Fix warnings

Author: fchollet

keras/src/callbacks/model_checkpoint.py

@@ -248,11 +248,10 @@ def _should_save_model(self, epoch, batch, logs, filepath):
             current = logs.get(self.monitor)
             if current is None:
                 warnings.warn(
-                    f"Can save best model only with {self.monitor} "
-                    "available, skipping.",
+                    f"Can save best model only with {self.monitor} available.",
                     stacklevel=2,
                 )
-                return False
+                return True
             elif (
                 isinstance(current, np.ndarray) or backend.is_tensor(current)
             ) and len(current.shape) > 0:

keras/src/callbacks/model_checkpoint_test.py

@@ -167,17 +167,17 @@ def get_model():
                 filepath, monitor="unknown", save_best_only=True
             )
         ]
-        model.fit(
-            x_train,
-            y_train,
-            batch_size=BATCH_SIZE,
-            validation_data=(x_test, y_test),
-            callbacks=cbks,
-            epochs=1,
-            verbose=0,
-        )
-        # File won't be written.
-        self.assertFalse(os.path.exists(filepath))
+        with pytest.warns(UserWarning):
+            model.fit(
+                x_train,
+                y_train,
+                batch_size=BATCH_SIZE,
+                validation_data=(x_test, y_test),
+                callbacks=cbks,
+                epochs=1,
+                verbose=0,
+            )
+        self.assertTrue(os.path.exists(filepath))
 
         # Case 6
         with warnings.catch_warnings(record=True) as warning_logs:

keras/src/models/functional.py

@@ -288,7 +288,13 @@ def _adjust_input_rank(self, flat_inputs):
 
     def _standardize_inputs(self, inputs):
         raise_exception = False
-        if isinstance(inputs, dict) and not isinstance(
+        if (
+            isinstance(self._inputs_struct, list)
+            and len(self._inputs_struct) == 1
+            and ops.is_tensor(inputs)
+        ):
+            inputs = [inputs]
+        elif isinstance(inputs, dict) and not isinstance(
             self._inputs_struct, dict
         ):
             # This is to avoid warning