[remove fluid.layers.relu] remove unit tests (part 1)

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

@@ -186,7 +186,7 @@ def func(self, place):
 
         x = layers.data('x', shape, False, dtype)
         x.persistable = True
-        y = layers.relu(x)
+        y = F.relu(x)
         x_arr = np.random.uniform(-1, 1, shape).astype(dtype)
         x_arr[np.abs(x_arr) < 0.005] = 0.02
 

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

@@ -18,6 +18,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 import paddle.static as static
 
 
@@ -285,7 +286,7 @@ def test_error(self):
         x = fluid.data(name='x', shape=[None, 2, 8, 8], dtype='float32')
         x.stop_gradient = False
         conv = fluid.layers.conv2d(x, 4, 1, bias_attr=False)
-        y = fluid.layers.relu(conv)
+        y = F.relu(conv)
 
         with self.assertRaises(TypeError):
             x_grad = fluid.gradients(y.name, x)

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

@@ -18,6 +18,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.fluid import core
 
 paddle.enable_static()
@@ -160,7 +161,7 @@ def build_origin_program(
                 data_layout='NHWC',
             )
             out = bn1 + bn2
-            out = fluid.layers.relu(out)
+            out = F.relu(out)
             prediction = fluid.layers.fc(
                 input=out, size=10, act='softmax', param_attr=self.fc_param_attr
             )

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

@@ -22,6 +22,7 @@
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
+import paddle.nn.functional as F
 
 
 class TestMNIST(TestParallelExecutorBase):
@@ -97,7 +98,7 @@ def build_program(self, main_program, startup_program):
             X = fluid.data(name="X", shape=[3, 3], dtype='float32')
             Y = fluid.data(name="Y", shape=[3, 3], dtype='float32')
             Out1 = X * 5
-            Out2 = fluid.layers.relu(Out1)
+            Out2 = F.relu(Out1)
             prediction = paddle.tensor.math._add_with_axis(Y, Out2, axis=1)
             loss = paddle.mean(prediction)
             sgd = fluid.optimizer.SGD(learning_rate=0.001)

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

@@ -20,6 +20,7 @@
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
+import paddle.nn.functional as F
 
 
 def norm(*args, **kargs):
@@ -59,7 +60,7 @@ def simple_depthwise_net(use_feed):
     hidden = paddle.reshape(img, (-1, 1, 28, 28))
     for _ in range(4):
         hidden = sep_conv(hidden, channel=200, stride=2, filter=5)
-        hidden = fluid.layers.relu(hidden)
+        hidden = F.relu(hidden)
     prediction = fluid.layers.fc(hidden, size=10, act='softmax')
     loss = paddle.nn.functional.cross_entropy(
         input=prediction, label=label, reduction='none', use_softmax=False

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

@@ -17,6 +17,7 @@
 import numpy as np
 
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.fluid.reader import use_pinned_memory
 
 
@@ -45,7 +46,7 @@ def setUp(self):
     def iter_loader_data(self, loader):
         for _ in range(self.epoch_num):
             for image, label in loader():
-                relu = fluid.layers.relu(image)
+                relu = F.relu(image)
                 self.assertEqual(image.shape, [self.batch_size, 784])
                 self.assertEqual(label.shape, [self.batch_size, 1])
                 self.assertEqual(relu.shape, [self.batch_size, 784])

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

@@ -18,6 +18,7 @@
 import numpy as np
 
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.fluid import core
 
 
@@ -112,7 +113,7 @@ def __reader__():
             try:
                 for _ in range(self.epoch_num):
                     for image, _ in loader():
-                        fluid.layers.relu(image)
+                        F.relu(image)
             except core.EnforceNotMet as ex:
                 self.assertIn("Blocking queue is killed", str(ex))
                 exception = ex

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

@@ -17,6 +17,7 @@
 import numpy as np
 
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.io import DataLoader, Dataset
 
 
@@ -71,7 +72,7 @@ def prepare_data_loader(self):
     def run_one_epoch_with_break(self, loader):
         for step_id, data in enumerate(loader()):
             image, label = data
-            relu = fluid.layers.relu(image)
+            relu = F.relu(image)
             self.assertEqual(image.shape, [self.batch_size, 784])
             self.assertEqual(label.shape, [self.batch_size, 1])
             self.assertEqual(relu.shape, [self.batch_size, 784])

