rm unittests eager guard test part14 initializer2layer_norm (#48835)

* rm unittests eager guard test part14 initializer2layer_norm

* monior change

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

@@ -605,16 +605,14 @@ class TestBilinearInitializerDygraphAPI(unittest.TestCase):
 
     def test_bilinear_initializer(self):
         paddle.disable_static()
-        with framework._test_eager_guard():
-            eager_x = self.func_test_case()
+        eager_x = self.func_test_case()
         legacy_x = self.func_test_case()
         self.assertEqual(eager_x.numpy().all(), legacy_x.numpy().all())
         paddle.enable_static()
 
     def test_bilinear_initializer_fp16(self):
         paddle.disable_static()
-        with framework._test_eager_guard():
-            eager_x = self.func_test_case_fp16()
+        eager_x = self.func_test_case_fp16()
         legacy_x = self.func_test_case_fp16()
         self.assertEqual(eager_x.numpy().all(), legacy_x.numpy().all())
         paddle.enable_static()
@@ -712,7 +710,7 @@ class TestSetGlobalInitializer(unittest.TestCase):
 
 
 class TestUniformInitializerDygraph(unittest.TestCase):
-    def func_uniform_initializer(self, dtype="float32"):
+    def test_uniform_initializer(self, dtype="float32"):
         """
         In dygraph mode, we can use initializer directly to initialize a tensor.
         """
@@ -737,14 +735,9 @@ class TestUniformInitializerDygraph(unittest.TestCase):
 
         paddle.enable_static()
 
-    def test_uniform_initializer(self, dtype="float32"):
-        with framework._test_eager_guard():
-            self.func_uniform_initializer()
-        self.func_uniform_initializer()
-
 
 class TestXavierInitializerDygraph(unittest.TestCase):
-    def func_xvarier_initializer(self, dtype="float32"):
+    def test_xvarier_initializer(self, dtype="float32"):
         """
         In dygraph mode, we can use initializer directly to initialize a tensor.
         """
@@ -767,14 +760,9 @@ class TestXavierInitializerDygraph(unittest.TestCase):
         np.testing.assert_allclose(hist, hist2, rtol=0, atol=0.01)
         paddle.enable_static()
 
-    def test_xavier_initializer(self, dtype="float32"):
-        with framework._test_eager_guard():
-            self.func_xvarier_initializer()
-        self.func_xvarier_initializer()
-
 
 class TestMSRAInitializerDygraph(unittest.TestCase):
-    def func_msra_initializer(self, dtype="float32"):
+    def test_msra_initializer(self, dtype="float32"):
         """
         In dygraph mode, we can use initializer directly to initialize a tensor.
         """
@@ -797,14 +785,9 @@ class TestMSRAInitializerDygraph(unittest.TestCase):
         np.testing.assert_allclose(hist, hist2, rtol=0, atol=0.01)
         paddle.enable_static()
 
-    def test_msra_initializer(self, dtype="float32"):
-        with framework._test_eager_guard():
-            self.func_msra_initializer()
-        self.func_msra_initializer()
-
 
 class TesetconsistencyOfDynamicAndStaticGraph(unittest.TestCase):
-    def func_order(self):
+    def test_order(self):
         paddle.set_device('cpu')
         SEED = 123
         weight_attr = paddle.framework.ParamAttr(
@@ -854,11 +837,6 @@ class TesetconsistencyOfDynamicAndStaticGraph(unittest.TestCase):
         np.testing.assert_array_equal(dynamic_res[0], static_res[0])
         np.testing.assert_array_equal(dynamic_res[1], static_res[1])
 
-    def test_order(self):
-        with framework._test_eager_guard():
-            self.func_order()
-        self.func_order()
-
 
 # 2-D Parameter with shape: [10, 15]
 class TestOrthogonalInitializer1(unittest.TestCase):
@@ -881,7 +859,7 @@ class TestOrthogonalInitializer1(unittest.TestCase):
             np.matmul(a, a.T), 9 * np.eye(10), rtol=1e-5, atol=1e-8
         )
 
