Del old dygraph optest2 (#51458)

* delete old dygraph op test

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

@@ -437,6 +437,7 @@ class TestMKLDNNExpOp(TestActivation):
 # Check if primitives already exist in backward
 class TestMKLDNNAbsPrimitivesAlreadyExist(unittest.TestCase):
     def setUp(self):
+        paddle.enable_static()
         super().setUp()
 
         np.random.seed(123)

python/paddle/fluid/tests/unittests/test_atan2_op.py

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid.core as core
@@ -44,10 +44,10 @@ class TestAtan2(OpTest):
         self.outputs = {'Out': out}
 
     def test_check_grad(self):
-        self.check_grad(['X1', 'X2'], 'Out', check_eager=True)
+        self.check_grad(['X1', 'X2'], 'Out')
 
     def test_check_output(self):
-        self.check_output(check_eager=True)
+        self.check_output()
 
     def init_dtype(self):
         self.dtype = np.float64
@@ -67,7 +67,6 @@ class TestAtan2_float(TestAtan2):
                     self.inputs['X2'],
                     1 / self.inputs['X1'].size,
                 ),
-                check_eager=True,
             )
 
 

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 from test_fusion_lstm_op import ACTIVATION, fc
 from test_softmax_op import stable_softmax
 

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
@@ -65,7 +65,7 @@ class TestAucOp(OpTest):
         }
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_dygraph=False)
 
 
 class TestGlobalAucOp(OpTest):
@@ -105,7 +105,7 @@ class TestGlobalAucOp(OpTest):
         }
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_dygraph=False)
 
 
 class TestAucAPI(unittest.TestCase):

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 from paddle.fluid import metrics
 
@@ -66,7 +66,7 @@ class TestAucSinglePredOp(OpTest):
         }
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_dygraph=False)
 
 
 class TestAucGlobalSinglePredOp(OpTest):
@@ -109,7 +109,7 @@ class TestAucGlobalSinglePredOp(OpTest):
         }
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_dygraph=False)
 
 
 if __name__ == "__main__":

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle.fluid.core as core
 

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

@@ -16,7 +16,7 @@ import os
 import unittest
 
 import numpy as np
-from op_test import OpTest, _set_use_system_allocator
+from eager_op_test import OpTest, _set_use_system_allocator
 
 import paddle
 import paddle.fluid as fluid

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
@@ -135,8 +135,6 @@ class TestBicubicInterpOp(OpTest):
         self.init_test_case()
         self.op_type = "bicubic_interp"
         # NOTE(dev): some AsDispensible input is not used under imperative mode.
-        # Skip check_eager while found them in Inputs.
-        self.check_eager = True
         input_np = np.random.random(self.input_shape).astype("float64")
 
         if self.data_layout == "NCHW":
@@ -165,10 +163,8 @@ class TestBicubicInterpOp(OpTest):
         self.inputs = {'X': input_np}
         if self.out_size is not None:
             self.inputs['OutSize'] = self.out_size
-            self.check_eager = False
         if self.actual_shape is not None:
             self.inputs['OutSize'] = self.actual_shape
-            self.check_eager = False
 
         self.attrs = {
             'out_h': self.out_h,
@@ -181,12 +177,10 @@ class TestBicubicInterpOp(OpTest):
         self.outputs = {'Out': output_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=self.check_eager)
+        self.check_output()
 
     def test_check_grad(self):
-        self.check_grad(
-            ['X'], 'Out', in_place=True, check_eager=self.check_eager
-        )
+        self.check_grad(['X'], 'Out', in_place=True)
 
     def init_test_case(self):
         self.interp_method = 'bicubic'

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
@@ -186,8 +186,6 @@ class TestBicubicInterpOp(OpTest):
         self.init_test_case()
         self.op_type = "bicubic_interp_v2"
         # NOTE(dev): some AsDispensible input is not used under imperative mode.
-        # Skip check_eager while found them in Inputs.
-        self.check_eager = True
         input_np = np.random.random(self.input_shape).astype("float64")
         scale_h = 0
         scale_w = 0
@@ -227,10 +225,8 @@ class TestBicubicInterpOp(OpTest):
         self.inputs = {'X': input_np}
         if self.out_size is not None:
             self.inputs['OutSize'] = self.out_size
-            self.check_eager = False
         if self.actual_shape is not None:
             self.inputs['OutSize'] = self.actual_shape
-            self.check_eager = False
 
         self.attrs = {
             'out_h': self.out_h,
@@ -249,12 +245,10 @@ class TestBicubicInterpOp(OpTest):
         self.outputs = {'Out': output_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=self.check_eager)
+        self.check_output()
 
     def test_check_grad(self):
-        self.check_grad(
-            ['X'], 'Out', in_place=True, check_eager=self.check_eager
-        )
+        self.check_grad(['X'], 'Out', in_place=True)
 
     def init_test_case(self):
         self.interp_method = 'bicubic'

