[remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceCo…

…nv RowConv (PaddlePaddle#48654)

* [remove fluid] PRelu BilinearTensorProduct

* [remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceConv RowConv

* [remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceConv RowConv

* [remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceConv RowConv

* [remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceConv RowConv

* [remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceConv RowConv

* [remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceConv RowConv

* [remove fluid] PRelu BilinearTensorProduct Conv2DTranspose SequenceConv RowConv

python/paddle/fluid/tests/unittests/dygraph_to_static/test_basic_api_transformation.py

@@ -113,11 +113,11 @@ def test_transformed_static_result(self):
 
 # 1. test Apis that inherit from layers.Layer
 def dyfunc_BilinearTensorProduct(layer1, layer2):
-    bilinearTensorProduct = fluid.dygraph.nn.BilinearTensorProduct(
-        input1_dim=5,
-        input2_dim=4,
-        output_dim=1000,
-        param_attr=fluid.ParamAttr(
+    bilinearTensorProduct = paddle.nn.Bilinear(
+        5,
+        4,
+        1000,
+        weight_attr=fluid.ParamAttr(
             initializer=fluid.initializer.Constant(value=0.99)
         ),
         bias_attr=fluid.ParamAttr(
@@ -165,12 +165,11 @@ def dyfunc_Conv3D(input):
 
 
 def dyfunc_Conv2DTranspose(input):
-    conv2dTranspose = fluid.dygraph.nn.Conv2DTranspose(
-        num_channels=3,
-        num_filters=12,
-        filter_size=12,
-        use_cudnn=False,
-        param_attr=fluid.ParamAttr(
+    conv2dTranspose = paddle.nn.Conv2DTranspose(
+        3,
+        12,
+        12,
+        weight_attr=fluid.ParamAttr(
             initializer=fluid.initializer.Constant(value=0.99)
         ),
         bias_attr=fluid.ParamAttr(
@@ -221,11 +220,12 @@ def dyfunc_Pool2D(input):
 
 
 def dyfunc_Prelu(input):
-    prelu0 = fluid.PRelu(
-        mode='all',
-        param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant(1.0)),
+    prelu0 = paddle.nn.PReLU(
+        weight_attr=fluid.ParamAttr(
+            initializer=fluid.initializer.Constant(1.0)
+        ),
     )
-    res = prelu0(input=input)
+    res = prelu0(input)
     return res
 
 

python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py

@@ -37,7 +37,7 @@
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid.dygraph import to_variable
-from paddle.fluid.dygraph.nn import BatchNorm, Conv2DTranspose
+from paddle.fluid.dygraph.nn import BatchNorm
 from paddle.jit import ProgramTranslator
 from paddle.jit.api import declarative
 
@@ -430,14 +430,13 @@ def __init__(
                 initializer=fluid.initializer.Constant(0.0)
             )
 
-        self._deconv = Conv2DTranspose(
+        self._deconv = paddle.nn.Conv2DTranspose(
             num_channels,
             num_filters,
-            filter_size=filter_size,
+            filter_size,
             stride=stride,
             padding=padding,
-            use_cudnn=use_cudnn,
-            param_attr=fluid.ParamAttr(
+            weight_attr=fluid.ParamAttr(
                 initializer=fluid.initializer.NormalInitializer(
                     loc=0.0, scale=stddev
                 )

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

@@ -24,9 +24,7 @@
 class TestDygraphBilinearTensorProductAPIError(unittest.TestCase):
     def test_errors(self):
         with fluid.program_guard(fluid.Program(), fluid.Program()):
-            layer = fluid.dygraph.nn.BilinearTensorProduct(
-                input1_dim=5, input2_dim=4, output_dim=1000
-            )
+            layer = paddle.nn.Bilinear(5, 4, 1000)
             # the input must be Variable.
             x0 = fluid.create_lod_tensor(
                 np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace()

python/paddle/fluid/tests/unittests/test_conv2d_transpose_op.py

@@ -1084,86 +1084,5 @@ def call_func(self, x):
         return out
 
 
-class TestTensorOutputSize5(TestTensorOutputSize1):
-    def path_prefix(self):
-        return 'conv2d_transpose_tensor_output_size5'
-
-    def call_func(self, x):
-        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
-        output_size = [17, paddle.assign([17])]
-        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
-            num_channels=3,
-            num_filters=6,
-            filter_size=3,
-            output_size=output_size,
-            stride=2,
-        )
-        out = conv2d_trans(x)
-        return out
-
-
-class TestTensorOutputSize6(TestTensorOutputSize1):
-    def path_prefix(self):
-        return 'conv2d_transpose_tensor_output_size6'
-
-    def var_prefix(self):
-        return "Var["
-
-    def call_func(self, x):
-        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
-        output_size = paddle.assign([17, 17])
-        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
-            num_channels=3,
-            num_filters=6,
-            filter_size=3,
-            output_size=output_size,
-            stride=2,
-        )
-        out = conv2d_trans(x)
-        return out
-
-
-class TestTensorOutputSize7(TestTensorOutputSize1):
-    def path_prefix(self):
-        return 'conv2d_transpose_tensor_output_size7'
-
-    def var_prefix(self):
-        return ""
-
-    def call_func(self, x):
-        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
-        output_size = 17
-        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
-            num_channels=3,
-            num_filters=6,
-            filter_size=3,
-            output_size=output_size,
-            stride=2,
-        )
-        out = conv2d_trans(x)
-        return out
-
-
-class TestTensorOutputSize8(TestTensorOutputSize1):
-    def path_prefix(self):
-        return 'conv2d_transpose_tensor_output_size8'
-
-    def var_prefix(self):
-        return ""
-
-    def call_func(self, x):
-        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
-        output_size = [17, 17]
-        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
-            num_channels=3,
-            num_filters=6,
-            filter_size=3,
-            output_size=output_size,
-            stride=2,
-        )
-        out = conv2d_trans(x)
-        return out
-
-
 if __name__ == '__main__':
     unittest.main()

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

@@ -12,10 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import unittest
+
+import numpy as np
+
 import paddle
 import paddle.fluid as fluid
-import numpy as np
-import unittest
 
 
 def infinite_reader():

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

@@ -21,7 +21,7 @@
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.framework as framework
-from paddle.fluid.dygraph.nn import BatchNorm, Embedding, GroupNorm, PRelu
+from paddle.fluid.dygraph.nn import BatchNorm, Embedding, GroupNorm
 from paddle.nn import Linear
 
 
@@ -212,9 +212,6 @@ def __init__(self):
                     self.layer_norm_1 = paddle.nn.LayerNorm([10])
                     self.layer_norm_2 = paddle.nn.LayerNorm(10)
 
-                    self.prelu1 = PRelu("channel", channel=5)
-                    self.prelu2 = PRelu("channel", channel=5)
-
                     self.group_norm1 = GroupNorm(8, 4)
                     self.gourp_norm2 = GroupNorm(8, 4)
 

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

@@ -185,10 +185,10 @@ def __init__(
     ):
         super().__init__()
 
-        self._deconv = fluid.dygraph.Conv2DTranspose(
-            num_channels=num_channels,
-            num_filters=num_filters,
-            filter_size=filter_size,
+        self._deconv = paddle.nn.Conv2DTranspose(
+            num_channels,
+            num_filters,
+            filter_size,
             stride=stride,
             padding=padding,
             bias_attr=None if use_bias else False,