-    def func_orthogonal(self):
+    def test_orthogonal(self):
         self.config()
         paddle.set_default_dtype(self.dtype)
 
@@ -918,11 +896,6 @@ class TestOrthogonalInitializer1(unittest.TestCase):
 
         self.check_result(res_dygraph, res_static)
 
-    def test_orthogonal(self):
-        with framework._test_eager_guard():
-            self.func_orthogonal()
-        self.func_orthogonal()
-
 
 # 2-D Parameter with shape: [15, 10]
 class TestOrthogonalInitializer2(TestOrthogonalInitializer1):
@@ -998,7 +971,7 @@ class TestOrthogonalInitializer4(unittest.TestCase):
             np.matmul(a, a.T), 9 * np.eye(6), rtol=1e-5, atol=1e-8
         )
 
-    def func_orthogonal(self):
+    def test_orthogonal(self):
         self.config()
         paddle.set_default_dtype(self.dtype)
 
@@ -1030,11 +1003,6 @@ class TestOrthogonalInitializer4(unittest.TestCase):
             )[0]
         self.check_result(res_dygraph, res_static)
 
-    def test_orthogonal(self):
-        with framework._test_eager_guard():
-            self.func_orthogonal()
-        self.func_orthogonal()
-
 
 # 4-D Parameter with shape: [50, 4, 3, 3]
 class TestOrthogonalInitializer5(TestOrthogonalInitializer4):
@@ -1105,7 +1073,7 @@ class TestDiracInitializer1(unittest.TestCase):
         np.testing.assert_array_equal(w_dygraph, w_static)
         np.testing.assert_array_equal(conv_out, conv_in[:, 0:2, 1:9])
 
-    def func_dirac(self):
+    def test_dirac(self):
         self.config()
         paddle.set_default_dtype(self.dtype)
 
@@ -1151,11 +1119,6 @@ class TestDiracInitializer1(unittest.TestCase):
             weight_dygraph, weight_static, conv_input, conv_output
         )
 
-    def test_dirac(self):
-        with framework._test_eager_guard():
-            self.func_dirac()
-        self.func_dirac()
-
 
 # initialize Conv2D weight
 class TestDiracInitializer2(TestDiracInitializer1):

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

@@ -17,7 +17,6 @@ import unittest
 import numpy as np
 
 import paddle
-from paddle.fluid.framework import _test_eager_guard
 from paddle.static import Program, program_guard
 
 
@@ -54,7 +53,7 @@ class TestMultiplyApi(unittest.TestCase):
         res = paddle.inner(x, y)
         return res.numpy()
 
-    def func_test_multiply(self):
+    def test_multiply(self):
         np.random.seed(7)
 
         # test static computation graph: 3-d array
@@ -113,14 +112,9 @@ class TestMultiplyApi(unittest.TestCase):
         res = self._run_dynamic_graph_case(x_data, y_data)
         np.testing.assert_allclose(res, np.inner(x_data, y_data), rtol=1e-05)
 
-    def test_multiply(self):
-        with _test_eager_guard():
-            self.func_test_multiply()
-        self.func_test_multiply()
-
 
 class TestMultiplyError(unittest.TestCase):
-    def func_test_errors(self):
+    def test_errors(self):
         # test static computation graph: dtype can not be int8
         paddle.enable_static()
         with program_guard(Program(), Program()):
@@ -174,11 +168,6 @@ class TestMultiplyError(unittest.TestCase):
         y_data = np.random.randn(200).astype(np.float32)
         self.assertRaises(ValueError, paddle.inner, x_data, y_data)
 
-    def test_errors(self):
-        with _test_eager_guard():
-            self.func_test_errors()
-        self.func_test_errors()
-
 
 if __name__ == '__main__':
     paddle.enable_static()