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

@@ -19,6 +19,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.wrapped_decorator import wrap_decorator
 from paddle.vision.models import resnet50, resnet101
@@ -317,8 +318,8 @@ def func_example_no_grad_vars(self):
         numel = x_np.size
         x.stop_gradient = False
 
-        y1 = fluid.layers.relu(x)
-        y2 = fluid.layers.relu(x)
+        y1 = F.relu(x)
+        y2 = F.relu(x)
         z = y1 + y2
         w = z * z
 
@@ -436,7 +437,7 @@ def func_example_with_gradient_accumulation_and_create_graph(self):
         numel = x_np.size
         x.stop_gradient = False
 
-        y = fluid.layers.relu(x)
+        y = F.relu(x)
         z = y + 1
         w = z * z
 
@@ -489,8 +490,8 @@ def func_example_with_gradient_accumulation_and_no_grad_vars(self):
         numel = x_np.size
         x.stop_gradient = False
 
-        y1 = fluid.layers.relu(x)
-        y2 = fluid.layers.relu(x)
+        y1 = F.relu(x)
+        y2 = F.relu(x)
         z = y1 + y2
         w = z * z
 
@@ -540,7 +541,7 @@ def func_example_with_gradient_accumulation_and_not_create_graph(self):
         numel = x_np.size
         x.stop_gradient = False
 
-        y = fluid.layers.relu(x)
+        y = F.relu(x)
         z = y + 1
         w = z * z
 

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

@@ -21,6 +21,7 @@
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
+import paddle.nn.functional as F
 from paddle.fluid.dygraph.base import to_variable
 from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import AdamOptimizer
@@ -58,7 +59,7 @@ def __init__(self, name_scope, num_hidden):
         self.gc2 = GraphConv(self.full_name(), 32, 10)
 
     def forward(self, x, adj):
-        x = fluid.layers.relu(self.gc(x, adj))
+        x = F.relu(self.gc(x, adj))
         return self.gc2(x, adj)
 
 

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

@@ -19,6 +19,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.fluid import core
 from paddle.fluid.dygraph.base import to_variable
 from paddle.fluid.dygraph.parallel import (
@@ -34,7 +35,7 @@ def __init__(self, name_scope):
         super().__init__(name_scope)
 
     def forward(self, inputs):
-        x = fluid.layers.relu(inputs)
+        x = F.relu(inputs)
         x = paddle.multiply(x, x)
         x = paddle.sum(x)
         return [x]

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

@@ -19,6 +19,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.fluid import core
 from paddle.fluid.optimizer import SGDOptimizer
 
@@ -38,7 +39,7 @@ def forward(self, inputs):
         x = paddle.reshape(inputs, shape=[-1, 4])
         x = self.affine1(x)
         x = paddle.nn.functional.dropout(x, self.dropout_ratio)
-        x = fluid.layers.relu(x)
+        x = F.relu(x)
         action_scores = self.affine2(x)
         return paddle.nn.functional.softmax(action_scores, axis=1)
 

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

@@ -344,19 +344,19 @@ def test_SyncBatchNorm(self):
     def test_relu(self):
         with self.static_graph():
             t = layers.data(name='t', shape=[3, 3], dtype='float32')
-            ret = layers.relu(t)
+            ret = F.relu(t)
             static_ret = self.get_static_graph_result(
                 feed={'t': np.ones([3, 3], dtype='float32')}, fetch_list=[ret]
             )[0]
 
         with self.dynamic_graph():
             with _test_eager_guard():
                 t = np.ones([3, 3], dtype='float32')
-                dy_eager_ret = layers.relu(base.to_variable(t))
+                dy_eager_ret = F.relu(base.to_variable(t))
                 dy_eager_ret_value = dy_eager_ret.numpy()
 
             t = np.ones([3, 3], dtype='float32')
-            dy_ret = layers.relu(base.to_variable(t))
+            dy_ret = F.relu(base.to_variable(t))
             dy_ret_value = dy_ret.numpy()
 
         np.testing.assert_allclose(static_ret, dy_ret_value, rtol=1e-05)

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

@@ -18,6 +18,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 
 
 class TestMemoryReuseExcludeFeedVar(unittest.TestCase):
@@ -29,7 +30,7 @@ def main_impl(self, place):
         image = fluid.layers.data(
             name='image', shape=self.image_shape, dtype='float32'
         )
-        relu_image = fluid.layers.relu(image)
+        relu_image = F.relu(image)
         loss = paddle.mean(relu_image)
 
         build_strategy = fluid.BuildStrategy()

