rm _disable_legacy_dygraph and disable one mkldnn test file (#48721)

* rm _disable_legacy_dygraph

* disable test_flags_mkldnn_ops_on_off test

python/paddle/fluid/tests/unittests/mkldnn/CMakeLists.txt

@@ -5,6 +5,7 @@ file(
 string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
 
 list(REMOVE_ITEM TEST_OPS "test_onnx_format_quantization_mobilenetv1")
+list(REMOVE_ITEM TEST_OPS "test_flags_mkldnn_ops_on_off")
 
 if(WITH_MKLDNN AND NOT WIN32)
   list(APPEND TEST_OPS "test_onnx_format_quantization_mobilenetv1")
@@ -19,4 +20,4 @@ if(WITH_MKLDNN AND NOT WIN32)
   set_tests_properties(test_onnx_format_quantization_mobilenetv1
                        PROPERTIES TIMEOUT 300)
 endif()
-set_tests_properties(test_flags_mkldnn_ops_on_off PROPERTIES TIMEOUT 120)
+# set_tests_properties(test_flags_mkldnn_ops_on_off PROPERTIES TIMEOUT 120)

python/paddle/fluid/tests/unittests/mkldnn/check_flags_mkldnn_ops_on_off.py

@@ -18,11 +18,9 @@ import numpy as np
 
 import paddle
 import paddle.fluid as fluid
-from paddle.fluid.framework import _enable_legacy_dygraph, _global_flags
+from paddle.fluid.framework import _global_flags
 from paddle.fluid.layer_helper import LayerHelper
 
-_enable_legacy_dygraph()
-
 
 def check():
     print(

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

@@ -22,7 +22,6 @@ from decorator_helper import prog_scope
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
-import paddle.fluid.framework as framework
 import paddle.fluid.layers as layers
 from paddle.fluid import Program, program_guard
 from paddle.fluid.backward import append_backward
@@ -42,7 +41,6 @@ class TestAssignOp(op_test.OpTest):
         self.check_output(check_eager=True)
         fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
         paddle.disable_static()
-        framework._disable_legacy_dygraph()
 
     def test_backward(self):
         paddle.enable_static()
@@ -50,7 +48,6 @@ class TestAssignOp(op_test.OpTest):
         self.check_grad(['X'], 'Out', check_eager=True)
         fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
         paddle.disable_static()
-        framework._disable_legacy_dygraph()
 
 
 class TestAssignFP16Op(op_test.OpTest):
@@ -67,7 +64,6 @@ class TestAssignFP16Op(op_test.OpTest):
         self.check_output(check_eager=True)
         fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
         paddle.disable_static()
-        framework._disable_legacy_dygraph()
 
     def test_backward(self):
         paddle.enable_static()
@@ -75,7 +71,6 @@ class TestAssignFP16Op(op_test.OpTest):
         self.check_grad(['X'], 'Out', check_eager=True)
         fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
         paddle.disable_static()
-        framework._disable_legacy_dygraph()
 
 
 class TestAssignOpWithLoDTensorArray(unittest.TestCase):

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

@@ -22,15 +22,12 @@ import paddle.fluid.core as core
 from paddle.fluid.framework import (
     EagerParamBase,
     _current_expected_place,
-    _disable_legacy_dygraph,
-    _test_eager_guard,
     in_dygraph_mode,
 )
 
 
 class EagerScaleTestCase(unittest.TestCase):
     def test_scale_base(self):
-        with _test_eager_guard():
         paddle.set_device("cpu")
         arr = np.ones([4, 16, 16, 32]).astype('float32')
         tensor = paddle.to_tensor(arr, 'float32', core.CPUPlace())
@@ -43,7 +40,6 @@ class EagerScaleTestCase(unittest.TestCase):
         self.assertEqual(tensor.stop_gradient, True)
 
     def test_retain_grad_and_run_backward(self):
-        with _test_eager_guard():
         paddle.set_device("cpu")
 
         input_data = np.ones([4, 16, 16, 32]).astype('float32')
@@ -63,7 +59,6 @@ class EagerScaleTestCase(unittest.TestCase):
         np.testing.assert_array_equal(data_eager.grad.numpy(), input_data)
 
     def test_retain_grad_and_run_backward_raises(self):
-        with _test_eager_guard():
         paddle.set_device("cpu")
 
         input_data = np.ones([4, 16, 16, 32]).astype('float32')
@@ -74,9 +69,7 @@ class EagerScaleTestCase(unittest.TestCase):
         grad_data = np.ones([4, 16, 16, 32]).astype('float32')
         grad_data2 = np.ones([4, 16]).astype('float32')
         grad_eager = paddle.to_tensor(grad_data, 'float32', core.CPUPlace())
-            grad_eager2 = paddle.to_tensor(
-                grad_data2, 'float32', core.CPUPlace()
-            )
+        grad_eager2 = paddle.to_tensor(grad_data2, 'float32', core.CPUPlace())
 
         data_eager.retain_grads()
 