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

@@ -17,11 +17,10 @@ import unittest
 import numpy as np
 
 import paddle
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestInplace(unittest.TestCase):
-    def func_test_forward_version(self):
+    def test_forward_version(self):
         with paddle.fluid.dygraph.guard():
             var = paddle.to_tensor(np.ones((4, 2, 3)).astype(np.float32))
             self.assertEqual(var.inplace_version, 0)
@@ -38,12 +37,7 @@ class TestInplace(unittest.TestCase):
             var[2] = 3
             self.assertEqual(var.inplace_version, 3)
 
-    def test_forward_version(self):
-        with _test_eager_guard():
-            self.func_test_forward_version()
-        self.func_test_forward_version()
-
-    def func_test_backward_error(self):
+    def test_backward_error(self):
         # It raises an error because the inplace operator will result
         # in incorrect gradient computation.
         with paddle.fluid.dygraph.guard():
@@ -67,12 +61,7 @@ class TestInplace(unittest.TestCase):
             ):
                 loss.backward()
 
-    def test_backward_error(self):
-        with _test_eager_guard():
-            self.func_test_backward_error()
-        self.func_test_backward_error()
-
-    def func_test_backward_success_1(self):
+    def test_backward_success_1(self):
         # var_b is modified inplace before using it, the inplace operator doesn't result
         # in incorrect gradient computation.
         with paddle.fluid.dygraph.guard():
@@ -87,12 +76,7 @@ class TestInplace(unittest.TestCase):
             loss = var_c.sum()
             loss.backward()
 
-    def test_backward_success_1(self):
-        with _test_eager_guard():
-            self.func_test_backward_success_1()
-        self.func_test_backward_success_1()
-
-    def func_test_backward_success_2(self):
+    def test_backward_success_2(self):
         # Although var_b is modified inplace after using it, it does not used in gradient computation.
         # The inplace operator doesn't result in incorrect gradient computation.
         with paddle.fluid.dygraph.guard():
@@ -112,11 +96,6 @@ class TestInplace(unittest.TestCase):
 
             loss.backward()
 
-    def test_backward_success_2(self):
-        with _test_eager_guard():
-            self.func_test_backward_success_2()
-        self.func_test_backward_success_2()
-
 
 class TestDygraphInplace(unittest.TestCase):
     def setUp(self):
@@ -136,7 +115,7 @@ class TestDygraphInplace(unittest.TestCase):
     def inplace_api_processing(self, var):
         return paddle.squeeze_(var)
 
-    def func_test_inplace_api(self):
+    def test_inplace_api(self):
         var = paddle.to_tensor(self.input_var_numpy).astype(self.dtype)
         inplace_var = self.inplace_api_processing(var)
         self.assertTrue(id(var) == id(inplace_var))
@@ -144,12 +123,7 @@ class TestDygraphInplace(unittest.TestCase):
         inplace_var[0] = 2.0
         np.testing.assert_array_equal(var.numpy(), inplace_var.numpy())
 
-    def test_inplace_api(self):
-        with _test_eager_guard():
-            self.func_test_inplace_api()
-        self.func_test_inplace_api()
-
-    def func_test_forward_version(self):
+    def test_forward_version(self):
         with paddle.fluid.dygraph.guard():
             var = paddle.to_tensor(self.input_var_numpy).astype(self.dtype)
             self.assertEqual(var.inplace_version, 0)
@@ -163,12 +137,7 @@ class TestDygraphInplace(unittest.TestCase):
             inplace_var = self.inplace_api_processing(inplace_var)
             self.assertEqual(var.inplace_version, 3)
 
-    def test_forward_version(self):
-        with _test_eager_guard():
-            self.func_test_forward_version()
-        self.func_test_forward_version()
-
-    def func_test_leaf_inplace_var_error(self):
+    def test_leaf_inplace_var_error(self):
         with paddle.fluid.dygraph.guard():
             var = paddle.to_tensor(self.input_var_numpy).astype(self.dtype)
             var.stop_gradient = False
@@ -178,12 +147,7 @@ class TestDygraphInplace(unittest.TestCase):
 
             self.assertRaises(ValueError, leaf_inplace_error)
 
