remove nets.py in fluid

python/paddle/fluid/__init__.py

@@ -56,7 +56,6 @@
 from . import layers
 from . import dygraph
 from . import contrib
-from . import nets
 from . import optimizer
 from . import backward
 from .backward import gradients
@@ -124,7 +123,6 @@
         'disable_dygraph',
         'enable_imperative',
         'disable_imperative',
-        'nets',
         'optimizer',
         'backward',
         'regularizer',

python/paddle/fluid/tests/book/notest_understand_sentiment.py

@@ -23,21 +23,23 @@
 import paddle
 import paddle.fluid as fluid
 
+from ..unittests import nets
+
 
 def convolution_net(
     data, label, input_dim, class_dim=2, emb_dim=32, hid_dim=32
 ):
     emb = fluid.layers.embedding(
         input=data, size=[input_dim, emb_dim], is_sparse=True
     )
-    conv_3 = fluid.nets.sequence_conv_pool(
+    conv_3 = nets.sequence_conv_pool(
         input=emb,
         num_filters=hid_dim,
         filter_size=3,
         act="tanh",
         pool_type="sqrt",
     )
-    conv_4 = fluid.nets.sequence_conv_pool(
+    conv_4 = nets.sequence_conv_pool(
         input=emb,
         num_filters=hid_dim,
         filter_size=4,

python/paddle/fluid/tests/book/test_image_classification.py

@@ -24,6 +24,8 @@
 import paddle
 import paddle.fluid as fluid
 
+from ..unittests import nets
+
 paddle.enable_static()
 
 
@@ -74,7 +76,7 @@ def layer_warp(block_func, input, ch_in, ch_out, count, stride):
 
 def vgg16_bn_drop(input):
     def conv_block(input, num_filter, groups, dropouts):
-        return fluid.nets.img_conv_group(
+        return nets.img_conv_group(
             input=input,
             pool_size=2,
             pool_stride=2,

python/paddle/fluid/tests/book/test_recognize_digits.py

@@ -23,6 +23,8 @@
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 
+from ..unittests import nets
+
 paddle.enable_static()
 
 BATCH_SIZE = 64
@@ -45,7 +47,7 @@ def mlp(img, label):
 
 
 def conv_net(img, label):
-    conv_pool_1 = fluid.nets.simple_img_conv_pool(
+    conv_pool_1 = nets.simple_img_conv_pool(
         input=img,
         filter_size=5,
         num_filters=20,
@@ -54,7 +56,7 @@ def conv_net(img, label):
         act="relu",
     )
     conv_pool_1 = paddle.static.nn.batch_norm(conv_pool_1)
-    conv_pool_2 = fluid.nets.simple_img_conv_pool(
+    conv_pool_2 = nets.simple_img_conv_pool(
         input=conv_pool_1,
         filter_size=5,
         num_filters=50,

python/paddle/fluid/tests/book/test_recommender_system.py

@@ -23,10 +23,11 @@
 import paddle.fluid as fluid
 import paddle.fluid.framework as framework
 import paddle.fluid.layers as layers
-import paddle.fluid.nets as nets
 from paddle.fluid.executor import Executor
 from paddle.fluid.optimizer import SGDOptimizer
 
+from ..unittests import nets
+
 paddle.enable_static()
 
 IS_SPARSE = True

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

@@ -20,6 +20,8 @@
 import paddle.distributed.fleet as fleet
 import paddle.fluid as fluid
 
+from . import nets
+
 paddle.enable_static()
 
 DTYPE = "float32"
@@ -31,7 +33,7 @@
 
 
 def cnn_model(data):
-    conv_pool_1 = fluid.nets.simple_img_conv_pool(
+    conv_pool_1 = nets.simple_img_conv_pool(
         input=data,
         filter_size=5,
         num_filters=20,
@@ -42,7 +44,7 @@ def cnn_model(data):
             initializer=paddle.nn.initializer.Constant(value=0.01)
         ),
     )
-    conv_pool_2 = fluid.nets.simple_img_conv_pool(
+    conv_pool_2 = nets.simple_img_conv_pool(
         input=conv_pool_1,
         filter_size=5,
         num_filters=50,