@@ -96,7 +89,6 @@ class EagerScaleTestCase(unittest.TestCase):
 
 class EagerDtypeTestCase(unittest.TestCase):
     def check_to_tesnsor_and_numpy(self, dtype, proto_dtype):
-        with _test_eager_guard():
         arr = np.random.random([4, 16, 16, 32]).astype(dtype)
         tensor = paddle.to_tensor(arr, dtype)
         self.assertEqual(tensor.dtype, proto_dtype)
@@ -315,7 +307,7 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         place_list = [core.CPUPlace()]
         if core.is_compiled_with_cuda():
             place_list.append(core.CUDAPlace(0))
-        with _test_eager_guard():
+
         for p in place_list:
             self.constructor(p)
 
@@ -639,13 +631,13 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         place_list = [core.CPUPlace()]
         if core.is_compiled_with_cuda():
             place_list.append(core.CUDAPlace(0))
-        with _test_eager_guard():
+
         for p in place_list:
             self.constructor_with_kwargs(p)
 
     def test_copy_and_copy_to(self):
         print("Test_copy_and_copy_to")
-        with _test_eager_guard():
+
         paddle.set_device("cpu")
         arr = np.ones([4, 16, 16, 32]).astype('float32')
         arr1 = np.zeros([4, 16]).astype('float32')
@@ -701,9 +693,7 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
 
             tensor10 = paddle.to_tensor([1, 2, 3], place='gpu_pinned')
             tensor11 = tensor10._copy_to(core.CUDAPlace(0), True)
-                np.testing.assert_array_equal(
-                    tensor10.numpy(), tensor11.numpy()
-                )
+            np.testing.assert_array_equal(tensor10.numpy(), tensor11.numpy())
         else:
             tensor3 = tensor2._copy_to(core.CPUPlace(), True)
             np.testing.assert_array_equal(tensor3.numpy(), arr2)
@@ -718,7 +708,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
             self.assertTrue(tensor4.place.is_cpu_place())
 
     def test_share_buffer_to(self):
-        with _test_eager_guard():
         arr = np.ones([4, 16, 16, 32]).astype('float32')
         arr1 = np.zeros([4, 16]).astype('float32')
         arr2 = np.ones([4, 16, 16, 32]).astype('float32') + np.ones(
@@ -750,7 +739,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         self.assertTrue(tensor3._is_shared_buffer_with(tensor))
 
     def test_share_underline_tensor_to(self):
-        with _test_eager_guard():
         arr = np.ones([4, 16, 16, 32]).astype('float32')
         arr1 = np.zeros([4, 16]).astype('float32')
         arr2 = np.ones([4, 16, 16, 32]).astype('float32') + np.ones(
@@ -783,7 +771,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
 
     def test_properties(self):
         print("Test_properties")
-        with _test_eager_guard():
         paddle.set_device("cpu")
         arr = np.ones([4, 16, 16, 32]).astype('float32')
         tensor = paddle.to_tensor(
@@ -808,11 +795,7 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
 
     def test_global_properties(self):
         print("Test_global_properties")
-        _disable_legacy_dygraph()
         self.assertTrue(in_dygraph_mode())
-        with _test_eager_guard():
-            self.assertTrue(in_dygraph_mode())
-        self.assertFalse(in_dygraph_mode())
 
     def test_place_guard(self):
         if core.is_compiled_with_cuda():
@@ -829,7 +812,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
                 )
 
     def test_value(self):
-        with _test_eager_guard():
         arr = np.random.rand(4, 16, 16, 32).astype('float64')
 
         egr_tensor0 = core.eager.Tensor(value=arr)
@@ -854,7 +836,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         self.assertTrue(egr_tensor0.value().get_tensor()._is_initialized())
 
     def test_set_value(self):
-        with _test_eager_guard():
         ori_arr = np.random.rand(4, 16, 16, 32).astype('float32')
         egr_tensor = core.eager.Tensor(value=ori_arr)
         self.assertEqual(egr_tensor.stop_gradient, True)
@@ -872,7 +853,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         np.testing.assert_array_equal(egr_tensor.numpy(), new_arr)
 
     def test_sharding_related_api(self):
-        with _test_eager_guard():
         arr0 = np.random.rand(4, 16, 16, 32).astype('float32')
         egr_tensor1 = core.eager.Tensor(
             arr0, core.CPUPlace(), True, False, "numpy_tensor1", False
@@ -881,7 +861,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         self.assertEqual(egr_tensor1._slice(0, 2)._numel(), 16384)
 
