all cases use large shape (#22065)

affine_channel, affine_grid, bilinear_interp, bilinear_tensor_product,
clip, crop, crop_tensor, cumsum, data_norm, expand, expand_as

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

@@ -62,15 +62,15 @@ class TestAffineChannelOp(OpTest):
         self.check_grad(['X'], 'Out', no_grad_set=set(['Scale', 'Bias']))
 
     def init_test_case(self):
-        self.shape = [2, 8, 12, 12]
-        self.C = 8
+        self.shape = [2, 100, 12, 12]
+        self.C = 100
         self.layout = 'NCHW'
 
 
 class TestAffineChannelNHWC(TestAffineChannelOp):
     def init_test_case(self):
-        self.shape = [2, 12, 12, 16]
-        self.C = 16
+        self.shape = [2, 12, 12, 100]
+        self.C = 100
         self.layout = 'NHWC'
 
     def test_check_grad_stopgrad_dx(self):
@@ -82,8 +82,8 @@ class TestAffineChannelNHWC(TestAffineChannelOp):
 
 class TestAffineChannel2D(TestAffineChannelOp):
     def init_test_case(self):
-        self.shape = [8, 32]
-        self.C = 32
+        self.shape = [8, 100]
+        self.C = 100
         self.layout = 'NCHW'
 
     def test_check_grad_stopgrad_dx(self):

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

@@ -66,8 +66,8 @@ class TestAffineGridOp(OpTest):
 
 class TestAffineGridOpCase1(TestAffineGridOp):
     def initTestCase(self):
-        self.theta_shape = (3, 2, 3)
-        self.output_shape = np.array([3, 2, 5, 7]).astype("int32")
+        self.theta_shape = (20, 2, 3)
+        self.output_shape = np.array([20, 2, 5, 7]).astype("int32")
         self.dynamic_shape = True
 
 

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

@@ -144,7 +144,7 @@ class TestBilinearInterpOp(OpTest):
 
     def init_test_case(self):
         self.interp_method = 'bilinear'
-        self.input_shape = [2, 3, 4, 4]
+        self.input_shape = [2, 3, 5, 5]
         self.out_h = 2
         self.out_w = 2
         self.scale = 0.
@@ -248,7 +248,7 @@ class TestBilinearInterpActualShape(TestBilinearInterpOp):
 class TestBilinearInterpDataLayout(TestBilinearInterpOp):
     def init_test_case(self):
         self.interp_method = 'bilinear'
-        self.input_shape = [2, 4, 4, 3]
+        self.input_shape = [2, 5, 5, 3]
         self.out_h = 2
         self.out_w = 2
         self.scale = 0.
@@ -438,7 +438,7 @@ class TestBilinearInterpOp_attr_tensor(OpTest):
 
     def init_test_case(self):
         self.interp_method = 'bilinear'
-        self.input_shape = [2, 3, 4, 4]
+        self.input_shape = [2, 3, 5, 5]
         self.out_h = 3
         self.out_w = 3
         self.scale = 0.

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

@@ -23,9 +23,9 @@ class TestBilinearTensorProductOp(OpTest):
     def setUp(self):
         self.op_type = "bilinear_tensor_product"
         batch_size = 6
-        size0 = 5
-        size1 = 4
-        size2 = 5
+        size0 = 30
+        size1 = 20
+        size2 = 100
         a = np.random.random((batch_size, size0)).astype("float64")
         b = np.random.random((batch_size, size1)).astype("float64")
         w = np.random.random((size2, size0, size1)).astype("float64")

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

@@ -43,7 +43,7 @@ class TestClipOp(OpTest):
         self.check_grad(['X'], 'Out')
 
     def initTestCase(self):
-        self.shape = (4, 4)
+        self.shape = (10, 10)
         self.max = 0.7
         self.min = 0.1
 

