remove unittests eager guard tests part2 (#48798)

* remove unittests eager guard tests part2

* rm bicubic eager guard tests

* review

* fix

* fix dtype bug in bce_loss_with_logits

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

@@ -23,7 +23,6 @@ import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.nn.functional as F
 from paddle.fluid import Program, program_guard
-from paddle.fluid.framework import _test_eager_guard
 
 paddle.enable_static()
 
@@ -2100,11 +2099,6 @@ class TestHardswishAPI(unittest.TestCase):
             )
             F.hardswish(x_fp16)
 
-    def test_api_eager_dygraph(self):
-        with _test_eager_guard():
-            self.test_dygraph_api()
-            self.test_errors()
-
 
 class TestSoftRelu(TestActivation):
     def setUp(self):
@@ -2355,11 +2349,6 @@ class TestCELUAPI(unittest.TestCase):
             )
             self.celu(x_fp16)
 
-    def test_api_eager_dygraph(self):
-        with _test_eager_guard():
-            self.test_dygraph_api()
-            self.test_errors()
-
 
 class TestReciprocal(TestActivation):
     def setUp(self):
@@ -3361,7 +3350,7 @@ class TestSwishAPI(unittest.TestCase):
         for r in res:
             np.testing.assert_allclose(out_ref, r, rtol=1e-05)
 
-    def func_test_dygraph_api(self):
+    def test_dygraph_api(self):
         paddle.disable_static(self.place)
         x = paddle.to_tensor(self.x_np)
         out1 = F.swish(x)
@@ -3372,11 +3361,6 @@ class TestSwishAPI(unittest.TestCase):
             np.testing.assert_allclose(out_ref, r.numpy(), rtol=1e-05)
         paddle.enable_static()
 
-    def test_dygraph_api(self):
-        with _test_eager_guard():
-            self.func_test_dygraph_api()
-        self.func_test_dygraph_api()
-
     def test_fluid_api(self):
         paddle.enable_static()
         with fluid.program_guard(fluid.Program()):

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

@@ -20,7 +20,6 @@ from op_test import OpTest
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
-from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.op import Operator
 
 
@@ -187,10 +186,6 @@ class TestAdamOpMultipleSteps(OpTest):
                 "float32"
             )
 
-    def test_api_eager_dygraph(self):
-        with _test_eager_guard():
-            self.test_check_output()
-
 
 def adam_step(inputs, attributes):
     '''
@@ -750,14 +745,6 @@ class TestAdamOpV2(unittest.TestCase):
             adam.step()
         paddle.enable_static()
 
-    def test_api_eager_dygraph(self):
-        with _test_eager_guard():
-            self.test_adam_op_dygraph()
-            self.test_adam_op_with_state_dict()
-            self.test_adam_with_grad_clip()
-            self.test_adam_op_with_set_lr()
-            self.test_adam_op_with_sparse_input_and_weight_decay()
-
 
 class TestAdamOptimizer(unittest.TestCase):
     def _test(
@@ -1281,10 +1268,6 @@ class TestMultiTensorAdam(unittest.TestCase):
                 self._check_with_param_arrt(place, use_amp)
                 self._check_with_param_group(place, use_amp)
 
-    def test_api_eager_dygraph(self):
-        with _test_eager_guard():
-            self.test_main()
-
 
 if __name__ == "__main__":
     paddle.enable_static()

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

@@ -18,11 +18,10 @@ import numpy as np
 
 import paddle
 import paddle.fluid as fluid
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestAdamaxAPI(unittest.TestCase):
-    def func_adamax_api_dygraph(self):
+    def test_adamax_api_dygraph(self):
         paddle.disable_static()
         value = np.arange(26).reshape(2, 13).astype("float32")
         a = paddle.to_tensor(value)
@@ -37,12 +36,7 @@ class TestAdamaxAPI(unittest.TestCase):
         adam.step()
         adam.clear_gradients()
 
-    def test_adamax_api_dygraph(self):
-        with _test_eager_guard():
-            self.func_adamax_api_dygraph()
-        self.func_adamax_api_dygraph()
-
-    def func_adamax_api(self):
+    def test_adamax_api(self):
         paddle.enable_static()
         place = fluid.CPUPlace()
         shape = [2, 3, 8, 8]
@@ -70,14 +64,9 @@ class TestAdamaxAPI(unittest.TestCase):
         rets = exe.run(train_prog, feed={"data": data_np}, fetch_list=[loss])
         assert rets[0] is not None
 
