fix unittests (#21786)

test=develop

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

@@ -29,20 +29,18 @@ from utils import DyGraphProgramDescTracerTestHelper
 
 class SimpleNet(fluid.Layer):
     def __init__(self,
-                 name_scope,
                  hidden_size,
                  vocab_size,
                  num_steps=20,
                  init_scale=0.1,
                  is_sparse=False,
                  dtype='float32'):
-        super(SimpleNet, self).__init__(name_scope)
+        super(SimpleNet, self).__init__()
         self.hidden_size = hidden_size
         self.vocab_size = vocab_size
         self.init_scale = init_scale
         self.num_steps = num_steps
         self.embedding = Embedding(
-            self.full_name(),
             size=[vocab_size, hidden_size],
             dtype=dtype,
             is_sparse=is_sparse,
@@ -100,7 +98,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     fluid.default_main_program().random_seed = seed
 
                     simple_net = SimpleNet(
-                        "simple_net",
                         hidden_size=hidden_size,
                         vocab_size=vocab_size,
                         num_steps=num_steps,
@@ -120,7 +117,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     for i in range(batch_num):
                         x_data = np.arange(12).reshape(4, 3).astype('int64')
                         y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
-                        x_data = x_data.reshape((-1, num_steps, 1))
+                        x_data = x_data.reshape((-1, num_steps))
                         y_data = y_data.reshape((-1, 1))
 
                         x = to_variable(x_data)
@@ -143,7 +140,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     fluid.default_main_program().random_seed = seed
 
                     simple_net = SimpleNet(
-                        "simple_net",
                         hidden_size=hidden_size,
                         vocab_size=vocab_size,
                         num_steps=num_steps,
@@ -153,7 +149,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     exe = fluid.Executor(place)
                     sgd = SGDOptimizer(learning_rate=1e-3)
                     x = fluid.layers.data(
-                        name="x", shape=[-1, num_steps, 1], dtype='int64')
+                        name="x", shape=[-1, num_steps], dtype='int64')
                     y = fluid.layers.data(name="y", shape=[-1, 1], dtype=dtype)
 
                     static_loss = simple_net(x, y)
@@ -172,7 +168,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     for i in range(batch_num):
                         x_data = np.arange(12).reshape(4, 3).astype('int64')
                         y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
-                        x_data = x_data.reshape((-1, num_steps, 1))
+                        x_data = x_data.reshape((-1, num_steps))
                         y_data = y_data.reshape((-1, 1))
                         fetch_list = [static_loss]
                         fetch_list.extend(static_param_name_list)

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

@@ -24,10 +24,9 @@ import paddle.fluid.core as core
 
 
 class SimpleNet(fluid.Layer):
-    def __init__(self, name_scope, vocab_size, hidden_size, dtype):
-        super(SimpleNet, self).__init__(name_scope)
+    def __init__(self, vocab_size, hidden_size, dtype):
+        super(SimpleNet, self).__init__()
         self.emb = fluid.dygraph.Embedding(
-            self.full_name(),
             size=[vocab_size, hidden_size],
             dtype=dtype,
             param_attr='emb.w',
@@ -53,11 +52,10 @@ class TestSimpleNet(unittest.TestCase):
                         adam = SGDOptimizer(learning_rate=0.001)
                         # grad_clip = fluid.dygraph_grad_clip.GradClipByGlobalNorm(5.0)
 
-                        input_word = np.array(
-                            [[[1], [2]], [[2], [1]]]).astype('int64')
+                        input_word = np.array([[1, 2], [2, 1]]).astype('int64')
                         input = to_variable(input_word)
 
-                        simplenet = SimpleNet("SimpleNet", 20, 32, dtype)
+                        simplenet = SimpleNet(20, 32, dtype)
                         input_emb, emb = simplenet(input)
 
                         try:
@@ -99,11 +97,10 @@ class TestSimpleNet(unittest.TestCase):
                     grad_clip = fluid.dygraph_grad_clip.GradClipByGlobalNorm(
                         5.0)
 
-                    input_word = np.array(
-                        [[[1], [2]], [[2], [1]]]).astype('int64')
+                    input_word = np.array([[1, 2], [2, 1]]).astype('int64')
                     input = to_variable(input_word)
 
-                    simplenet = SimpleNet("SimpleNet", 20, 32, "float32")
+                    simplenet = SimpleNet(20, 32, "float32")
                     input_emb, emb = simplenet(input)
 
                     try:

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

@@ -30,20 +30,18 @@ from paddle.fluid.dygraph.jit import TracedLayer
 
 class SimpleNet(fluid.Layer):
     def __init__(self,
-                 name_scope,
                  hidden_size,
                  vocab_size,
                  num_steps=20,
                  init_scale=0.1,
                  is_sparse=False,
                  dtype='float32'):
-        super(SimpleNet, self).__init__(name_scope)
+        super(SimpleNet, self).__init__()
         self.hidden_size = hidden_size
         self.vocab_size = vocab_size
         self.init_scale = init_scale
         self.num_steps = num_steps
         self.embedding = Embedding(
-            self.full_name(),
             size=[vocab_size, hidden_size],
             dtype=dtype,
             is_sparse=is_sparse,
@@ -109,7 +107,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     fluid.default_main_program().random_seed = seed
 
                     simple_net = SimpleNet(
-                        "simple_net",
                         hidden_size=hidden_size,
                         vocab_size=vocab_size,
                         num_steps=num_steps,
@@ -130,7 +127,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     for i in range(batch_num):
                         x_data = np.arange(12).reshape(4, 3).astype('int64')
                         y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
-                        x_data = x_data.reshape((-1, num_steps, 1))
+                        x_data = x_data.reshape((-1, num_steps))
                         y_data = y_data.reshape((-1, 1))
 
                         x = to_variable(x_data)
@@ -153,7 +150,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     fluid.default_main_program().random_seed = seed
 
                     simple_net = SimpleNet(
-                        "simple_net",
                         hidden_size=hidden_size,
                         vocab_size=vocab_size,
                         num_steps=num_steps,
@@ -163,7 +159,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     exe = fluid.Executor(place)
                     sgd = SGDOptimizer(learning_rate=1e-3)
                     x = fluid.layers.data(
-                        name="x", shape=[-1, num_steps, 1], dtype='int64')
+                        name="x", shape=[-1, num_steps], dtype='int64')
                     y = fluid.layers.data(name="y", shape=[-1, 1], dtype=dtype)
 
                     static_loss = simple_net(x, y)
@@ -182,7 +178,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
                     for i in range(batch_num):
                         x_data = np.arange(12).reshape(4, 3).astype('int64')
                         y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
-                        x_data = x_data.reshape((-1, num_steps, 1))
+                        x_data = x_data.reshape((-1, num_steps))
                         y_data = y_data.reshape((-1, 1))
                         fetch_list = [static_loss]
                         fetch_list.extend(static_param_name_list)