fix input shape of op tests (#21682)

* fix input shape of op tests for elementwise_sub,
gather, pad2d, transpose, softmax, scale,
elementwise_max, hierarchical_sigmoid, reshape2,
sign, squeeze, reduce_sum, sum, squeeze2,
unsqueeze, unsqueeze2, cast, reverse

test=develop

* fix cast, elementwise_mul, gather, scale, sign,
softmax, transpose

test=develop

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

@@ -49,7 +49,7 @@ class TestElementwiseOp(OpTest):
 class TestElementwiseMaxOp_scalar(TestElementwiseOp):
     def setUp(self):
         self.op_type = "elementwise_max"
-        x = np.random.random_integers(-5, 5, [2, 3, 4]).astype("float32")
+        x = np.random.random_integers(-5, 5, [2, 3, 20]).astype("float32")
         y = np.array([0.5]).astype("float32")
         self.inputs = {'X': x, 'Y': y}
         self.outputs = {'Out': np.maximum(self.inputs['X'], self.inputs['Y'])}
@@ -58,9 +58,9 @@ class TestElementwiseMaxOp_scalar(TestElementwiseOp):
 class TestElementwiseMaxOp_Vector(TestElementwiseOp):
     def setUp(self):
         self.op_type = "elementwise_max"
-        x = np.random.random((32, )).astype("float32")
-        sgn = np.random.choice([-1, 1], (32, )).astype("float32")
-        y = x + sgn * np.random.uniform(0.1, 1, (32, )).astype("float32")
+        x = np.random.random((100, )).astype("float32")
+        sgn = np.random.choice([-1, 1], (100, )).astype("float32")
+        y = x + sgn * np.random.uniform(0.1, 1, (100, )).astype("float32")
         self.inputs = {'X': x, 'Y': y}
         self.outputs = {'Out': np.maximum(self.inputs['X'], self.inputs['Y'])}
 
@@ -68,7 +68,7 @@ class TestElementwiseMaxOp_Vector(TestElementwiseOp):
 class TestElementwiseMaxOp_broadcast_0(TestElementwiseOp):
     def setUp(self):
         self.op_type = "elementwise_max"
-        x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float32)
+        x = np.random.uniform(0.5, 1, (2, 3, 20)).astype(np.float32)
         sgn = np.random.choice([-1, 1], (2, )).astype(np.float32)
         y = x[:, 0, 0] + sgn * \
             np.random.uniform(1, 2, (2, )).astype(np.float32)
@@ -84,7 +84,7 @@ class TestElementwiseMaxOp_broadcast_0(TestElementwiseOp):
 class TestElementwiseMaxOp_broadcast_1(TestElementwiseOp):
     def setUp(self):
         self.op_type = "elementwise_max"
-        x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float32)
+        x = np.random.uniform(0.5, 1, (2, 3, 20)).astype(np.float32)
         sgn = np.random.choice([-1, 1], (3, )).astype(np.float32)
         y = x[0, :, 0] + sgn * \
             np.random.uniform(1, 2, (3, )).astype(np.float32)
@@ -100,7 +100,7 @@ class TestElementwiseMaxOp_broadcast_1(TestElementwiseOp):
 class TestElementwiseMaxOp_broadcast_2(TestElementwiseOp):
     def setUp(self):
         self.op_type = "elementwise_max"
-        x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float32)
+        x = np.random.uniform(0.5, 1, (10, 3, 4)).astype(np.float32)
         sgn = np.random.choice([-1, 1], (4, )).astype(np.float32)
         y = x[0, 0, :] + sgn * \
             np.random.uniform(1, 2, (4, )).astype(np.float32)

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

@@ -22,8 +22,8 @@ class TestElementwiseOp(OpTest):
     def setUp(self):
         self.op_type = "elementwise_sub"
         self.inputs = {
-            'X': np.random.uniform(0.1, 1, [2, 3]).astype("float32"),
-            'Y': np.random.uniform(0.1, 1, [2, 3]).astype("float32")
+            'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float32"),
+            'Y': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float32")
         }
         self.outputs = {'Out': self.inputs['X'] - self.inputs['Y']}
 

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

@@ -51,7 +51,7 @@ class TestCase1(TestGatherOp):
         """
         For one dimension input
         """
-        self.x_shape = (10)
+        self.x_shape = (100)
         self.x_type = "float32"
         self.index = [1, 3, 5]
         self.index_type = "int32"