     def test_copy_gradient_from(self):
-        with _test_eager_guard():
         np_x = np.random.random((2, 2))
         np_y = np.random.random((2, 2))
         x = paddle.to_tensor(np_x, dtype="float64", stop_gradient=False)
@@ -892,7 +871,6 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         np.testing.assert_array_equal(x.grad.numpy(), np_y)
 
     def test_clear(self):
-        with _test_eager_guard():
         np_x = np.random.random((3, 8, 8))
         x = paddle.to_tensor(np_x, dtype="float64")
         self.assertTrue(x._is_initialized())
@@ -901,7 +879,7 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
 
     def test_use_gpudnn(self):
         np_x = np.random.random((3, 8, 8))
-        with _test_eager_guard():
+
         self.assertTrue(in_dygraph_mode())
         x = paddle.to_tensor(np_x, dtype="float64")
         y = x._use_gpudnn(False)
@@ -909,20 +887,13 @@ class EagerVariablePropertiesAndMethodsTestCase(unittest.TestCase):
         y = x._use_gpudnn(True)
         np.testing.assert_array_equal(x.numpy(), y.numpy())
 
-        self.assertFalse(in_dygraph_mode())
-        x = paddle.to_tensor(np_x, dtype="float64")
-        with self.assertRaises(AttributeError):
-            x = x._use_gpudnn(False)
-
 
 class EagerParamBaseUsageTestCase(unittest.TestCase):
     def test_print(self):
-        with _test_eager_guard():
         linear = paddle.nn.Linear(3, 3, bias_attr=False)
         print(linear.weight)
 
     def test_copy(self):
-        with _test_eager_guard():
         linear = paddle.nn.Linear(1, 3)
         linear_copy = copy.deepcopy(linear)
         linear_copy2 = linear.weight._copy_to(core.CPUPlace(), True)
@@ -963,18 +934,6 @@ class EagerParamBaseUsageTestCase(unittest.TestCase):
         paddle.set_default_dtype("float32")
         return res
 
-    def test_fp16_initializer(self):
-        res1 = list()
-        res2 = list()
-        paddle.seed(102)
-        paddle.framework.random._manual_program_seed(102)
-        with _test_eager_guard():
-            res1 = self.func_fp16_initilaizer()
-        res2 = self.func_fp16_initilaizer()
-
-        for i in range(len(res1)):
-            np.testing.assert_array_equal(res1[i], res2[i])
-
     def func_layer_helper_base(self, value):
         base = paddle.fluid.layer_helper_base.LayerHelperBase(
             "test_layer", "test_layer"
@@ -984,20 +943,7 @@ class EagerParamBaseUsageTestCase(unittest.TestCase):
     def func_base_to_variable(self, value):
         paddle.fluid.dygraph.base.to_variable(value)
 
-    def test_to_variable(self):
-        value = np.random.rand(4, 16, 16, 32).astype('float32')
-        res1 = None
-        res3 = None
-        with _test_eager_guard():
-            res1 = self.func_layer_helper_base(value)
-            res3 = self.func_base_to_variable(value)
-        res2 = self.func_layer_helper_base(value)
-        res4 = self.func_base_to_variable(value)
-        np.testing.assert_array_equal(res1, res2)
-        np.testing.assert_array_equal(res3, res4)
-
     def test_backward_with_single_tensor(self):
-        with _test_eager_guard():
         arr4 = np.random.rand(4, 16, 16, 32).astype('float32')
         egr_tensor12 = core.eager.Tensor(arr4, core.CPUPlace())
         egr_tensor12.retain_grads()
@@ -1015,7 +961,6 @@ class EagerParamBaseUsageTestCase(unittest.TestCase):
         np.testing.assert_array_equal(egr_tensor12.gradient(), arr)
 
     def test_set_value(self):
-        with _test_eager_guard():
         linear = paddle.nn.Linear(1, 3)
         ori_place = linear.weight.place
         new_weight = np.ones([1, 3]).astype('float32')
@@ -1026,12 +971,5 @@ class EagerParamBaseUsageTestCase(unittest.TestCase):
         self.assertTrue(linear.weight.place._equals(ori_place))
 
 
-class EagerGuardTestCase(unittest.TestCase):
-    def test__test_eager_guard(self):
-        tracer = paddle.fluid.dygraph.tracer.Tracer()
-        with _test_eager_guard(tracer):
-            self.assertTrue(in_dygraph_mode())
-
-
 if __name__ == "__main__":
     unittest.main()

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

@@ -73,7 +73,6 @@ class LinalgLstsqTestCase(unittest.TestCase):
 
     def test_eager_dygraph(self):
         paddle.disable_static()
-        paddle.fluid.framework._disable_legacy_dygraph()
         for dev in self.devices:
             paddle.set_device(dev)
             place = paddle.CPUPlace() if dev == "cpu" else paddle.CUDAPlace(0)