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

@@ -16,7 +16,7 @@ import math
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest, paddle_static_guard
 
 import paddle
 
@@ -192,26 +192,27 @@ class TestBilateralSliceOp1(TestBilateralSliceOp):
 
 class TestBilateralSliceApi(unittest.TestCase):
     def test_api(self):
-        x = paddle.fluid.data(
-            name='x', shape=[None, 3, 25, 15], dtype='float32'
-        )
-        guide = paddle.fluid.data(
-            name='guide', shape=[None, 25, 15], dtype='float32'
-        )
-        grid = paddle.fluid.data(
-            name='grid', shape=[None, None, 8, 5, 3], dtype='float32'
-        )
-        paddle.fluid.contrib.layers.bilateral_slice(x, guide, grid, False)
-
-        if not paddle.fluid.is_compiled_with_cuda():
-            return
-
-        with paddle.fluid.dygraph.guard():
-            x1 = paddle.rand([3, 1, 50, 30])
-            guide1 = paddle.rand([3, 50, 30])
-            grid1 = paddle.rand([3, 2, 2, 5, 3])
-
-            paddle.fluid.contrib.bilateral_slice(x1, guide1, grid1, False)
+        with paddle_static_guard():
+            x = paddle.fluid.data(
+                name='x', shape=[None, 3, 25, 15], dtype='float32'
+            )
+            guide = paddle.fluid.data(
+                name='guide', shape=[None, 25, 15], dtype='float32'
+            )
+            grid = paddle.fluid.data(
+                name='grid', shape=[None, None, 8, 5, 3], dtype='float32'
+            )
+            paddle.fluid.contrib.layers.bilateral_slice(x, guide, grid, False)
+
+            if not paddle.fluid.is_compiled_with_cuda():
+                return
+
+            with paddle.fluid.dygraph.guard():
+                x1 = paddle.rand([3, 1, 50, 30])
+                guide1 = paddle.rand([3, 50, 30])
+                grid1 = paddle.rand([3, 2, 2, 5, 3])
+
+                paddle.fluid.contrib.bilateral_slice(x1, guide1, grid1, False)
 
 
 if __name__ == "__main__":

python/paddle/fluid/tests/unittests/test_bilinear_interp_v2_op.py

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
@@ -219,10 +219,10 @@ class TestBilinearInterpOp(OpTest):
         self.outputs = {'Out': output_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=True)
+        self.check_output()
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out', in_place=True, check_eager=True)
+        self.check_grad(['X'], 'Out', in_place=True)
 
     def init_test_case(self):
         self.interp_method = 'bilinear'
@@ -409,9 +409,7 @@ class TestBilinearInterpOpUint8(OpTest):
         self.outputs = {'Out': output_np}
 
     def test_check_output(self):
-        self.check_output_with_place(
-            place=core.CPUPlace(), atol=1, check_eager=True
-        )
+        self.check_output_with_place(place=core.CPUPlace(), atol=1)
 
     def init_test_case(self):
         self.interp_method = 'bilinear'
@@ -585,10 +583,10 @@ class TestBilinearInterpOp_attr_tensor(OpTest):
         self.outputs = {'Out': output_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=True)
+        self.check_output()
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out', in_place=True, check_eager=True)
+        self.check_grad(['X'], 'Out', in_place=True)
 
     def init_test_case(self):
         self.interp_method = 'bilinear'

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest, paddle_static_guard
 
 import paddle
 import paddle.fluid as fluid
@@ -23,28 +23,29 @@ import paddle.fluid as fluid
 
