diff --git a/python/paddle/fluid/tests/unittests/test_reduce_op.py b/python/paddle/fluid/tests/unittests/test_reduce_op.py index cf35f9dbcdaaae1357ccdfd6b5cba85ac98d2037..b0b85f633a2bf613cdbdcc2ba7b31b5d970da8ca 100644 --- a/python/paddle/fluid/tests/unittests/test_reduce_op.py +++ b/python/paddle/fluid/tests/unittests/test_reduce_op.py @@ -475,87 +475,71 @@ class API_TestSumOpError(unittest.TestCase): def test_errors(self): def test_dtype1(): with fluid.program_guard(fluid.Program(), fluid.Program()): - data = fluid.data(name="data", shape=[10], dtype="float32") - paddle.sum(data, dtype="int32") + data = fluid.data(name="data", shape=[10], dtype="float64") + paddle.sum(data, dtype="float32") self.assertRaises(ValueError, test_dtype1) def test_dtype2(): with fluid.program_guard(fluid.Program(), fluid.Program()): - data = fluid.data(name="data", shape=[10], dtype="float32") - paddle.sum(data, dtype="float32") + data = fluid.data(name="data", shape=[10], dtype="int64") + paddle.sum(data, dtype="int32") self.assertRaises(ValueError, test_dtype2) def test_dtype3(): with fluid.program_guard(fluid.Program(), fluid.Program()): - data = fluid.data(name="data", shape=[10], dtype="int32") - paddle.sum(data, dtype="bool") + data = fluid.data(name="data", shape=[10], dtype="float64") + paddle.sum(data, dtype="int32") self.assertRaises(ValueError, test_dtype3) - def test_dtype4(): + def test_type(): with fluid.program_guard(fluid.Program(), fluid.Program()): data = fluid.data(name="data", shape=[10], dtype="int32") - paddle.sum(data, dtype="int32") + paddle.sum(data, dtype="bool") - self.assertRaises(ValueError, test_dtype3) + self.assertRaises(TypeError, test_type) class API_TestSumOp(unittest.TestCase): - def test_static(self): - with fluid.program_guard(fluid.Program(), fluid.Program()): - data = fluid.data("data", shape=[10, 10], dtype="float32") - result_sum = paddle.sum(x=data, axis=1, dtype="float64") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - input_data = np.random.rand(10, 10).astype(np.float32) - res, = exe.run(feed={"data": input_data}, fetch_list=[result_sum]) - self.assertEqual( - (res == np.sum(input_data.astype(np.float64), axis=1)).all(), True) + def run_static(self, + shape, + x_dtype, + attr_axis, + attr_dtype=None, + np_axis=None): + if np_axis is None: + np_axis = attr_axis with fluid.program_guard(fluid.Program(), fluid.Program()): - data = fluid.data("data", shape=[10, 10], dtype="int32") - result_sum = paddle.sum(x=data, axis=1, dtype="int64") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - input_data = np.random.randint(10, size=(10, 10)).astype(np.int32) - res, = exe.run(feed={"data": input_data}, fetch_list=[result_sum]) - self.assertEqual( - (res == np.sum(input_data.astype(np.int64), axis=1)).all(), True) + data = fluid.data("data", shape=shape, dtype=x_dtype) + result_sum = paddle.sum(x=data, axis=attr_axis, dtype=attr_dtype) - with fluid.program_guard(fluid.Program(), fluid.Program()): - data = fluid.data("data", shape=[10, 10], dtype="int32") - result_sum = paddle.sum(x=data, axis=1) - place = fluid.CPUPlace() - exe = fluid.Executor(place) - input_data = np.random.randint(10, size=(10, 10)).astype(np.int32) + exe = fluid.Executor(fluid.CPUPlace()) + input_data = np.random.rand(*shape).astype(x_dtype) res, = exe.run(feed={"data": input_data}, fetch_list=[result_sum]) - self.assertEqual((res == np.sum(input_data, axis=1)).all(), True) - with