-    def test_leaf_inplace_var_error(self):
-        with _test_eager_guard():
-            self.func_test_leaf_inplace_var_error()
-        self.func_test_leaf_inplace_var_error()
-
-    def func_test_backward_error(self):
+    def test_backward_error(self):
         # It raises an error because the inplace operator will result
         # in incorrect gradient computation.
         with paddle.fluid.dygraph.guard():
@@ -205,12 +169,7 @@ class TestDygraphInplace(unittest.TestCase):
             ):
                 loss.backward()
 
-    def test_backward_error(self):
-        with _test_eager_guard():
-            self.func_test_backward_error()
-        self.func_test_backward_error()
-
-    def func_test_backward_success_1(self):
+    def test_backward_success_1(self):
         # var_b is modified inplace before using it, the inplace operator doesn't result
         # in incorrect gradient computation.
         grad_var_a, grad_var_a_inplace = 0, 1
@@ -242,12 +201,7 @@ class TestDygraphInplace(unittest.TestCase):
 
         self.assertTrue(self.np_compare(grad_var_a_inplace, grad_var_a))
 
-    def test_backward_success_1(self):
-        with _test_eager_guard():
-            self.func_test_backward_success_1()
-        self.func_test_backward_success_1()
-
-    def func_test_backward_success_2(self):
+    def test_backward_success_2(self):
         # Although var_b is modified inplace after using it, it does not used in gradient computation.
         # The inplace operator doesn't result in incorrect gradient computation.
         grad_var_a, grad_var_a_inplace = 0, 1
@@ -286,11 +240,6 @@ class TestDygraphInplace(unittest.TestCase):
             grad_var_a = var_a.grad.numpy()
         np.testing.assert_array_equal(grad_var_a_inplace, grad_var_a)
 
-    def test_backward_success_2(self):
-        with _test_eager_guard():
-            self.func_test_backward_success_2()
-        self.func_test_backward_success_2()
-
 
 class TestDygraphInplaceUnsqueeze(TestDygraphInplace):
     def non_inplace_api_processing(self, var):
@@ -507,7 +456,7 @@ class TestDygraphInplaceRemainder(TestDygraphInplaceAdd):
 
 
 class TestLossIsInplaceVar(unittest.TestCase):
-    def func_test_loss_is_inplace_var(self):
+    def test_loss_is_inplace_var(self):
         with paddle.fluid.dygraph.guard():
             var_a = paddle.ones((2, 2))
             var_a.stop_gradient = False
@@ -530,14 +479,9 @@ class TestLossIsInplaceVar(unittest.TestCase):
 
         np.testing.assert_array_equal(inplace_grad_var_a, grad_var_a)
 
-    def test_loss_is_inplace_var(self):
-        with _test_eager_guard():
-            self.func_test_loss_is_inplace_var()
-        self.func_test_loss_is_inplace_var()
-
 
 class TestContinuouslyInplace(unittest.TestCase):
-    def func_test_continuously_inplace(self):
+    def test_continuously_inplace(self):
         a = paddle.rand([2, 3])
         a.stop_gradient = False
         b = a * 2
@@ -548,24 +492,18 @@ class TestContinuouslyInplace(unittest.TestCase):
 
         b.backward()
 
-    def test_continuously_inplace(self):
-        with _test_eager_guard():
-            self.func_test_continuously_inplace()
-        self.func_test_continuously_inplace()
-
 
 class TestGetitemBeforeInplace(unittest.TestCase):
     def test_getitem_before_inplace(self):
-        with _test_eager_guard():
-            a = paddle.ones(shape=[4, 2, 3], dtype="float32")
-            a.stop_gradient = False
-            b = a**2
-            b[0] = 3
-            # getitem has no_need_buffer input
-            c = b[0:2]
-            loss = c.sum()
-            b[1] = 2
-            loss.backward()
+        a = paddle.ones(shape=[4, 2, 3], dtype="float32")
+        a.stop_gradient = False
+        b = a**2
+        b[0] = 3
+        # getitem has no_need_buffer input
+        c = b[0:2]
+        loss = c.sum()
+        b[1] = 2
+        loss.backward()
 
 
 if __name__ == '__main__':