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

@@ -66,7 +66,7 @@ class TestCropOp(OpTest):
         }
 
     def initTestCase(self):
-        self.x_shape = (8, 8)
+        self.x_shape = (10, 10)
         self.crop_shape = (2, 2)
         self.offsets = [1, 2]
 
@@ -86,8 +86,8 @@ class TestCase1(TestCropOp):
 
 class TestCase2(TestCropOp):
     def initTestCase(self):
-        self.x_shape = (4, 8)
-        self.crop_shape = [4, 8]
+        self.x_shape = (15, 8)
+        self.crop_shape = [15, 8]
         self.offsets = [0, 0]
 
 
@@ -101,15 +101,15 @@ class TestCase3(TestCropOp):
 
 class TestCase4(TestCropOp):
     def initTestCase(self):
-        self.x_shape = (4, 4)
-        self.crop_shape = [4, 4]
+        self.x_shape = (10, 10)
+        self.crop_shape = [10, 10]
         self.offsets = [0, 0]
         self.crop_by_input = True
 
 
 class TestCase5(TestCropOp):
     def initTestCase(self):
-        self.x_shape = (3, 4, 5)
+        self.x_shape = (3, 4, 10)
         self.crop_shape = [2, 2, 3]
         self.offsets = [1, 0, 2]
         self.offset_by_input = True

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

@@ -72,7 +72,7 @@ class TestCropTensorOp(OpTest):
         self.outputs = {'Out': crop(self.inputs['X'], self.offsets, crop_shape)}
 
     def initTestCase(self):
-        self.x_shape = (8, 8)
+        self.x_shape = (10, 10)
         self.crop_shape = [2, 2]
         self.offsets = [1, 2]
 
@@ -169,7 +169,7 @@ class TestCropTensorOpTensorAttr(OpTest):
         self.outputs = {'Out': crop(self.inputs['X'], self.offsets, crop_shape)}
 
     def initTestCase(self):
-        self.x_shape = (8, 8)
+        self.x_shape = (10, 10)
         self.crop_shape = (2, 2)
         self.offsets = [1, 2]
         self.shape_attr = [0, 0]

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

@@ -82,7 +82,7 @@ class TestSumOp4(OpTest):
 class TestSumOp5(OpTest):
     def setUp(self):
         self.op_type = "cumsum"
-        self.inputs = {'X': np.random.random((5, 6)).astype("float64")}
+        self.inputs = {'X': np.random.random((5, 20)).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=1)}
 
     def test_check_output(self):
@@ -95,7 +95,7 @@ class TestSumOp5(OpTest):
 class TestSumOp7(OpTest):
     def setUp(self):
         self.op_type = "cumsum"
-        self.inputs = {'X': np.random.random((6)).astype("float64")}
+        self.inputs = {'X': np.random.random((100)).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=0)}
 
     def test_check_output(self):
@@ -109,7 +109,7 @@ class TestSumOp8(OpTest):
     def setUp(self):
         self.op_type = "cumsum"
         self.attrs = {'axis': 2, "exclusive": True}
-        a = np.random.random((5, 6, 3)).astype("float64")
+        a = np.random.random((5, 6, 4)).astype("float64")
         self.inputs = {'X': a}
         self.outputs = {
             'Out': np.concatenate(

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

@@ -234,12 +234,11 @@ class TestDataNormOpWithSlotDim(OpTest):
         self.use_mkldnn = False
         epsilon = 0.00001
         slot_dim = 1
-        x_shape = [2, 3]
-        scale_shape = [3]
+        x_shape = [2, 50]
+        scale_shape = [50]
         tp = np.float32
 
-        x_val = np.array([[-0.35702616, 0.0, -0.08306625],
-                          [0.41199666, 0.0, -0.10180971]]).astype(tp)
+        x_val = np.random.uniform(-1, 1, x_shape).astype(tp)
         batch_size = np.ones(scale_shape).astype(tp)
         batch_size *= 1e4
         batch_sum = np.zeros(scale_shape).astype(tp)
@@ -248,8 +247,8 @@ class TestDataNormOpWithSlotDim(OpTest):
 
         y = np.array(x_val)
 
