Renaming ASPP to SpatialPyramidPooling.

PiperOrigin-RevId: 335049970

official/vision/keras_cv/layers/__init__.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 # ==============================================================================
 """Keras-CV layers package definition."""
-from official.vision.keras_cv.layers.deeplab import ASPP
+from official.vision.keras_cv.layers.deeplab import SpatialPyramidPooling

official/vision/keras_cv/layers/deeplab.py

@@ -18,7 +18,7 @@ import tensorflow as tf
 
 
 @tf.keras.utils.register_keras_serializable(package='keras_cv')
-class ASPP(tf.keras.layers.Layer):
+class SpatialPyramidPooling(tf.keras.layers.Layer):
   """Implements the Atrous Spatial Pyramid Pooling.
 
   Reference:
@@ -36,10 +36,10 @@ class ASPP(tf.keras.layers.Layer):
       kernel_regularizer=None,
       interpolation='bilinear',
       **kwargs):
-    """Initializes `ASPP`.
+    """Initializes `SpatialPyramidPooling`.
 
     Arguments:
-      output_channels: Number of channels produced by ASPP.
+      output_channels: Number of channels produced by SpatialPyramidPooling.
       dilation_rates: A list of integers for parallel dilated conv.
       batchnorm_momentum: A float for the momentum in BatchNorm. Defaults to
         0.99.
@@ -51,7 +51,7 @@ class ASPP(tf.keras.layers.Layer):
         `bilinear`.
       **kwargs: Other keyword arguments for the layer.
     """
-    super(ASPP, self).__init__(**kwargs)
+    super(SpatialPyramidPooling, self).__init__(**kwargs)
 
     self.output_channels = output_channels
     self.dilation_rates = dilation_rates
@@ -133,5 +133,5 @@ class ASPP(tf.keras.layers.Layer):
             self.kernel_regularizer),
         'interpolation': self.interpolation,
     }
-    base_config = super(ASPP, self).get_config()
+    base_config = super(SpatialPyramidPooling, self).get_config()
     return dict(list(base_config.items()) + list(config.items()))

official/vision/keras_cv/layers/deeplab_test.py

@@ -25,20 +25,22 @@ class DeeplabTest(keras_parameterized.TestCase):
 
   def test_aspp(self):
     inputs = tf.keras.Input(shape=(64, 64, 128), dtype=tf.float32)
-    layer = deeplab.ASPP(output_channels=256, dilation_rates=[6, 12, 18])
+    layer = deeplab.SpatialPyramidPooling(output_channels=256,
+                                          dilation_rates=[6, 12, 18])
     output = layer(inputs)
     self.assertAllEqual([None, 64, 64, 256], output.shape)
 
   def test_aspp_invalid_shape(self):
     inputs = tf.keras.Input(shape=(64, 64), dtype=tf.float32)
-    layer = deeplab.ASPP(output_channels=256, dilation_rates=[6, 12, 18])
+    layer = deeplab.SpatialPyramidPooling(output_channels=256,
+                                          dilation_rates=[6, 12, 18])
     with self.assertRaises(ValueError):
       _ = layer(inputs)
 
   def test_config_with_custom_name(self):
-    layer = deeplab.ASPP(256, [5], name='aspp')
+    layer = deeplab.SpatialPyramidPooling(256, [5], name='aspp')
     config = layer.get_config()
-    layer_1 = deeplab.ASPP.from_config(config)
+    layer_1 = deeplab.SpatialPyramidPooling.from_config(config)
     self.assertEqual(layer_1.name, layer.name)