reduce unittest gpu memory

python/paddle/v2/framework/tests/test_add_two_op.py

@@ -13,8 +13,8 @@ class TestAddOp(unittest.TestCase):
     def setUp(self):
         self.type = "add_two"
         self.inputs = {
-            'X': numpy.random.random((102, 105)).astype("float32"),
-            'Y': numpy.random.random((102, 105)).astype("float32")
+            'X': numpy.random.random((12, 15)).astype("float32"),
+            'Y': numpy.random.random((12, 15)).astype("float32")
         }
         self.outputs = {'Out': self.inputs['X'] + self.inputs['Y']}
 

python/paddle/v2/framework/tests/test_cross_entropy_op.py

@@ -10,7 +10,7 @@ class TestCrossEntropy(unittest.TestCase):
     def setUp(self):
         # TODO this unit test is not passed
         self.type = "onehot_cross_entropy"
-        batch_size = 100
+        batch_size = 32
         class_num = 10
         X = numpy.random.random((batch_size, class_num)).astype("float32")
         label = 5 * numpy.ones(batch_size).astype("int32")
@@ -24,7 +24,7 @@ def setUp(self):
 class CrossEntropyGradOpTest(GradientChecker):
     def test_softmax_grad(self):
         op = create_op("onehot_cross_entropy")
-        batch_size = 100
+        batch_size = 32
         class_num = 10
         inputs = {
             "X": numpy.random.uniform(

python/paddle/v2/framework/tests/test_fill_zeros_like_op.py

@@ -8,7 +8,7 @@ class TestFillZerosLikeOp(unittest.TestCase):
 
     def setUp(self):
         self.type = "fill_zeros_like"
-        self.inputs = {'Src': numpy.random.random((219, 232)).astype("float32")}
+        self.inputs = {'Src': numpy.random.random((29, 22)).astype("float32")}
         self.outputs = {'Dst': numpy.zeros_like(self.inputs['Src'])}
 
 

python/paddle/v2/framework/tests/test_gaussian_random_op.py

@@ -19,7 +19,7 @@ def gaussian_random_test(self, place):
         op = Operator(
             "gaussian_random",
             Out="Out",
-            dims=[1000, 784],
+            dims=[10, 24],
             mean=.0,
             std=1.,
             seed=10)

python/paddle/v2/framework/tests/test_mean_op.py

@@ -8,7 +8,7 @@ class TestMeanOp(unittest.TestCase):
 
     def setUp(self):
         self.type = "mean"
-        self.inputs = {'X': np.random.random((32, 784)).astype("float32")}
+        self.inputs = {'X': np.random.random((32, 84)).astype("float32")}
         self.outputs = {'Out': np.mean(self.inputs['X'])}
 
 

python/paddle/v2/framework/tests/test_mul_op.py

@@ -9,8 +9,8 @@ class TestMulOp(unittest.TestCase):
     def setUp(self):
         self.type = "mul"
         self.inputs = {
-            'X': np.random.random((32, 84)).astype("float32"),
-            'Y': np.random.random((84, 100)).astype("float32")
+            'X': np.random.random((32, 24)).astype("float32"),
+            'Y': np.random.random((24, 10)).astype("float32")
         }
         self.outputs = {'Out': np.dot(self.inputs['X'], self.inputs['Y'])}
 

python/paddle/v2/framework/tests/test_rowwise_add_op.py

@@ -9,8 +9,8 @@ class TestRowwiseAddOp(unittest.TestCase):
     def setUp(self):
         self.type = "rowwise_add"
         self.inputs = {
-            'X': np.random.random((32, 84)).astype("float32"),
-            'b': np.random.random(84).astype("float32")
+            'X': np.random.random((32, 24)).astype("float32"),
+            'b': np.random.random(24).astype("float32")
         }
         self.outputs = {'Out': np.add(self.inputs['X'], self.inputs['b'])}
 

python/paddle/v2/framework/tests/test_sgd_op.py

@@ -8,8 +8,8 @@ class TestSGD(unittest.TestCase):
 
     def setUp(self):
         self.type = "sgd"
-        w = numpy.random.random((102, 105)).astype("float32")
-        g = numpy.random.random((102, 105)).astype("float32")
+        w = numpy.random.random((12, 15)).astype("float32")
+        g = numpy.random.random((12, 15)).astype("float32")
         lr = 0.1
 
         self.inputs = {'param': w, 'grad': g}

python/paddle/v2/framework/tests/test_sigmoid_op.py

@@ -8,7 +8,7 @@ class TestSigmoidOp(unittest.TestCase):
 
     def setUp(self):
         self.type = "sigmoid"
-        self.inputs = {'X': np.random.random((32, 100)).astype("float32")}
+        self.inputs = {'X': np.random.random((32, 18)).astype("float32")}
         self.outputs = {'Y': 1 / (1 + np.exp(-self.inputs['X']))}
 
 

python/paddle/v2/framework/tests/test_softmax_op.py

@@ -18,7 +18,7 @@ class TestSoftmaxOp(unittest.TestCase):
 
     def setUp(self):
         self.type = "softmax"
-        self.inputs = {'X': np.random.random((32, 100)).astype("float32")}
+        self.inputs = {'X': np.random.random((32, 22)).astype("float32")}
         self.outputs = {
             'Y': np.apply_along_axis(stable_softmax, 1, self.inputs['X'])
         }

python/paddle/v2/framework/tests/test_tensor.py

@@ -11,10 +11,10 @@ def test_int_tensor(self):
 
         tensor = var.get_tensor()
 
-        tensor.set_dims([1000, 784])
+        tensor.set_dims([100, 84])
         tensor.alloc_int(place)
         tensor_array = numpy.array(tensor)
-        self.assertEqual((1000, 784), tensor_array.shape)
+        self.assertEqual((100, 84), tensor_array.shape)
         tensor_array[3, 9] = 1
         tensor_array[19, 11] = 2
         tensor.set(tensor_array, place)
@@ -30,11 +30,11 @@ def test_float_tensor(self):
 
         tensor = var.get_tensor()
 
-        tensor.set_dims([1000, 784])
+        tensor.set_dims([100, 84])
         tensor.alloc_float(place)
 
         tensor_array = numpy.array(tensor)
-        self.assertEqual((1000, 784), tensor_array.shape)
+        self.assertEqual((100, 84), tensor_array.shape)
         tensor_array[3, 9] = 1.0
         tensor_array[19, 11] = 2.0
         tensor.set(tensor_array, place)