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

@@ -21,7 +21,6 @@ import paddle.fluid as fluid
 import paddle.fluid.core as core
 from paddle.fluid import Program, program_guard
 from paddle.fluid.dygraph import to_variable
-from paddle.fluid.framework import _test_eager_guard
 
 
 def _reference_instance_norm_naive(x, scale, bias, epsilon, mean, var):
@@ -291,10 +290,6 @@ class TestElasticNormOp(unittest.TestCase):
                     outputs.numpy(), out_np, rtol=1e-05, atol=1e-06
                 )
 
-    def test_eager_api(self):
-        with _test_eager_guard():
-            self.test_norm()
-
 
 class TestElasticNormOpCase2(unittest.TestCase):
     def init_test_case(self):
@@ -329,10 +324,6 @@ class TestElasticNormOpCase2(unittest.TestCase):
                     outputs.numpy(), out_np, rtol=1e-05, atol=1e-06
                 )
 
-    def test_eager_api(self):
-        with _test_eager_guard():
-            self.test_norm()
-
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/fluid/tests/unittests/test_instance_norm_op_v2.py

@@ -20,7 +20,6 @@ import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 from paddle.fluid import Program, program_guard
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestInstanceNorm(unittest.TestCase):
@@ -118,11 +117,6 @@ class TestInstanceNorm(unittest.TestCase):
             y2 = compute_v2(x)
             np.testing.assert_allclose(y1, y2, rtol=1e-05)
 
-    def test_eager_api(self):
-        with _test_eager_guard():
-            self.test_dygraph()
-            self.test_error()
-
 
 if __name__ == '__main__':
     unittest.main()

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

@@ -19,7 +19,6 @@ import unittest
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestSaveLoadAPIError(unittest.TestCase):
@@ -30,7 +29,7 @@ class TestSaveLoadAPIError(unittest.TestCase):
     def tearDown(self):
         self.temp_dir.cleanup()
 
-    def func_test_get_valid_program_error(self):
+    def test_get_valid_program_error(self):
         # case 1: CompiledProgram no program
         graph = core.Graph(core.ProgramDesc())
         compiled_program = fluid.CompiledProgram(graph)
@@ -41,12 +40,7 @@ class TestSaveLoadAPIError(unittest.TestCase):
         with self.assertRaises(TypeError):
             fluid.io._get_valid_program("program")
 
-    def test_get_valid_program_error(self):
-        with _test_eager_guard():
-            self.func_test_get_valid_program_error()
-        self.func_test_get_valid_program_error()
-
-    def func_test_load_vars_error(self):
+    def test_load_vars_error(self):
         place = fluid.CPUPlace()
         exe = fluid.Executor(place)
         # case 1: main_program type error when vars None
@@ -64,11 +58,6 @@ class TestSaveLoadAPIError(unittest.TestCase):
                 vars="vars",
             )
 
-    def test_load_vars_error(self):
-        with _test_eager_guard():
-            self.func_test_load_vars_error()
-        self.func_test_load_vars_error()
-
 
 class TestSaveInferenceModelAPIError(unittest.TestCase):
     def setUp(self):
@@ -77,7 +66,7 @@ class TestSaveInferenceModelAPIError(unittest.TestCase):
     def tearDown(self):
         self.temp_dir.cleanup()
 
-    def func_test_useless_feeded_var_names(self):
+    def test_useless_feeded_var_names(self):
         start_prog = fluid.Program()
         main_prog = fluid.Program()
         with fluid.program_guard(main_prog, start_prog):
@@ -98,11 +87,6 @@ class TestSaveInferenceModelAPIError(unittest.TestCase):
                 main_program=main_prog,
             )
 