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

@@ -147,7 +147,7 @@ class TestHSigmoidOp(OpTest):
         self.op_type = "hierarchical_sigmoid"
         num_classes = 6
         feature_size = 8
-        batch_size = 4
+        batch_size = 15
         x = np.random.random((batch_size, feature_size)).astype("float32") * 2
         w = np.random.random(
             (num_classes - 1, feature_size)).astype("float32") * 2

python/paddle/fluid/tests/unittests/test_pad2d_op.py

@@ -56,7 +56,7 @@ class TestPad2dOp(OpTest):
         self.check_grad(['X'], 'Out', max_relative_error=0.006)
 
     def initTestCase(self):
-        self.shape = (2, 3, 4, 4)
+        self.shape = (2, 3, 4, 5)
         self.paddings = [0, 1, 2, 3]
         self.mode = "constant"
         self.data_format = "NCHW"
@@ -65,7 +65,7 @@ class TestPad2dOp(OpTest):
 
 class TestCase1(TestPad2dOp):
     def initTestCase(self):
-        self.shape = (2, 3, 4, 4)
+        self.shape = (2, 3, 4, 5)
         self.paddings = [0, 1, 2, 3]
         self.mode = "reflect"
         self.data_format = "NCHW"
@@ -73,7 +73,7 @@ class TestCase1(TestPad2dOp):
 
 class TestCase2(TestPad2dOp):
     def initTestCase(self):
-        self.shape = (2, 3, 4, 4)
+        self.shape = (2, 3, 4, 5)
         self.paddings = [0, 1, 2, 3]
         self.mode = "edge"
         self.data_format = "NCHW"
@@ -81,7 +81,7 @@ class TestCase2(TestPad2dOp):
 
 class TestCase3(TestPad2dOp):
     def initTestCase(self):
-        self.shape = (2, 4, 4, 2)
+        self.shape = (2, 4, 4, 4)
         self.paddings = [0, 1, 2, 3]
         self.mode = "reflect"
         self.data_format = "NHWC"
@@ -89,7 +89,7 @@ class TestCase3(TestPad2dOp):
 
 class TestCase4(TestPad2dOp):
     def initTestCase(self):
-        self.shape = (2, 4, 4, 2)
+        self.shape = (2, 4, 4, 4)
         self.paddings = [0, 1, 2, 3]
         self.mode = "edge"
         self.data_format = "NHWC"
@@ -97,7 +97,7 @@ class TestCase4(TestPad2dOp):
 
 class TestCase5(TestPad2dOp):
     def initTestCase(self):
-        self.shape = (2, 4, 4, 2)
+        self.shape = (2, 4, 4, 4)
         self.paddings = [0, 1, 2, 3]
         self.mode = "constant"
         self.pad_value = 1.2
@@ -106,7 +106,7 @@ class TestCase5(TestPad2dOp):
 
 class TestCase6(TestPad2dOp):
     def initTestCase(self):
-        self.shape = (2, 4, 4, 2)
+        self.shape = (2, 4, 4, 4)
         self.paddings = [0, 1, 2, 3]
         self.mode = "constant"
         self.pad_value = 1.2
@@ -116,7 +116,7 @@ class TestCase6(TestPad2dOp):
 
 class TestCase7(TestPad2dOp):
     def initTestCase(self):
-        self.shape = (2, 3, 4, 4)
+        self.shape = (2, 3, 4, 5)
         self.paddings = [0, 1, 2, 3]
         self.mode = "reflect"
         self.data_format = "NCHW"

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

@@ -169,7 +169,7 @@ class TestAnyOpWithKeepDim(OpTest):
 class Test1DReduce(OpTest):
     def setUp(self):
         self.op_type = "reduce_sum"
-        self.inputs = {'X': np.random.random(20).astype("float64")}
+        self.inputs = {'X': np.random.random(120).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].sum(axis=0)}
 
     def test_check_output(self):

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

@@ -35,9 +35,9 @@ class TestReshapeOp(OpTest):
         }
 
     def init_data(self):
-        self.ori_shape = (2, 25)
-        self.new_shape = (5, 10)
-        self.infered_shape = (5, 10)
+        self.ori_shape = (2, 60)
+        self.new_shape = (12, 10)
+        self.infered_shape = (12, 10)
 
     def test_check_output(self):
 
@@ -49,7 +49,7 @@ class TestReshapeOp(OpTest):
 
 class TestReshapeOpDimInfer1(TestReshapeOp):
     def init_data(self):
-        self.ori_shape = (5, 10)
+        self.ori_shape = (5, 25)
         self.new_shape = (5, -1, 5)
         self.infered_shape = (5, -1, 5)
 

