diff --git a/python/paddle/v2/framework/tests/op_test_util.py b/python/paddle/v2/framework/tests/op_test_util.py index 9ee66c2c5103811519c3a2c28653536f97009161..e6bc7d8a9b5ddd4582a5ef8a47cb63a7e5911892 100644 --- a/python/paddle/v2/framework/tests/op_test_util.py +++ b/python/paddle/v2/framework/tests/op_test_util.py @@ -33,23 +33,28 @@ class OpTestMeta(type): for place in places: for in_name in func.all_input_args: - if hasattr(self, in_name): + if hasattr(self, "inputs") and in_name in self.inputs: kwargs[in_name] = in_name var = scope.new_var(in_name).get_tensor() - arr = getattr(self, in_name) + arr = self.inputs[in_name] var.set_dims(arr.shape) var.set(arr, place) else: kwargs[in_name] = "@EMPTY@" for out_name in func.all_output_args: - if hasattr(self, out_name): - kwargs[out_name] = out_name - scope.new_var(out_name).get_tensor() + if not hasattr(self, "outputs"): + raise ValueError( + "The test op must set self.outputs dict.") + if out_name not in self.outputs: + raise ValueError("The %s is not in self.outputs dict." % + (out_name)) + kwargs[out_name] = out_name + scope.new_var(out_name).get_tensor() for attr_name in func.all_attr_args: - if hasattr(self, attr_name): - kwargs[attr_name] = getattr(self, attr_name) + if hasattr(self, "attrs") and attr_name in self.attrs: + kwargs[attr_name] = self.attrs[attr_name] op = func(**kwargs) @@ -60,7 +65,7 @@ class OpTestMeta(type): for out_name in func.all_output_args: actual = numpy.array(scope.find_var(out_name).get_tensor()) - expect = getattr(self, out_name) + expect = self.outputs[out_name] numpy.isclose(actual, expect) obj.test_all = test_all diff --git a/python/paddle/v2/framework/tests/test_add_two_op.py b/python/paddle/v2/framework/tests/test_add_two_op.py index 6e6643201bf361fce1bad7de10b2562f0525e00a..8ef48f4727b0af46a696c6f463045d98e7a08800 100644 --- a/python/paddle/v2/framework/tests/test_add_two_op.py +++ b/python/paddle/v2/framework/tests/test_add_two_op.py @@ -12,9 +12,11 @@ class TestAddOp(unittest.TestCase): def setUp(self): self.type = "add_two" - self.X = numpy.random.random((102, 105)).astype("float32") - self.Y = numpy.random.random((102, 105)).astype("float32") - self.Out = self.X + self.Y + self.inputs = { + 'X': numpy.random.random((102, 105)).astype("float32"), + 'Y': numpy.random.random((102, 105)).astype("float32") + } + self.outputs = {'Out': self.inputs['X'] + self.inputs['Y']} class TestAddGradOp(unittest.TestCase): diff --git a/python/paddle/v2/framework/tests/test_cross_entropy_op.py b/python/paddle/v2/framework/tests/test_cross_entropy_op.py index 6d022f6bc0be60dbf2f796780a969bff0e8bfded..b26e25d58b59bd1cb16e9ba2a1cccd27799b15f2 100644 --- a/python/paddle/v2/framework/tests/test_cross_entropy_op.py +++ b/python/paddle/v2/framework/tests/test_cross_entropy_op.py @@ -7,15 +7,17 @@ class TestSGD(unittest.TestCase): __metaclass__ = OpTestMeta def setUp(self): + # TODO this unit test is not passed self.type = "onehot_cross_entropy" batch_size = 100 class_num = 10 - self.X = numpy.random.random((batch_size, class_num)).astype("float32") - self.label = 5 * numpy.ones(batch_size).astype("int32") + X = numpy.random.random((batch_size, class_num)).astype("float32") + label = 5 * numpy.ones(batch_size).astype("int32") + self.inputs = {'X': X, 'label': label} Y = [] for i in range(0, batch_size): - Y.append(-numpy.log(self.X[i][self.label[i]])) - self.Y = numpy.array(Y).astype("float32") + Y.append(-numpy.log(X[i][label[i]])) + self.outputs = {'Y': numpy.array(Y).astype("float32")} # TODO(superjom) add gradient check diff --git a/python/paddle/v2/framework/tests/test_mean_op.py b/python/paddle/v2/framework/tests/test_mean_op.py index 78fff1eeff998109a51ea662f963a102eff49d3a..b5d52b90567bcd0c9f376147145d8638049f7bab 100644 --- a/python/paddle/v2/framework/tests/test_mean_op.py +++ b/python/paddle/v2/framework/tests/test_mean_op.py @@ -8,8 +8,8 @@ class TestMeanOp(unittest.TestCase): def setUp(self): self.type = "mean" - self.X = np.random.random((32, 784)).astype("float32") - self.Out = np.mean(self.X) + self.inputs = {'X': np.random.random((32, 784)).astype("float32")} + self.outputs = {'Out': np.mean(self.inputs['X'])} if __name__ == '__main__': diff --git a/python/paddle/v2/framework/tests/test_mul_op.py b/python/paddle/v2/framework/tests/test_mul_op.py index e1ac66d3a4d23d617f7c5a4d97d070b2660954c8..ec0ac99156a546dd3fb7b27778032bece38ab5a9 100644 --- a/python/paddle/v2/framework/tests/test_mul_op.py +++ b/python/paddle/v2/framework/tests/test_mul_op.py @@ -8,9 +8,11 @@ class TestMulOp(unittest.TestCase): def setUp(self): self.type = "mul" - self.X = np.random.random((32, 84)).astype("float32") - self.Y = np.random.random((84, 100)).astype("float32") - self.Out = np.dot(self.X, self.Y) + self.inputs = { + 'X': np.random.random((32, 84)).astype("float32"), + 'Y': np.random.random((84, 100)).astype("float32") + } + self.outputs = {'Out': np.dot(self.inputs['X'], self.inputs['Y'])} if __name__ == '__main__': diff --git a/python/paddle/v2/framework/tests/test_rowwise_add_op.py b/python/paddle/v2/framework/tests/test_rowwise_add_op.py index 04abc14ee198fe4e2307e009c696a2b40ec271b6..f8521eb517057fbeb104b28af7da4fffe54f37de 100644 --- a/python/paddle/v2/framework/tests/test_rowwise_add_op.py +++ b/python/paddle/v2/framework/tests/test_rowwise_add_op.py @@ -8,9 +8,11 @@ class TestRowwiseAddOp(unittest.TestCase): def setUp(self): self.type = "rowwise_add" - self.X = np.random.random((32, 84)).astype("float32") - self.b = np.random.random(84).astype("float32") - self.Out = np.add(self.X, self.b) + self.inputs = { + 'X': np.random.random((32, 84)).astype("float32"), + 'b': np.random.random(84).astype("float32") + } + self.outputs = {'Out': np.add(self.inputs['X'], self.inputs['b'])} if __name__ == '__main__': diff --git a/python/paddle/v2/framework/tests/test_sgd_op.py b/python/paddle/v2/framework/tests/test_sgd_op.py index ca03cc11abe2ceb31b33a87797aa752943dd2a7d..e5f9ef865e84f1a78e28884ad7e2e758f9ca8054 100644 --- a/python/paddle/v2/framework/tests/test_sgd_op.py +++ b/python/paddle/v2/framework/tests/test_sgd_op.py @@ -8,10 +8,13 @@ class TestSGD(unittest.TestCase): def setUp(self): self.type = "sgd" - self.param = numpy.random.random((102, 105)).astype("float32") - self.grad = numpy.random.random((102, 105)).astype("float32") - self.learning_rate = 0.1 - self.param_out = self.param - self.learning_rate * self.grad + w = numpy.random.random((102, 105)).astype("float32") + g = numpy.random.random((102, 105)).astype("float32") + lr = 0.1 + + self.inputs = {'param': w, 'grad': g} + self.attrs = {'learning_rate': lr} + self.outputs = {'param_out': w - lr * g} if __name__ == "__main__": diff --git a/python/paddle/v2/framework/tests/test_sigmoid_op.py b/python/paddle/v2/framework/tests/test_sigmoid_op.py index 50044a122f1d66dd54a24f6cce76074a60ee2262..2610bcf16303d492dce3ce63c93b54b0c88f6bba 100644 --- a/python/paddle/v2/framework/tests/test_sigmoid_op.py +++ b/python/paddle/v2/framework/tests/test_sigmoid_op.py @@ -8,8 +8,8 @@ class TestSigmoidOp(unittest.TestCase): def setUp(self): self.type = "sigmoid" - self.X = np.random.random((32, 100)).astype("float32") - self.Y = 1 / (1 + np.exp(-self.X)) + self.inputs = {'X': np.random.random((32, 100)).astype("float32")} + self.outputs = {'Y': 1 / (1 + np.exp(-self.inputs['X']))} if __name__ == '__main__': diff --git a/python/paddle/v2/framework/tests/test_softmax_op.py b/python/paddle/v2/framework/tests/test_softmax_op.py index c80888128781d98e4ed30d845a30b39121f66459..98ca8ddc860c3825411b02b2f6ed612db46a18d7 100644 --- a/python/paddle/v2/framework/tests/test_softmax_op.py +++ b/python/paddle/v2/framework/tests/test_softmax_op.py @@ -19,8 +19,10 @@ class TestSoftmaxOp(unittest.TestCase): def setUp(self): self.type = "softmax" - self.X = np.random.random((32, 100)).astype("float32") - self.Y = np.apply_along_axis(stable_softmax, 1, self.X) + self.inputs = {'X': np.random.random((32, 100)).astype("float32")} + self.outputs = { + 'Y': np.apply_along_axis(stable_softmax, 1, self.inputs['X']) + } class TestSoftmaxGradOp(unittest.TestCase):