Correct failed test case

keras-team · Dec 21, 2024 · c366d3e · c366d3e
1 parent dcbad19
commit c366d3e
Showing 1 changed file with 39 additions and 4 deletions.
diff --git a/keras/src/layers/preprocessing/image_preprocessing/random_color_jitter.py b/keras/src/layers/preprocessing/image_preprocessing/random_color_jitter.py
@@ -7,6 +7,7 @@
     BaseImagePreprocessingLayer,
 )
 from keras.src.random.seed_generator import SeedGenerator
+from keras.src.utils import backend_utils
 
 
 @keras_export("keras.layers.RandomColorJitter")
@@ -114,13 +115,47 @@ def __init__(
     def transform_images(self, images, transformation, training=True):
         if training:
             if self.brightness_factor is not None:
-                images = self.random_brightness(images)
+                if backend_utils.in_tf_graph():
+                    self.random_brightness.backend.set_backend("tensorflow")
+                transformation = (
+                    self.random_brightness.get_random_transformation(
+                        images,
+                        seed=self._get_seed_generator(self.backend._backend),
+                    )
+                )
+                images = self.random_brightness.transform_images(
+                    images, transformation
+                )
             if self.contrast_factor is not None:
-                images = self.random_contrast(images)
+                if backend_utils.in_tf_graph():
+                    self.random_contrast.backend.set_backend("tensorflow")
+                transformation = self.random_contrast.get_random_transformation(
+                    images, seed=self._get_seed_generator(self.backend._backend)
+                )
+                images = self.random_contrast.transform_images(
+                    images, transformation
+                )
             if self.saturation_factor is not None:
-                images = self.random_saturation(images)
+                if backend_utils.in_tf_graph():
+                    self.random_saturation.backend.set_backend("tensorflow")
+                transformation = (
+                    self.random_saturation.get_random_transformation(
+                        images,
+                        seed=self._get_seed_generator(self.backend._backend),
+                    )
+                )
+                images = self.random_saturation.transform_images(
+                    images, transformation
+                )
             if self.hue_factor is not None:
-                images = self.random_hue(images)
+                if backend_utils.in_tf_graph():
+                    self.random_hue.backend.set_backend("tensorflow")
+                transformation = self.random_hue.get_random_transformation(
+                    images, seed=self._get_seed_generator(self.backend._backend)
+                )
+                images = self.random_hue.transform_images(
+                    images, transformation
+                )
             images = self.backend.cast(images, self.compute_dtype)
         return images