Mutiply bug allow non-tensor data input #27690

Joejiong · 2020-09-28T13:09:14Z

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Bug fixes

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from __future__ import print_function
import paddle
import paddle.tensor as tensor
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard
import numpy as np
import unittest


class TestMultiplyAPI(unittest.TestCase):
    """TestMultiplyAPI."""

    def __run_static_graph_case(self, x_data, y_data, axis=-1):
        with program_guard(Program(), Program()):
            paddle.enable_static()
            x = paddle.static.data(
                name='x', shape=x_data.shape, dtype=x_data.dtype)
            y = paddle.static.data(
                name='y', shape=y_data.shape, dtype=y_data.dtype)
            res = tensor.multiply(x, y, axis=axis)

            place = fluid.CUDAPlace(0) if fluid.core.is_compiled_with_cuda(
            ) else fluid.CPUPlace()
            exe = fluid.Executor(place)
            outs = exe.run(fluid.default_main_program(),
                           feed={'x': x_data,
                                 'y': y_data},
                           fetch_list=[res])
            res = outs[0]
            return res

    def __run_dynamic_graph_case(self, x_data, y_data, axis=-1):
        paddle.disable_static()
        x = paddle.to_tensor(x_data)
        y = paddle.to_tensor(y_data)
        res = paddle.multiply(x, y, axis=axis)
        return res.numpy()

    def __run_dynamic_graph_case_with_numpy_input(self, x_data, y_data,
                                                  axis=-1):
        paddle.disable_static()
        res = paddle.multiply(x_data, y_data, axis=axis)
        return res.numpy()

    def test_multiply(self):
        """test_multiply."""
        np.random.seed(7)
        # test static computation graph: 1-d array
        x_data = np.random.rand(200)
        y_data = np.random.rand(200)
        res = self.__run_static_graph_case(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test static computation graph: 2-d array
        x_data = np.random.rand(2, 500)
        y_data = np.random.rand(2, 500)
        res = self.__run_static_graph_case(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test static computation graph: broadcast
        x_data = np.random.rand(2, 500)
        y_data = np.random.rand(500)
        res = self.__run_static_graph_case(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test static computation graph: broadcast with axis
        x_data = np.random.rand(2, 300, 40)
        y_data = np.random.rand(300)
        res = self.__run_static_graph_case(x_data, y_data, axis=1)
        expected = np.multiply(x_data, y_data[..., np.newaxis])
        self.assertTrue(np.allclose(res, expected))

        # test dynamic computation graph: 1-d array
        x_data = np.random.rand(200)
        y_data = np.random.rand(200)
        res = self.__run_dynamic_graph_case(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test dynamic numpy input computation graph: 1-d array
        x_data = np.random.rand(200)
        y_data = np.random.rand(200)
        res = self.__run_dynamic_graph_case_with_numpy_input(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test dynamic computation graph: 2-d array
        x_data = np.random.rand(20, 50)
        y_data = np.random.rand(20, 50)
        res = self.__run_dynamic_graph_case(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test dynamic numpy input computation graph: 1-d array
        x_data = np.random.rand(20, 50)
        y_data = np.random.rand(20, 50)
        res = self.__run_dynamic_graph_case_with_numpy_input(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test dynamic computation graph: broadcast
        x_data = np.random.rand(2, 500)
        y_data = np.random.rand(500)
        res = self.__run_dynamic_graph_case(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test dynamic computation graph: broadcast
        x_data = np.random.rand(2, 500)
        y_data = np.random.rand(500)
        res = self.__run_dynamic_graph_case_with_numpy_input(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

        # test dynamic computation graph: broadcast with axis
        x_data = np.random.rand(2, 300, 40)
        y_data = np.random.rand(300)
        res = self.__run_dynamic_graph_case(x_data, y_data, axis=1)
        expected = np.multiply(x_data, y_data[..., np.newaxis])
        self.assertTrue(np.allclose(res, expected))


class TestMultiplyError(unittest.TestCase):
    """TestMultiplyError."""

    def test_errors(self):
        """test_errors."""
        # test static computation graph: dtype can not be int8
        paddle.enable_static()
        with program_guard(Program(), Program()):
            x = paddle.static.data(name='x', shape=[100], dtype=np.int8)
            y = paddle.static.data(name='y', shape=[100], dtype=np.int8)
            self.assertRaises(TypeError, tensor.multiply, x, y)

        # test static computation graph: inputs must be broadcastable 
        with program_guard(Program(), Program()):
            x = paddle.static.data(name='x', shape=[20, 50], dtype=np.float64)
            y = paddle.static.data(name='y', shape=[20], dtype=np.float64)
            self.assertRaises(fluid.core.EnforceNotMet, tensor.multiply, x, y)

        np.random.seed(7)
        # test dynamic computation graph: dtype can not be int8
        paddle.disable_static()
        x_data = np.random.randn(200).astype(np.int8)
        y_data = np.random.randn(200).astype(np.int8)
        x = paddle.to_tensor(x_data)
        y = paddle.to_tensor(y_data)
        self.assertRaises(fluid.core.EnforceNotMet, paddle.multiply, x, y)