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

@@ -18,7 +18,7 @@
 
 import paddle
 import paddle.fluid as fluid
-import paddle.fluid.layers as layers
+import paddle.nn.functional as F
 from paddle import _legacy_C_ops
 
 
@@ -66,7 +66,7 @@ def test_relu(self):
             a = np.random.uniform(-1, 1, self.shape).astype(self.dtype)
             x = fluid.dygraph.to_variable(a)
 
-            res1 = layers.relu(x)
+            res1 = F.relu(x)
             res2 = _legacy_C_ops.relu(x)
 
             np.testing.assert_array_equal(res1.numpy(), res2.numpy())

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

@@ -19,6 +19,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 from paddle.fluid.framework import _in_legacy_dygraph
 from paddle.fluid.wrapped_decorator import wrap_decorator
 
@@ -220,7 +221,7 @@ def func_example_with_gradient_accumulation_and_create_graph(self):
         numel = x_np.size
         x.stop_gradient = False
 
-        y = fluid.layers.relu(x)
+        y = F.relu(x)
         z = y + 1
         w = z * z
 
@@ -261,8 +262,8 @@ def test_example_with_gradient_accumulation_and_no_grad_vars(self):
         numel = x_np.size
         x.stop_gradient = False
 
-        y1 = fluid.layers.relu(x)
-        y2 = fluid.layers.relu(x)
+        y1 = F.relu(x)
+        y2 = F.relu(x)
         z = y1 + y2
         w = z * z
 
@@ -308,7 +309,7 @@ def test_example_with_gradient_accumulation_and_not_create_graph(self):
         numel = x_np.size
         x.stop_gradient = False
 
-        y = fluid.layers.relu(x)
+        y = F.relu(x)
         z = y + 1
         w = z * z
 

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

@@ -18,6 +18,7 @@
 
 import paddle
 import paddle.fluid as fluid
+import paddle.nn.functional as F
 
 
 class TestInferencePartialFeed(unittest.TestCase):
@@ -38,9 +39,9 @@ def run_network(self, places, use_split, has_persistable):
             else:
                 lr = fluid.data(name='lr', shape=[None], dtype='float32')
 
-            relu_x = fluid.layers.relu(x)
-            relu_y = fluid.layers.relu(y)
-            relu_lr = fluid.layers.relu(lr)
+            relu_x = F.relu(x)
+            relu_y = F.relu(y)
+            relu_lr = F.relu(lr)
 
         exe = fluid.Executor(places[0])
         exe.run(startup_prog)

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

@@ -20,6 +20,7 @@
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
+import paddle.nn.functional as F
 from paddle.fluid.framework import _in_legacy_dygraph, _test_eager_guard
 
 
@@ -653,7 +654,7 @@ def func_test_backward(self):
         with fluid.dygraph.guard():
             var = fluid.dygraph.to_variable(self.array)
             var.stop_gradient = False
-            loss = fluid.layers.relu(var)
+            loss = F.relu(var)
             loss.backward()
             grad_var = var._grad_ivar()
             self.assertEqual(grad_var.shape, self.shape)
@@ -667,7 +668,7 @@ def func_test_gradient(self):
         with fluid.dygraph.guard():
             var = fluid.dygraph.to_variable(self.array)
             var.stop_gradient = False
-            loss = fluid.layers.relu(var)
+            loss = F.relu(var)
             loss.backward()
             grad_var = var.gradient()
             self.assertEqual(grad_var.shape, self.array.shape)

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

@@ -20,6 +20,7 @@
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.fluid.layers as layers
+import paddle.nn.functional as F
 from paddle.fluid.backward import append_backward
 from paddle.fluid.framework import Program, program_guard
 
@@ -96,7 +97,7 @@ def body(i, ten, test_dict, test_list, test_list_dict):
             test_list[0] = paddle.reshape(test_list[0], [2, -1]) + 1
 
             test_list_dict[0]["test_key"] += 1
-            test_list_dict[0]["test_key"] = fluid.layers.relu(
+            test_list_dict[0]["test_key"] = F.relu(
                 test_list_dict[0]["test_key"]
             )