-    def test_adamax_api(self):
-        with _test_eager_guard():
-            self.func_adamax_api()
-        self.func_adamax_api()
-
 
 class TestAdamaxAPIGroup(TestAdamaxAPI):
-    def func_adamax_api_dygraph(self):
+    def test_adamax_api_dygraph(self):
         paddle.disable_static()
         value = np.arange(26).reshape(2, 13).astype("float32")
         a = paddle.to_tensor(value)
@@ -103,11 +92,6 @@ class TestAdamaxAPIGroup(TestAdamaxAPI):
         adam.step()
         adam.clear_gradients()
 
-    def test_adamax_api_dygraph(self):
-        with _test_eager_guard():
-            self.func_adamax_api_dygraph()
-        self.func_adamax_api_dygraph()
-
 
 if __name__ == "__main__":
     unittest.main()

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

@@ -21,7 +21,6 @@ from op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
-from paddle.fluid.framework import _test_eager_guard
 from paddle.framework import core
 
 
@@ -250,11 +249,6 @@ class TestAdamWOp(unittest.TestCase):
                 0.1, epsilon=-1, parameters=linear.parameters()
             )
 
-    def test_api_eager_dygraph(self):
-        with _test_eager_guard():
-            self.test_adamw_op_dygraph()
-            self.test_adamw_op_invalid_input()
-
 
 class TestAdamWOpGroup(TestAdamWOp):
     def test_adamw_op_dygraph(self):

python/paddle/fluid/tests/unittests/test_adaptive_max_pool3d.py

@@ -181,7 +181,7 @@ class TestAdaptiveMaxPool3DAPI(unittest.TestCase):
 
             assert np.allclose(res_5, self.res_5_np)
 
-    def func_dynamic_graph(self):
+    def test_dynamic_graph(self):
         for use_cuda in (
             [False, True] if core.is_compiled_with_cuda() else [False]
         ):
@@ -216,11 +216,6 @@ class TestAdaptiveMaxPool3DAPI(unittest.TestCase):
 
             assert np.allclose(out_5.numpy(), self.res_5_np)
 
-    def test_dynamic_graph(self):
-        with paddle.fluid.framework._test_eager_guard():
-            self.func_dynamic_graph()
-        self.func_dynamic_graph()
-
 
 class TestAdaptiveMaxPool3DClassAPI(unittest.TestCase):
     def setUp(self):

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

@@ -18,7 +18,6 @@ import numpy as np
 
 import paddle
 import paddle.fluid as fluid
-from paddle.fluid.framework import _test_eager_guard
 
 
 class TestAllcloseLayer(unittest.TestCase):
@@ -101,7 +100,7 @@ class TestAllcloseLayer(unittest.TestCase):
                 with fluid.program_guard(main, startup):
                     self.allclose_check(use_cuda=True, dtype='float64')
 
-    def func_dygraph_mode(self):
+    def test_dygraph_mode(self):
         x_1 = np.array([10000.0, 1e-07]).astype("float32")
         y_1 = np.array([10000.1, 1e-08]).astype("float32")
         x_2 = np.array([10000.0, 1e-08]).astype("float32")
@@ -188,11 +187,6 @@ class TestAllcloseLayer(unittest.TestCase):
             )
             self.assertEqual(ret_5.numpy()[0], True)
 
-    def test_dygraph_mode(self):
-        with _test_eager_guard():
-            self.func_dygraph_mode()
-        self.func_dygraph_mode()
-
 
 if __name__ == "__main__":
     unittest.main()

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

@@ -20,7 +20,6 @@ import op_test
 import paddle
 import paddle.fluid.core as core
 from paddle.distributed.models.moe import utils
-from paddle.fluid.framework import _test_eager_guard
 
 
 def assign_pos(x, _cum_count):
@@ -118,7 +117,7 @@ class TestAssignPosAPI(unittest.TestCase):
             )
             assert_allclose(res[0], self.out, self.cum_count)
 
-    def func_api_dygraph(self):
+    def test_api_dygraph(self):
         paddle.disable_static()
         x = paddle.to_tensor(self.x)
         cum_count = paddle.to_tensor(self.cum_count).astype(x.dtype)
@@ -126,11 +125,6 @@ class TestAssignPosAPI(unittest.TestCase):
         out = utils._assign_pos(x, cum_count)
         assert_allclose(out.numpy(), self.out, self.cum_count)
 
-    def test_api_dygraph(self):
-        with _test_eager_guard():
-            self.func_api_dygraph()
-        self.func_api_dygraph()
-
 
 if __name__ == '__main__':
     paddle.enable_static()

