Remove loss_fn name

tensorlayer · May 19, 2022 · 74eb09a · 74eb09a
1 parent e1d0a8e
commit 74eb09a
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Showing 3 changed files with 6 additions and 6 deletions.
diff --git a/setup.py b/setup.py
@@ -20,7 +20,7 @@
 
 MAJOR = 0
 MINOR = 5
-PATCH = 2
+PATCH = 3
 PRE_RELEASE = ''
 # Use the following formatting: (major, minor, patch, prerelease)
 VERSION = (MAJOR, MINOR, PATCH, PRE_RELEASE)

diff --git a/tensorlayerx/model/core.py b/tensorlayerx/model/core.py
@@ -307,7 +307,7 @@ def tf_train(
                     val_loss, val_acc, n_iter = 0, 0, 0
                     for X_batch, y_batch in test_dataset:
                         _logits = network(X_batch)  # is_train=False, disable dropout
-                        val_loss += loss_fn(_logits, y_batch, name='eval_loss')
+                        val_loss += loss_fn(_logits, y_batch)
                         if metrics:
                             metrics.update(_logits, y_batch)
                             val_acc += metrics.result()
@@ -360,7 +360,7 @@ def ms_train(
                     val_loss, val_acc, n_iter = 0, 0, 0
                     for X_batch, y_batch in test_dataset:
                         _logits = network(X_batch)
-                        val_loss += loss_fn(_logits, y_batch, name='eval_loss')
+                        val_loss += loss_fn(_logits, y_batch)
                         if metrics:
                             metrics.update(_logits, y_batch)
                             val_acc += metrics.result()
@@ -414,7 +414,7 @@ def pd_train(
                     val_loss, val_acc, n_iter = 0, 0, 0
                     for X_batch, y_batch in test_dataset:
                         _logits = network(X_batch)  # is_train=False, disable dropout
-                        val_loss += loss_fn(_logits, y_batch, name='eval_loss')
+                        val_loss += loss_fn(_logits, y_batch)
                         if metrics:
                             metrics.update(_logits, y_batch)
                             val_acc += metrics.result()
@@ -468,7 +468,7 @@ def th_train(
                     val_loss, val_acc, n_iter = 0, 0, 0
                     for X_batch, y_batch in test_dataset:
                         _logits = network(X_batch)  # is_train=False, disable dropout
-                        val_loss += loss_fn(_logits, y_batch, name='eval_loss')
+                        val_loss += loss_fn(_logits, y_batch)
                         if metrics:
                             metrics.update(_logits, y_batch)
                             val_acc += metrics.result()

diff --git a/tensorlayerx/package_info.py b/tensorlayerx/package_info.py
@@ -4,7 +4,7 @@
 
 MAJOR = 0
 MINOR = 5
-PATCH = 2
+PATCH = 3
 PRE_RELEASE = ''
 # Use the following formatting: (major, minor, patch, prerelease)
 VERSION = (MAJOR, MINOR, PATCH, PRE_RELEASE)