-        mean = np.array([[0, 0, 0], [0, 0, 0]]).astype(tp)
-        scale = np.array([[1, 1, 1], [1, 1, 1]]).astype(tp)
+        mean = np.zeros(x_shape).astype(tp)
+        scale = np.ones(x_shape).astype(tp)
 
         self.inputs = {
             "X": x_val,

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

@@ -51,8 +51,8 @@ class TestExpandAsOpRank1(OpTest):
 class TestExpandAsOpRank2(OpTest):
     def setUp(self):
         self.op_type = "expand_as"
-        x = np.random.rand(2, 3).astype("float64")
-        target_tensor = np.random.rand(4, 6).astype("float64")
+        x = np.random.rand(10, 12).astype("float64")
+        target_tensor = np.random.rand(20, 24).astype("float64")
         self.inputs = {'X': x, 'target_tensor': target_tensor}
         self.attrs = {}
         bcast_dims = bcast(x, target_tensor)
@@ -69,8 +69,8 @@ class TestExpandAsOpRank2(OpTest):
 class TestExpandAsOpRank3(OpTest):
     def setUp(self):
         self.op_type = "expand_as"
-        x = np.random.rand(2, 3, 3).astype("float64")
-        target_tensor = np.random.rand(4, 6, 6).astype("float64")
+        x = np.random.rand(2, 3, 20).astype("float64")
+        target_tensor = np.random.rand(4, 6, 40).astype("float64")
         self.inputs = {'X': x, 'target_tensor': target_tensor}
         self.attrs = {}
         bcast_dims = bcast(x, target_tensor)
@@ -87,8 +87,8 @@ class TestExpandAsOpRank3(OpTest):
 class TestExpandAsOpRank4(OpTest):
     def setUp(self):
         self.op_type = "expand_as"
-        x = np.random.rand(1, 1, 3, 16).astype("float64")
-        target_tensor = np.random.rand(4, 6, 6, 32).astype("float64")
+        x = np.random.rand(1, 1, 7, 16).astype("float64")
+        target_tensor = np.random.rand(4, 6, 14, 32).astype("float64")
         self.inputs = {'X': x, 'target_tensor': target_tensor}
         self.attrs = {}
         bcast_dims = bcast(x, target_tensor)

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

@@ -45,7 +45,7 @@ class TestExpandOpRank1(OpTest):
 
 class TestExpandOpRank2_Corner(TestExpandOpRank1):
     def init_data(self):
-        self.ori_shape = [12]
+        self.ori_shape = [120]
         self.expand_times = [2]
 
 
@@ -57,13 +57,13 @@ class TestExpandOpRank2(TestExpandOpRank1):
 
 class TestExpandOpRank3_Corner(TestExpandOpRank1):
     def init_data(self):
-        self.ori_shape = (2, 4, 5)
+        self.ori_shape = (2, 10, 5)
         self.expand_times = (1, 1, 1)
 
 
 class TestExpandOpRank3(TestExpandOpRank1):
     def init_data(self):
-        self.ori_shape = (2, 4, 5)
+        self.ori_shape = (2, 4, 15)
         self.expand_times = (2, 1, 4)
 
 
@@ -92,7 +92,7 @@ class TestExpandOpRank1_tensor_attr(OpTest):
         self.outputs = {'Out': output}
 
     def init_data(self):
-        self.ori_shape = [12]
+        self.ori_shape = [100]
         self.expand_times = [2]
         self.infer_expand_times = [-1]
 
@@ -132,7 +132,7 @@ class TestExpandOpRank1_tensor(OpTest):
         self.outputs = {'Out': output}
 
     def init_data(self):
-        self.ori_shape = [12]
+        self.ori_shape = [100]
         self.expand_times = [2]
 
     def test_check_output(self):