fluid.program_guard(fluid.Program(), fluid.Program()): - data = fluid.data("data", shape=[10, 10], dtype="int32") - result_sum = paddle.sum(x=data, axis=1) - place = fluid.CPUPlace() - exe = fluid.Executor(place) - input_data = np.random.randint(10, size=(10, 10)).astype(np.int32) - res, = exe.run(feed={"data": input_data}, fetch_list=[result_sum]) - self.assertEqual((res == np.sum(input_data, axis=1)).all(), True) + self.assertTrue( + np.allclose( + res, np.sum(input_data.astype(attr_dtype), axis=np_axis))) - with fluid.program_guard(fluid.Program(), fluid.Program()): - input_data = np.random.randint(10, size=(5, 5, 5)).astype(np.int32) - data = fluid.data("data", shape=[5, 5, 5], dtype="int32") - sum1 = paddle.sum(x=data, axis=[0, 1]) - sum2 = paddle.sum(x=data, axis=()) - - place = fluid.CPUPlace() - exe = fluid.Executor(place) - res1, res2 = exe.run(feed={"data": input_data}, - fetch_list=[sum1, sum2]) - - self.assertEqual((res1 == np.sum(input_data, axis=(0, 1))).all(), True) - self.assertEqual( - (res2 == np.sum(input_data, axis=(0, 1, 2))).all(), True) + def test_static(self): + shape = [10, 10] + axis = 1 + + self.run_static(shape, "int32", axis, attr_dtype=None) + self.run_static(shape, "int32", axis, attr_dtype="int32") + self.run_static(shape, "int32", axis, attr_dtype="int64") + + self.run_static(shape, "float32", axis, attr_dtype=None) + self.run_static(shape, "float32", axis, attr_dtype="float32") + self.run_static(shape, "float32", axis, attr_dtype="float64") + + shape = [5, 5, 5] + self.run_static(shape, "int32", (0, 1), attr_dtype="int32") + self.run_static( + shape, "int32", (), attr_dtype="int32", np_axis=(0, 1, 2)) def test_dygraph(self): np_x = np.random.random([2, 3, 4]).astype('int32') diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py index e4a751ab5b8aa785bb7d27a1754dc8f6dc8261eb..ed2bbe03a366054dfe7d798310c7fa5d419b44a8 100755 --- a/python/paddle/tensor/math.py +++ b/python/paddle/tensor/math.py @@ -760,7 +760,8 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None): it's data type is the same as `x`. Raises: - ValueError: The :attr:`dtype` must be float64 or int64. + ValueError: If the data type of `x` is float64, :attr:`dtype` can not be float32 or int32. + ValueError: If the data type of `x` is int64, :attr:`dtype` can not be int32. TypeError: The type of :attr:`axis` must be int, list or tuple. Examples: @@ -815,10 +816,6 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None): 'out_dtype': convert_np_dtype_to_dtype_(dtype) }) dtype_flag = True - else: - raise ValueError( - "The value of 'dtype' in sum op must be float64, int64, but received of {}". - format(dtype)) if in_dygraph_mode(): axis = axis if axis != None and axis != [] else [0] @@ -832,6 +829,17 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None): 'reduce_all', reduce_all_flag) check_variable_and_dtype( x, 'x', ['float32', 'float64', 'int32', 'int64'], 'sum') + + if dtype is not None: + check_dtype(dtype, 'dtype', ['float32', 'float64', 'int32', 'int64'], 'sum') + x_dtype = convert_dtype(x.dtype) + + if (x_dtype == "float64" and dtype in ["float32", "int32"]) or \ + (x_dtype == "int64" and dtype == "int32"): + raise ValueError("The input(x)'s dtype is {} but the attr(dtype) of sum is {}, " + "which may cause data type overflows. Please reset attr(dtype) of sum." + .format(x_dtype, dtype)) + check_type(axis, 'axis', (int, list, tuple, type(None)), 'sum') helper = LayerHelper('sum', **locals())