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

@@ -19,12 +19,7 @@ import numpy as np
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid.dygraph import to_variable
-from paddle.fluid.framework import (
-    EagerParamBase,
-    ParamBase,
-    _test_eager_guard,
-    in_dygraph_mode,
-)
+from paddle.fluid.framework import EagerParamBase, ParamBase, in_dygraph_mode
 from paddle.jit import ProgramTranslator
 
 
@@ -66,7 +61,7 @@ class L3(fluid.Layer):
 
 
 class TestBaseLayer(unittest.TestCase):
-    def func_test_one_level(self):
+    def test_one_level(self):
         with fluid.dygraph.guard():
             l = L1()
             ret = l()
@@ -79,12 +74,7 @@ class TestBaseLayer(unittest.TestCase):
                 ret.numpy(), 0.2 * np.ones([2, 2]), rtol=1e-05
             )
 
-    def test_one_level(self):
-        with _test_eager_guard():
-            self.func_test_one_level()
-        self.func_test_one_level()
-
-    def func_test_three_level(self):
+    def test_three_level(self):
         with fluid.dygraph.guard():
             l = L3()
             expected_names = [
@@ -106,12 +96,7 @@ class TestBaseLayer(unittest.TestCase):
                 ret.numpy(), 0.8 * np.ones([2, 2]), rtol=1e-05
             )
 
-    def test_three_level(self):
-        with _test_eager_guard():
-            self.func_test_three_level()
-        self.func_test_three_level()
-
-    def func_test_add_parameter_with_error(self):
+    def test_add_parameter_with_error(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             param = net.create_parameter(shape=[1])
@@ -136,11 +121,6 @@ class TestBaseLayer(unittest.TestCase):
             net._loaddict_holder[load_param.name] = load_param
             net.add_parameter("load_param", load_param)
 
-    def test_add_parameter_with_error(self):
-        with _test_eager_guard():
-            self.func_test_add_parameter_with_error()
-        self.func_test_add_parameter_with_error()
-
 
 class BufferLayer(fluid.Layer):
     def __init__(self):
@@ -169,7 +149,7 @@ class BufferNet(fluid.Layer):
 
 
 class TestBuffer(unittest.TestCase):
-    def func_test_buffers_and_named_buffers(self):
+    def test_buffers_and_named_buffers(self):
         def names(named_buffers):
             return [name for name, _ in named_buffers]
 
@@ -192,12 +172,7 @@ class TestBuffer(unittest.TestCase):
                 ['net_buffer', 'new_buffer'],
             )
 
-    def test_buffers_and_named_buffers(self):
-        with _test_eager_guard():
-            self.func_test_buffers_and_named_buffers()
-        self.func_test_buffers_and_named_buffers()
-
-    def func_test_register_buffer_with_error(self):
+    def test_register_buffer_with_error(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var = to_variable(np.zeros([1]))
@@ -241,12 +216,7 @@ class TestBuffer(unittest.TestCase):
             with self.assertRaisesRegexp(KeyError, "already exists"):
                 net.register_buffer("attr_name", var)
 
-    def test_register_buffer_with_error(self):
-        with _test_eager_guard():
-            self.func_test_register_buffer_with_error()
-        self.func_test_register_buffer_with_error()
-
-    def func_test_register_buffer_same_name(self):
+    def test_register_buffer_same_name(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -260,12 +230,7 @@ class TestBuffer(unittest.TestCase):
             net.register_buffer("buffer_name", var3)
             self.assert_var_base_equal(net.buffer_name, var3)
 
-    def test_register_buffer_same_name(self):
-        with _test_eager_guard():
-            self.func_test_register_buffer_same_name()
-        self.func_test_register_buffer_same_name()
-
-    def func_test_buffer_not_persistable(self):
+    def test_buffer_not_persistable(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -274,12 +239,7 @@ class TestBuffer(unittest.TestCase):
             self.assertEqual(len(net.buffers()), 1)
             self.assertEqual(len(net.state_dict()), 0)
 
-    def test_buffer_not_persistable(self):
-        with _test_eager_guard():
-            self.func_test_buffer_not_persistable()
-        self.func_test_buffer_not_persistable()
-
-    def func_test_buffer_not_persistable_del(self):
+    def test_buffer_not_persistable_del(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -287,12 +247,7 @@ class TestBuffer(unittest.TestCase):
             del net.buffer_name
             self.assertEqual(len(net.buffers()), 0)
 