-    def test_useless_feeded_var_names(self):
-        with _test_eager_guard():
-            self.func_test_useless_feeded_var_names()
-        self.func_test_useless_feeded_var_names()
-
 
 class TestWhenTrainWithNoGrad(unittest.TestCase):
     def setUp(self):
@@ -111,7 +95,7 @@ class TestWhenTrainWithNoGrad(unittest.TestCase):
     def tearDown(self):
         self.temp_dir.cleanup()
 
-    def func_test_when_train_with_no_grad(self):
+    def test_when_train_with_no_grad(self):
         paddle.disable_static()
         net = paddle.nn.Linear(1024, 1)
         net = paddle.jit.to_static(net)
@@ -127,11 +111,6 @@ class TestWhenTrainWithNoGrad(unittest.TestCase):
             x = paddle.rand([1024], 'float32')
             net(x)
 
-    def test_when_train_with_no_grad(self):
-        with _test_eager_guard():
-            self.func_test_when_train_with_no_grad()
-        self.func_test_when_train_with_no_grad()
-
 
 if __name__ == '__main__':
     paddle.enable_static()

python/paddle/fluid/tests/unittests/test_isfinite_v2_op.py

@@ -18,7 +18,6 @@ import numpy as np
 
 import paddle
 import paddle.fluid as fluid
-from paddle.fluid.framework import _test_eager_guard
 
 
 def run_static(x_np, dtype, op_str, use_gpu=False):
@@ -51,14 +50,13 @@ def run_dygraph(x_np, op_str, use_gpu=True):
 
 def run_eager(x_np, op_str, use_gpu=True):
     with paddle.fluid.dygraph.guard():
-        with _test_eager_guard():
-            place = paddle.CPUPlace()
-            if use_gpu and fluid.core.is_compiled_with_cuda():
-                place = paddle.CUDAPlace(0)
-
-            x = paddle.to_tensor(x_np)
-            dygraph_result = getattr(paddle.tensor, op_str)(x)
-            return dygraph_result
+        place = paddle.CPUPlace()
+        if use_gpu and fluid.core.is_compiled_with_cuda():
+            place = paddle.CUDAPlace(0)
+
+        x = paddle.to_tensor(x_np)
+        dygraph_result = getattr(paddle.tensor, op_str)(x)
+        return dygraph_result
 
 
 def np_data_generator(

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

@@ -1837,5 +1837,4 @@ class TestNotJitForward(unittest.TestCase):
 
 
 if __name__ == '__main__':
-    with fluid.framework._test_eager_guard():
-        unittest.main()
+    unittest.main()

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

@@ -20,7 +20,6 @@ from op_test import OpTest
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.dygraph as dg
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestKronOp(OpTest):
@@ -104,11 +103,6 @@ class TestKronLayer(unittest.TestCase):
         (c,) = exe.run(main, feed={'a': a, 'b': b}, fetch_list=[out_var])
         np.testing.assert_allclose(c, np.kron(a, b))
 
-    def test_api_eager_dygraph(self):
-        with _test_eager_guard():
-            self.test_case()
-            self.test_case_with_output()
-
 
 class TestComplexKronOp(OpTest):
     def setUp(self):

python/paddle/fluid/tests/unittests/test_layer_norm_op_v2.py

@@ -20,7 +20,6 @@ import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 from paddle.fluid import Program, program_guard
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestDygraphLayerNormv2(unittest.TestCase):
@@ -66,12 +65,11 @@ class TestDygraphLayerNormv2(unittest.TestCase):
 
             def compute_v2(x):
                 with fluid.dygraph.guard(p):
-                    with _test_eager_guard():
-                        ln = paddle.nn.LayerNorm(shape[1:])
-                        x1 = paddle.to_tensor(x)
-                        x1.stop_gradient = False
-                        y = ln(x1)
-                        y.backward()
+                    ln = paddle.nn.LayerNorm(shape[1:])
+                    x1 = paddle.to_tensor(x)
+                    x1.stop_gradient = False
+                    y = ln(x1)
+                    y.backward()
                     return y.numpy(), x1.gradient()
 
             x = np.random.randn(*shape).astype("float32")