 class TestDygraphBilinearTensorProductAPIError(unittest.TestCase):
     def test_errors(self):
-        with fluid.program_guard(fluid.Program(), fluid.Program()):
-            layer = paddle.nn.Bilinear(5, 4, 1000)
-            # the input must be Variable.
-            x0 = fluid.create_lod_tensor(
-                np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace()
-            )
-            self.assertRaises(TypeError, layer, x0)
-            # the input dtype must be float32 or float64
-            x1 = fluid.data(name='x1', shape=[-1, 5], dtype="float16")
-            x2 = fluid.data(name='x2', shape=[-1, 4], dtype="float32")
-            self.assertRaises(TypeError, layer, x1, x2)
-            # the dimensions of x and y must be 2
-            paddle.enable_static()
-            x3 = paddle.static.data("", shape=[0], dtype="float32")
-            x4 = paddle.static.data("", shape=[0], dtype="float32")
-            self.assertRaises(
-                ValueError,
-                paddle.static.nn.bilinear_tensor_product,
-                x3,
-                x4,
-                1000,
-            )
+        with paddle_static_guard():
+            with fluid.program_guard(fluid.Program(), fluid.Program()):
+                layer = paddle.nn.Bilinear(5, 4, 1000)
+                # the input must be Variable.
+                x0 = fluid.create_lod_tensor(
+                    np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace()
+                )
+                self.assertRaises(TypeError, layer, x0)
+                # the input dtype must be float32 or float64
+                x1 = fluid.data(name='x1', shape=[-1, 5], dtype="float16")
+                x2 = fluid.data(name='x2', shape=[-1, 4], dtype="float32")
+                self.assertRaises(TypeError, layer, x1, x2)
+                # the dimensions of x and y must be 2
+                paddle.enable_static()
+                x3 = paddle.static.data("", shape=[0], dtype="float32")
+                x4 = paddle.static.data("", shape=[0], dtype="float32")
+                self.assertRaises(
+                    ValueError,
+                    paddle.static.nn.bilinear_tensor_product,
+                    x3,
+                    x4,
+                    1000,
+                )
 
 
 class TestBilinearTensorProductOp(OpTest):
@@ -73,10 +74,10 @@ class TestBilinearTensorProductOp(OpTest):
         self.outputs = {'Out': output + bias}
 
     def test_check_output(self):
-        self.check_output(check_eager=True)
+        self.check_output()
 
     def test_check_grad_normal(self):
-        self.check_grad(['X', 'Y', 'Weight', 'Bias'], 'Out', check_eager=True)
+        self.check_grad(['X', 'Y', 'Weight', 'Bias'], 'Out')
 
 
 if __name__ == "__main__":

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

@@ -17,7 +17,7 @@ import tempfile
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 import paddle
 import paddle.fluid as fluid
@@ -150,7 +150,7 @@ class TestBincountOp(OpTest):
         self.Out = np.bincount(self.np_input, minlength=self.minlength)
 
     def test_check_output(self):
-        self.check_output(check_eager=False)
+        self.check_output()
 
 
 class TestCase1(TestBincountOp):

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 
 def bipartite_match(distance, match_indices, match_dist):

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest, paddle_static_guard
 
 import paddle
 import paddle.fluid as fluid
@@ -32,31 +32,33 @@ class TestBmmOp(OpTest):
         self.outputs = {'Out': Out}
 
     def test_check_output(self):
-        self.check_output(check_eager=True)
+        self.check_output()
 
     def test_checkout_grad(self):
-        self.check_grad(['X', 'Y'], 'Out', check_eager=True)
+        self.check_grad(['X', 'Y'], 'Out')
 
 
 class API_TestBmm(unittest.TestCase):
     def test_out(self):
-        with fluid.program_guard(fluid.Program(), fluid.Program()):
-            data1 = paddle.static.data(
-                'data1', shape=[-1, 3, 4], dtype='float64'
-            )
-            data2 = paddle.static.data(
-                'data2', shape=[-1, 4, 5], dtype='float64'
-            )
-            result_bmm = paddle.bmm(data1, data2)
-            place = fluid.CPUPlace()
-            exe = fluid.Executor(place)
-            input1 = np.random.random([10, 3, 4]).astype('float64')
-            input2 = np.random.random([10, 4, 5]).astype('float64')
-            (result,) = exe.run(
-                feed={"data1": input1, "data2": input2}, fetch_list=[result_bmm]
-            )
-            expected_result = np.matmul(input1, input2)
-        np.testing.assert_allclose(expected_result, result, rtol=1e-05)
+        with paddle_static_guard():
+            with fluid.program_guard(fluid.Program(), fluid.Program()):
+                data1 = paddle.static.data(
+                    'data1', shape=[-1, 3, 4], dtype='float64'
+                )
+                data2 = paddle.static.data(
+                    'data2', shape=[-1, 4, 5], dtype='float64'
+                )
+                result_bmm = paddle.bmm(data1, data2)
+                place = fluid.CPUPlace()
+                exe = fluid.Executor(place)
+                input1 = np.random.random([10, 3, 4]).astype('float64')
+                input2 = np.random.random([10, 4, 5]).astype('float64')
+                (result,) = exe.run(
+                    feed={"data1": input1, "data2": input2},
+                    fetch_list=[result_bmm],
+                )
+                expected_result = np.matmul(input1, input2)
+            np.testing.assert_allclose(expected_result, result, rtol=1e-05)
 
 
 class API_TestDygraphBmm(unittest.TestCase):

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

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from eager_op_test import OpTest
 
 
 def box_clip(input_box, im_info, output_box):