-    def test_buffer_not_persistable_del(self):
-        with _test_eager_guard():
-            self.func_test_buffer_not_persistable_del()
-        self.func_test_buffer_not_persistable_del()
-
-    def func_test_buffer_not_persistable_overwrite(self):
+    def test_buffer_not_persistable_overwrite(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -308,12 +263,7 @@ class TestBuffer(unittest.TestCase):
             self.assertEqual(len(net.buffers()), 1)
             self.assertEqual(len(net.state_dict()), 0)
 
-    def test_buffer_not_persistable_overwrite(self):
-        with _test_eager_guard():
-            self.func_test_buffer_not_persistable_overwrite()
-        self.func_test_buffer_not_persistable_overwrite()
-
-    def func_test_buffer_not_persistable_assign(self):
+    def test_buffer_not_persistable_assign(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
@@ -337,24 +287,14 @@ class TestBuffer(unittest.TestCase):
             self.assertEqual(len(net.buffers()), 0)
             self.assertEqual(len(net.state_dict()), 1)
 
-    def test_buffer_not_persistable_assign(self):
-        with _test_eager_guard():
-            self.func_test_buffer_not_persistable_assign()
-        self.func_test_buffer_not_persistable_assign()
-
-    def func_test_buffer_not_persistable_load(self):
+    def test_buffer_not_persistable_load(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([1]))
             net.register_buffer("buffer_name", var1, persistable=False)
             net.load_dict({})
 
-    def test_buffer_not_persistable_load(self):
-        with _test_eager_guard():
-            self.func_test_buffer_not_persistable_load()
-        self.func_test_buffer_not_persistable_load()
-
-    def func_test_buffer_state_dict(self):
+    def test_buffer_state_dict(self):
         with fluid.dygraph.guard():
             net = fluid.Layer()
             var1 = to_variable(np.zeros([2, 3]))
@@ -375,11 +315,6 @@ class TestBuffer(unittest.TestCase):
 
             self.assert_var_base_equal(net_load.buffer_var1, var1)
 
-    def test_buffer_state_dict(self):
-        with _test_eager_guard():
-            self.func_test_buffer_state_dict()
-        self.func_test_buffer_state_dict()
-
     def assert_var_base_equal(self, var1, var2):
         np.testing.assert_array_equal(var1.numpy(), var2.numpy())
 
@@ -416,7 +351,7 @@ class TestModifiedBuffer(unittest.TestCase):
 
         return out, net.buffer1, net.buffer2
 
-    def func_test_modified(self):
+    def test_modified(self):
         self.funcsetUp()
         dy_outs = self._run(False)
         st_outs = self._run(True)
@@ -426,11 +361,6 @@ class TestModifiedBuffer(unittest.TestCase):
                 dy_outs[i].numpy(), st_outs[i].numpy()
             )
 
-    def test_modified(self):
-        with _test_eager_guard():
-            self.func_test_modified()
-        self.func_test_modified()
-
 
 class TestLayerTo(unittest.TestCase):
     def funcsetUp(self):
@@ -614,12 +544,6 @@ class TestLayerTo(unittest.TestCase):
         self.assertIsNone(model._buffers['buf_name'])
 
     def test_main(self):
-        with _test_eager_guard():
-            self.funcsetUp()
-            self.func_test_to_api()
-            self.func_test_to_api_paddle_dtype()
-            self.func_test_to_api_numpy_dtype()
-            self.func_test_to_api_none_buffer()
         self.funcsetUp()
         self.func_test_to_api()
         self.func_test_to_api_paddle_dtype()

python/paddle/fluid/tests/unittests/test_batch_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 TestBatchNorm(unittest.TestCase):
@@ -91,13 +90,12 @@ class TestBatchNorm(unittest.TestCase):
 
         def compute_1d(x):
             with fluid.dygraph.guard(p):
-                with _test_eager_guard():
-                    bn = paddle.nn.BatchNorm1D(shape[1])
-                    x1 = paddle.to_tensor(x)
-                    x1.stop_gradient = False
-                    y = bn(x1)
-                    y.backward()
-                    return y.numpy(), x1.gradient()
+                bn = paddle.nn.BatchNorm1D(shape[1])
+                x1 = paddle.to_tensor(x)
+                x1.stop_gradient = False
+                y = bn(x1)
+                y.backward()
+                return y.numpy(), x1.gradient()
 
         places = [fluid.CPUPlace()]
         if core.is_compiled_with_cuda():
@@ -138,14 +136,13 @@ class TestBatchNorm(unittest.TestCase):
 
