Fix test errors that were introduced by upgrading to Keras Core 0.1.5 (…

…keras-team#2041) * Fix build process for spatial pyramid pooling * Fix label encoder for YOLOV8 for 0.1.5
y-vectorfield · Aug 26, 2023 · 3e0e7a5 · 3e0e7a5
1 parent 6d87ffd
commit 3e0e7a5
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Showing 2 changed files with 10 additions and 2 deletions.
diff --git a/keras_cv/layers/spatial_pyramid.py b/keras_cv/layers/spatial_pyramid.py
@@ -91,6 +91,7 @@ def build(self, input_shape):
                 keras.layers.Activation(self.activation),
             ]
         )
+        conv_sequential.build(input_shape)
         self.aspp_parallel_channels.append(conv_sequential)
 
         # Channel 2 and afterwards are based on self.dilation_rates, and each of
@@ -109,6 +110,7 @@ def build(self, input_shape):
                     keras.layers.Activation(self.activation),
                 ]
             )
+            conv_sequential.build(input_shape)
             self.aspp_parallel_channels.append(conv_sequential)
 
         # Last channel is the global average pooling with conv2D 1x1 kernel.
@@ -125,10 +127,11 @@ def build(self, input_shape):
                 keras.layers.Activation(self.activation),
             ]
         )
+        pool_sequential.build(input_shape)
         self.aspp_parallel_channels.append(pool_sequential)
 
         # Final projection layers
-        self.projection = keras.Sequential(
+        projection = keras.Sequential(
             [
                 keras.layers.Conv2D(
                     filters=self.num_channels,
@@ -140,6 +143,11 @@ def build(self, input_shape):
                 keras.layers.Dropout(rate=self.dropout),
             ],
         )
+        projection_input_channels = (
+            2 + len(self.dilation_rates)
+        ) * self.num_channels
+        projection.build(tuple(input_shape[:-1]) + (projection_input_channels,))
+        self.projection = projection
 
     def call(self, inputs, training=None):
         """Calls the Atrous Spatial Pyramid Pooling layer on an input.

diff --git a/keras_cv/models/object_detection/yolo_v8/yolo_v8_label_encoder.py b/keras_cv/models/object_detection/yolo_v8/yolo_v8_label_encoder.py
@@ -225,7 +225,7 @@ def encode_to_targets(
 
         # return zeros if no gt boxes are present
         return ops.cond(
-            max_num_boxes > 0,
+            ops.array(max_num_boxes > 0),
             lambda: encode_to_targets(
                 pd_scores, pd_bboxes, anc_points, gt_labels, gt_bboxes, mask_gt
             ),