提交 cf5ac588 编写于 作者: Q qijun

reduce gpu memory allocation in op_test

上级 61f94f00
...@@ -8,8 +8,8 @@ class TestAddOp(unittest.TestCase): ...@@ -8,8 +8,8 @@ class TestAddOp(unittest.TestCase):
def setUp(self): def setUp(self):
self.type = "add_two" self.type = "add_two"
self.X = numpy.random.random((342, 345)).astype("float32") self.X = numpy.random.random((102, 105)).astype("float32")
self.Y = numpy.random.random((342, 345)).astype("float32") self.Y = numpy.random.random((102, 105)).astype("float32")
self.Out = self.X + self.Y self.Out = self.X + self.Y
......
...@@ -8,8 +8,8 @@ class TestMulOp(unittest.TestCase): ...@@ -8,8 +8,8 @@ class TestMulOp(unittest.TestCase):
def setUp(self): def setUp(self):
self.type = "mul" self.type = "mul"
self.X = np.random.random((32, 784)).astype("float32") self.X = np.random.random((32, 84)).astype("float32")
self.Y = np.random.random((784, 100)).astype("float32") self.Y = np.random.random((84, 100)).astype("float32")
self.Out = np.dot(self.X, self.Y) self.Out = np.dot(self.X, self.Y)
......
...@@ -8,8 +8,8 @@ class TestRowwiseAddOp(unittest.TestCase): ...@@ -8,8 +8,8 @@ class TestRowwiseAddOp(unittest.TestCase):
def setUp(self): def setUp(self):
self.type = "rowwise_add" self.type = "rowwise_add"
self.X = np.random.random((32, 784)).astype("float32") self.X = np.random.random((32, 84)).astype("float32")
self.b = np.random.random(784).astype("float32") self.b = np.random.random(84).astype("float32")
self.Out = np.add(self.X, self.b) self.Out = np.add(self.X, self.b)
......
...@@ -8,8 +8,8 @@ class TestSGD(unittest.TestCase): ...@@ -8,8 +8,8 @@ class TestSGD(unittest.TestCase):
def setUp(self): def setUp(self):
self.type = "sgd" self.type = "sgd"
self.param = numpy.random.random((342, 345)).astype("float32") self.param = numpy.random.random((102, 105)).astype("float32")
self.grad = numpy.random.random((342, 345)).astype("float32") self.grad = numpy.random.random((102, 105)).astype("float32")
self.learning_rate = 0.1 self.learning_rate = 0.1
self.param_out = self.param - self.learning_rate * self.grad self.param_out = self.param - self.learning_rate * self.grad
......
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