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

@@ -21,7 +21,7 @@ from op_test import OpTest
 
 class TestReverseOp(OpTest):
     def initTestCase(self):
-        self.x = np.random.random((3, 4)).astype('float32')
+        self.x = np.random.random((3, 40)).astype('float32')
         self.axis = [0]
 
     def setUp(self):
@@ -43,25 +43,25 @@ class TestReverseOp(OpTest):
 
 class TestCase0(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 4)).astype('float32')
+        self.x = np.random.random((3, 40)).astype('float32')
         self.axis = [1]
 
 
 class TestCase1(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 4)).astype('float32')
+        self.x = np.random.random((3, 40)).astype('float32')
         self.axis = [0, 1]
 
 
 class TestCase2(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 4, 5)).astype('float32')
+        self.x = np.random.random((3, 4, 10)).astype('float32')
         self.axis = [0, 2]
 
 
 class TestCase3(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 4, 5)).astype('float32')
+        self.x = np.random.random((3, 4, 10)).astype('float32')
         self.axis = [1, 2]
 
 

python/paddle/fluid/tests/unittests/test_squeeze2_op.py

@@ -39,9 +39,9 @@ class TestSqueezeOp(OpTest):
         self.check_grad(["X"], "Out")
 
     def init_test_case(self):
-        self.ori_shape = (1, 3, 1, 5)
+        self.ori_shape = (1, 3, 1, 40)
         self.axes = (0, 2)
-        self.new_shape = (3, 5)
+        self.new_shape = (3, 40)
 
     def init_attrs(self):
         self.attrs = {"axes": self.axes}

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

@@ -38,9 +38,9 @@ class TestSqueezeOp(OpTest):
         self.check_grad(["X"], "Out")
 
     def init_test_case(self):
-        self.ori_shape = (1, 3, 1, 5)
+        self.ori_shape = (1, 3, 1, 40)
         self.axes = (0, 2)
-        self.new_shape = (3, 5)
+        self.new_shape = (3, 40)
 
     def init_attrs(self):
         self.attrs = {"axes": self.axes}
@@ -49,9 +49,9 @@ class TestSqueezeOp(OpTest):
 # Correct: There is mins axis.
 class TestSqueezeOp1(TestSqueezeOp):
     def init_test_case(self):
-        self.ori_shape = (1, 3, 1, 5)
+        self.ori_shape = (1, 3, 1, 40)
         self.axes = (0, -2)
-        self.new_shape = (3, 5)
+        self.new_shape = (3, 40)
 
 
 # Correct: No axes input.

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

@@ -27,9 +27,9 @@ class TestSumOp(OpTest):
         self.init_kernel_type()
         self.use_mkldnn = False
         self.init_kernel_type()
-        x0 = np.random.random((3, 4)).astype(self.dtype)
-        x1 = np.random.random((3, 4)).astype(self.dtype)
-        x2 = np.random.random((3, 4)).astype(self.dtype)
+        x0 = np.random.random((3, 40)).astype(self.dtype)
+        x1 = np.random.random((3, 40)).astype(self.dtype)
+        x2 = np.random.random((3, 40)).astype(self.dtype)
         self.inputs = {"X": [("x0", x0), ("x1", x1), ("x2", x2)]}
         y = x0 + x1 + x2
         self.outputs = {'Out': y}

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

@@ -46,19 +46,19 @@ class TestTransposeOp(OpTest):
         self.check_grad(['X'], 'Out')
 
     def initTestCase(self):
-        self.shape = (3, 4)
+        self.shape = (3, 40)
         self.axis = (1, 0)
 
 
 class TestCase0(TestTransposeOp):
     def initTestCase(self):
-        self.shape = (3, )
+        self.shape = (100, )
         self.axis = (0, )
 
 
 class TestCase1(TestTransposeOp):
     def initTestCase(self):
-        self.shape = (3, 4, 5)
+        self.shape = (3, 4, 10)
         self.axis = (0, 2, 1)
 
 

python/paddle/fluid/tests/unittests/test_unsqueeze2_op.py

@@ -39,9 +39,9 @@ class TestUnsqueezeOp(OpTest):
         self.check_grad(["X"], "Out")
 
     def init_test_case(self):
-        self.ori_shape = (3, 5)
+        self.ori_shape = (3, 40)
         self.axes = (1, 2)
-        self.new_shape = (3, 1, 1, 5)
+        self.new_shape = (3, 1, 1, 40)
 
     def init_attrs(self):
         self.attrs = {"axes": self.axes}

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

@@ -36,9 +36,9 @@ class TestUnsqueezeOp(OpTest):
         self.check_grad(["X"], "Out")
 
     def init_test_case(self):
-        self.ori_shape = (3, 5)
+        self.ori_shape = (3, 40)
         self.axes = (1, 2)
-        self.new_shape = (3, 1, 1, 5)
+        self.new_shape = (3, 1, 1, 40)
 
     def init_attrs(self):
         self.attrs = {"axes": self.axes}