rename Dropout2D/3D to Dropout2d/3d, test=develop (#26796)

rename Dropout2D/3D to Dropout2d/3d

python/paddle/fluid/tests/unittests/test_dropout_op.py

@@ -530,7 +530,7 @@ class TestDropout2dFAPIError(unittest.TestCase):
             self.assertRaises(ValueError, test_dataformat)
 
 
-class TestDropout2DCAPI(unittest.TestCase):
+class TestDropout2dCAPI(unittest.TestCase):
     def setUp(self):
         np.random.seed(123)
         self.places = [fluid.CPUPlace()]
@@ -543,7 +543,7 @@ class TestDropout2DCAPI(unittest.TestCase):
                 input_np = np.random.random([2, 3, 4, 5]).astype("float32")
                 result_np = input_np
                 input = fluid.dygraph.to_variable(input_np)
-                m = paddle.nn.Dropout2D(p=0.)
+                m = paddle.nn.Dropout2d(p=0.)
                 m.eval()
                 result = m(input)
                 self.assertTrue(np.allclose(result.numpy(), result_np))
@@ -616,7 +616,7 @@ class TestDropout3dFAPIError(unittest.TestCase):
             self.assertRaises(ValueError, test_dataformat)
 
 
-class TestDropout3DCAPI(unittest.TestCase):
+class TestDropout3dCAPI(unittest.TestCase):
     def setUp(self):
         np.random.seed(123)
         self.places = [fluid.CPUPlace()]
@@ -629,7 +629,7 @@ class TestDropout3DCAPI(unittest.TestCase):
                 input_np = np.random.random([2, 3, 4, 5, 6]).astype("float32")
                 result_np = input_np
                 input = fluid.dygraph.to_variable(input_np)
-                m = paddle.nn.Dropout3D(p=0.)
+                m = paddle.nn.Dropout3d(p=0.)
                 m.eval()
                 result = m(input)
                 self.assertTrue(np.allclose(result.numpy(), result_np))

python/paddle/nn/__init__.py

@@ -94,8 +94,8 @@ from .layer.common import UpsamplingNearest2d  #DEFINE_ALIAS
 from .layer.common import UpsamplingBilinear2d  #DEFINE_ALIAS
 from .layer.common import Bilinear  #DEFINE_ALIAS
 from .layer.common import Dropout  #DEFINE_ALIAS
-from .layer.common import Dropout2D  #DEFINE_ALIAS
-from .layer.common import Dropout3D  #DEFINE_ALIAS
+from .layer.common import Dropout2d  #DEFINE_ALIAS
+from .layer.common import Dropout3d  #DEFINE_ALIAS
 from .layer.common import AlphaDropout  #DEFINE_ALIAS
 
 from .layer.pooling import AvgPool1d  #DEFINE_ALIAS

python/paddle/nn/layer/__init__.py

@@ -63,8 +63,8 @@ from .common import UpSample  #DEFINE_ALIAS
 from .common import UpsamplingNearest2d  #DEFINE_ALIAS
 from .common import UpsamplingBilinear2d  #DEFINE_ALIAS
 from .common import Dropout  #DEFINE_ALIAS
-from .common import Dropout2D  #DEFINE_ALIAS
-from .common import Dropout3D  #DEFINE_ALIAS
+from .common import Dropout2d  #DEFINE_ALIAS
+from .common import Dropout3d  #DEFINE_ALIAS
 from .common import AlphaDropout  #DEFINE_ALIAS
 from .pooling import AvgPool1d  #DEFINE_ALIAS
 from .pooling import AvgPool2d  #DEFINE_ALIAS

python/paddle/nn/layer/common.py

@@ -41,8 +41,8 @@ __all__ = [
     'ReplicationPad3d',
     'CosineSimilarity',
     'Dropout',
-    'Dropout2D',
-    'Dropout3D',
+    'Dropout2d',
+    'Dropout3d',
     'Bilinear',
     'AlphaDropout',
 ]
@@ -766,7 +766,7 @@ class Dropout(layers.Layer):
         return out
 
 
-class Dropout2D(layers.Layer):
+class Dropout2d(layers.Layer):
     """
     Randomly zero out entire channels (in the batched input 4d tensor with the shape `NCHW` ,
     a channel is a 2D feature map with the shape `HW`). Each channel will be zeroed out independently
@@ -798,7 +798,7 @@ class Dropout2D(layers.Layer):
             paddle.disable_static()
             x = np.random.random(size=(2, 3, 4, 5)).astype('float32')
             x = paddle.to_tensor(x)
-            m = paddle.nn.Dropout2D(p=0.5)
+            m = paddle.nn.Dropout2d(p=0.5)
             y_train = m(x)
             m.eval()  # switch the model to test phase
             y_test = m(x)
@@ -808,7 +808,7 @@ class Dropout2D(layers.Layer):
    """
 
     def __init__(self, p=0.5, data_format='NCHW', name=None):
-        super(Dropout2D, self).__init__()
+        super(Dropout2d, self).__init__()
 
         self.p = p
         self.data_format = data_format
@@ -824,7 +824,7 @@ class Dropout2D(layers.Layer):
         return out
 
 
-class Dropout3D(layers.Layer):
+class Dropout3d(layers.Layer):
     """
     Randomly zero out entire channels (in the batched input 5d tensor with the shape `NCDHW` ,
     a channel is a 3D feature map with the shape `DHW` ). Each channel will be zeroed out independently
@@ -856,7 +856,7 @@ class Dropout3D(layers.Layer):
             paddle.disable_static()
             x = np.random.random(size=(2, 3, 4, 5, 6)).astype('float32')
             x = paddle.to_tensor(x)
-            m = paddle.nn.Dropout3D(p=0.5)
+            m = paddle.nn.Dropout3d(p=0.5)
             y_train = m(x)
             m.eval()  # switch the model to test phase
             y_test = m(x)
@@ -866,7 +866,7 @@ class Dropout3D(layers.Layer):
    """
 
     def __init__(self, p=0.5, data_format='NCDHW', name=None):
-        super(Dropout3D, self).__init__()
+        super(Dropout3d, self).__init__()
 
         self.p = p
         self.data_format = data_format