        # test dynamic computation graph: inputs must be broadcastable
        x_data = np.random.rand(200, 5)
        y_data = np.random.rand(200)
        x = paddle.to_tensor(x_data)
        y = paddle.to_tensor(y_data)
        self.assertRaises(fluid.core.EnforceNotMet, paddle.multiply, x, y)

        # test dynamic computation graph: inputs must be broadcastable(python)
        x_data = np.random.rand(200, 5)
        y_data = np.random.rand(200)
        x = paddle.to_tensor(x_data)
        y = paddle.to_tensor(y_data)
        self.assertRaises(fluid.core.EnforceNotMet, paddle.multiply, x, y)

        # test dynamic computation graph: dtype must be same
        x_data = np.random.randn(200).astype(np.int64)
        y_data = np.random.randn(200).astype(np.float64)
        x = paddle.to_tensor(x_data)
        y = paddle.to_tensor(y_data)
        self.assertRaises(TypeError, paddle.multiply, x, y)


if __name__ == '__main__':
    unittest.main()

… mutiply_bug

paddle-bot-old · 2020-09-28T13:09:31Z

Thanks for your contribution!
Please wait for the result of CI firstly. See Paddle CI Manual for details.

… mutiply_bug

zhhsplendid

代码我觉得没有问题，测试有一些代码我觉得不是很好，已评论，因为ci已经过了，我这边先approve，要这个PR改还是下一个PR改请自己决定。

zhhsplendid · 2020-10-12T09:00:41Z

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

@@ -42,66 +43,140 @@ def __run_static_graph_case(self, x_data, y_data, axis=-1):
            res = outs[0]
            return res

+    def __run_static_graph_case_with_numpy_input(self, x_data, y_data, axis=-1):
+        with program_guard(Program(), Program()):


program是静态图才有的，所以最好paddle.enable_static写在with program_guard前面

zhhsplendid · 2020-10-12T09:00:47Z

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

@@ -26,6 +26,7 @@ class TestMultiplyAPI(unittest.TestCase):

    def __run_static_graph_case(self, x_data, y_data, axis=-1):
        with program_guard(Program(), Program()):
+            paddle.enable_static()


program是静态图才有的，所以最好paddle.enable_static写在with program_guard前面

zhhsplendid · 2020-10-12T09:01:34Z

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

+            res = tensor.multiply(x_data, y_data, axis=axis)
+            place = fluid.CUDAPlace(0) if fluid.core.is_compiled_with_cuda(
+            ) else fluid.CPUPlace()
+            exe = fluid.Executor(place)


将来可以尽量用2.0 迁移的写法，比如paddle.CPUPlace, paddle.CUDAPlace，paddle.static.Executor

zhhsplendid · 2020-10-12T09:02:40Z

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

        # test static computation graph: 1-d array
        x_data = np.random.rand(200)
        y_data = np.random.rand(200)
        res = self.__run_static_graph_case(x_data, y_data)
        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))

+        # test static computation graph: 1-d array


像我以前说过，python里面用注释分隔测试并不是最好的方法，你可以直接创建一个测试method:

def test_static_multiply_1d(self) 这类的

Mutiply allows non-tensor data input

Joejiong added 2 commits September 28, 2020 13:02

add implicitly paddle.tensor transform

d3022bb

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…

28aa96f

… mutiply_bug

Joejiong added 2 commits September 29, 2020 08:03

add static implicit tranformation

8f6f236

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…

ed1a0e4

… mutiply_bug

zhhsplendid reviewed Oct 12, 2020

View reviewed changes

zhhsplendid approved these changes Oct 12, 2020

View reviewed changes

zhhsplendid merged commit 2bcb7c0 into PaddlePaddle:develop Oct 12, 2020

Joejiong mentioned this pull request Oct 14, 2020

[cherry-pick] Mutiply bug allow data type other than tensor. #27938

Closed

chen-zhiyu pushed a commit to chen-zhiyu/Paddle that referenced this pull request Oct 15, 2020

Mutiply allows non-tensor data input (PaddlePaddle#27690)

aae1102

Mutiply allows non-tensor data input

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Mutiply bug allow non-tensor data input #27690

Mutiply bug allow non-tensor data input #27690

Joejiong commented Sep 28, 2020

paddle-bot-old bot commented Sep 28, 2020

zhhsplendid left a comment

zhhsplendid Oct 12, 2020

zhhsplendid Oct 12, 2020

zhhsplendid Oct 12, 2020

zhhsplendid Oct 12, 2020

Mutiply bug allow non-tensor data input #27690

Mutiply bug allow non-tensor data input #27690

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Joejiong commented Sep 28, 2020

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paddle-bot-old bot commented Sep 28, 2020

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