_asr_paraformer.py
+++ b/funasr/models/e2e_asr_paraformer.py
@@ -255,7 +255,8 @@
 
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + self.predictor_bias).sum().type_as(batch_size)
+            batch_size = int((text_lengths + self.predictor_bias).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
 
@@ -867,7 +868,8 @@
 
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + self.predictor_bias).sum().type_as(batch_size)
+            batch_size = int((text_lengths + self.predictor_bias).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
 
@@ -1494,7 +1496,8 @@
 
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + self.predictor_bias).sum().type_as(batch_size)
+            batch_size = int((text_lengths + self.predictor_bias).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
 
@@ -1765,7 +1768,8 @@
 
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + self.predictor_bias).sum().type_as(batch_size)
+            batch_size = int((text_lengths + self.predictor_bias).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
 
@@ -1967,7 +1971,8 @@
 
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + self.predictor_bias).sum().type_as(batch_size)
+            batch_size = int((text_lengths + self.predictor_bias).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
 
diff --git a/funasr/models/e2e_uni_asr.py b/funasr/models/e2e_uni_asr.py
index 45d90f1..07ebd81 100644
--- a/funasr/models/e2e_uni_asr.py
+++ b/funasr/models/e2e_uni_asr.py
@@ -442,7 +442,8 @@
         stats["loss"] = torch.clone(loss.detach())
         # force_gatherable: to-device and to-tensor if scalar for DataParallel
         if self.length_normalized_loss:
-            batch_size = (text_lengths + 1).sum().type_as(batch_size)
+            batch_size = int((text_lengths + 1).sum())
+
         loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
         return loss, stats, weight
 

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