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

@@ -21,6 +21,8 @@
 import paddle.distributed.fleet.base.role_maker as role_maker
 import paddle.fluid as fluid
 
+from . import nets
+
 paddle.enable_static()
 
 DTYPE = "float32"
@@ -32,7 +34,7 @@
 
 
 def cnn_model(data):
-    conv_pool_1 = fluid.nets.simple_img_conv_pool(
+    conv_pool_1 = nets.simple_img_conv_pool(
         input=data,
         filter_size=5,
         num_filters=20,
@@ -43,7 +45,7 @@ def cnn_model(data):
             initializer=paddle.nn.initializer.Constant(value=0.01)
         ),
     )
-    conv_pool_2 = fluid.nets.simple_img_conv_pool(
+    conv_pool_2 = nets.simple_img_conv_pool(
         input=conv_pool_1,
         filter_size=5,
         num_filters=50,

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

@@ -21,6 +21,8 @@
 import paddle.distributed.fleet.base.role_maker as role_maker
 import paddle.fluid as fluid
 
+from . import nets
+
 paddle.enable_static()
 
 DTYPE = "float32"
@@ -32,7 +34,7 @@
 
 
 def cnn_model(data):
-    conv_pool_1 = fluid.nets.simple_img_conv_pool(
+    conv_pool_1 = nets.simple_img_conv_pool(
         input=data,
         filter_size=5,
         num_filters=20,
@@ -43,7 +45,7 @@ def cnn_model(data):
             initializer=paddle.nn.initializer.Constant(value=0.01)
         ),
     )
-    conv_pool_2 = fluid.nets.simple_img_conv_pool(
+    conv_pool_2 = nets.simple_img_conv_pool(
         input=conv_pool_1,
         filter_size=5,
         num_filters=50,

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

@@ -20,6 +20,8 @@
 import paddle.fluid as fluid
 from paddle.incubate.distributed.fleet.collective import fleet
 
+from . import nets
+
 paddle.enable_static()
 
 DTYPE = "float32"
@@ -31,7 +33,7 @@
 
 
 def cnn_model(data):
-    conv_pool_1 = fluid.nets.simple_img_conv_pool(
+    conv_pool_1 = nets.simple_img_conv_pool(
         input=data,
         filter_size=5,
         num_filters=20,
@@ -42,7 +44,7 @@ def cnn_model(data):
             initializer=paddle.nn.initializer.Constant(value=0.01)
         ),
     )
-    conv_pool_2 = fluid.nets.simple_img_conv_pool(
+    conv_pool_2 = nets.simple_img_conv_pool(
         input=conv_pool_1,
         filter_size=5,
         num_filters=50,

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

@@ -19,6 +19,8 @@
 import paddle
 import paddle.fluid as fluid
 
+from . import nets
+
 paddle.enable_static()
 
 DTYPE = "float32"
@@ -30,7 +32,7 @@
 
 
 def cnn_model(data):
-    conv_pool_1 = fluid.nets.simple_img_conv_pool(
+    conv_pool_1 = nets.simple_img_conv_pool(
         input=data,
         filter_size=5,
         num_filters=20,
@@ -41,7 +43,7 @@ def cnn_model(data):
             initializer=paddle.nn.initializer.Constant(value=0.01)
         ),
     )
-    conv_pool_2 = fluid.nets.simple_img_conv_pool(
+    conv_pool_2 = nets.simple_img_conv_pool(
         input=conv_pool_1,
         filter_size=5,
         num_filters=50,

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

@@ -22,6 +22,8 @@
 import paddle
 import paddle.fluid as fluid
 
+from . import nets
+
 DTYPE = "float32"
 VOCAB_URL = 'http://paddle-dist-ce-data.bj.bcebos.com/imdb.vocab'
 VOCAB_MD5 = '23c86a0533c0151b6f12fa52b106dcc2'
@@ -63,7 +65,7 @@ def conv_net(
         ),
     )
 
-    conv_3 = fluid.nets.sequence_conv_pool(
+    conv_3 = nets.sequence_conv_pool(
         input=emb,
         num_filters=num_filters,
         filter_size=window_size,