             def compute_v2(x):
                 with fluid.dygraph.guard(p):
-                    with _test_eager_guard():
-                        print("v2")
-                        bn = paddle.nn.BatchNorm2D(shape[1])
-                        x1 = paddle.to_tensor(x)
-                        x1.stop_gradient = False
-                        y = bn(x1)
-                        y.backward()
-                        return y.numpy(), x1.gradient()
+                    print("v2")
+                    bn = paddle.nn.BatchNorm2D(shape[1])
+                    x1 = paddle.to_tensor(x)
+                    x1.stop_gradient = False
+                    y = bn(x1)
+                    y.backward()
+                    return y.numpy(), x1.gradient()
 
             x = np.random.randn(*shape).astype("float32")
             y1, g1 = compute_v1(x)
@@ -175,9 +172,8 @@ class TestBatchNorm(unittest.TestCase):
                     bn = paddle.nn.BatchNorm2D(shape[1])
                     y = bn(paddle.to_tensor(x))
 
-                    with _test_eager_guard():
-                        bn = paddle.nn.BatchNorm2D(shape[1])
-                        eag_y = bn(paddle.to_tensor(x))
+                    bn = paddle.nn.BatchNorm2D(shape[1])
+                    eag_y = bn(paddle.to_tensor(x))
                     assert np.allclose(eag_y.numpy(), y.numpy())
                 return y.numpy()
 

python/paddle/fluid/tests/unittests/test_bce_with_logits_loss.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 call_bce_layer(
@@ -172,15 +171,6 @@ class TestBCEWithLogitsLoss(unittest.TestCase):
                     functional=True,
                 )
 
-                with _test_eager_guard():
-                    eager_functional = test_dygraph(
-                        place,
-                        logit_np,
-                        label_np,
-                        reduction=reduction,
-                        functional=True,
-                    )
-
                 np.testing.assert_allclose(
                     static_functional, expected, rtol=1e-05
                 )
@@ -188,9 +178,6 @@ class TestBCEWithLogitsLoss(unittest.TestCase):
                     static_functional, dy_functional, rtol=1e-05
                 )
                 np.testing.assert_allclose(dy_functional, expected, rtol=1e-05)
-                np.testing.assert_allclose(
-                    eager_functional, expected, rtol=1e-05
-                )
 
     def test_BCEWithLogitsLoss_weight(self):
         logit_np = np.random.uniform(0.1, 0.8, size=(2, 3, 4, 10)).astype(

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

@@ -18,7 +18,6 @@ import numpy as np
 
 import paddle
 import paddle.nn.functional as F
-from paddle.fluid.framework import _test_eager_guard
 from paddle.incubate.optimizer.functional.bfgs import minimize_bfgs
 
 np.random.seed(123)
@@ -125,7 +124,7 @@ class TestBfgs(unittest.TestCase):
         results = test_static_graph(func, x0, dtype='float64')
         np.testing.assert_allclose(0.8, results[2], rtol=1e-05, atol=1e-8)
 
-    def func_rosenbrock(self):
+    def test_rosenbrock(self):
         # The Rosenbrock function is a standard optimization test case.
         a = np.random.random(size=[1]).astype('float32')
         minimum = [a.item(), (a**2).item()]
@@ -144,11 +143,6 @@ class TestBfgs(unittest.TestCase):
         results = test_dynamic_graph(func, x0)
         np.testing.assert_allclose(minimum, results[2], rtol=1e-05, atol=1e-8)
 
-    def test_rosenbrock(self):
-        with _test_eager_guard():
-            self.func_rosenbrock()
-        self.func_rosenbrock()
-
     def test_exception(self):
         def func(x):
             return paddle.dot(x, x)

python/paddle/fluid/tests/unittests/test_bicubic_interp_v2_op.py

@@ -20,7 +20,6 @@ from op_test import OpTest
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid import Program, program_guard
-from paddle.fluid.framework import _test_eager_guard
 from paddle.nn.functional import interpolate
 
 
@@ -363,12 +362,7 @@ class TestBicubicInterpDataLayout(TestBicubicInterpOp):
 
 
 class TestBicubicInterpOpAPI(unittest.TestCase):
-    def test_imperative_case(self):
-        with _test_eager_guard():
-            self.func_case()
-        self.func_case()
-
-    def func_case(self):
+    def test_case(self):
         np.random.seed(200)
         x_data = np.random.random((2, 3, 6, 6)).astype("float32")
         dim_data = np.array([12]).astype("int32")

python/paddle/nn/functional/loss.py

@@ -813,7 +813,7 @@ def binary_cross_entropy_with_logits(
         one = _C_ops.full(
             [1],
             float(1.0),
-            core.VarDesc.VarType.FP32,
+            logit.dtype,
             _current_expected_place(),
         )
         out = _C_ops.sigmoid_cross_entropy_with_logits(