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【PaddlePaddle Hackathon 3 No.12】为 Paddle 新增 pairwise_distance #44161

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merged 10 commits into from Jul 29, 2022
Merged

【PaddlePaddle Hackathon 3 No.12】为 Paddle 新增 pairwise_distance #44161

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1b7613f
add paddle.nn.functional.pairwise_distance (cattidea/Paddle#273)
Ainavo Jul 7, 2022
515df56
fix wrong variable name
SigureMo Jul 7, 2022
2c64711
加传统动态图
Ainavo Jul 7, 2022
5da6d36
引入paddle.fluid.framework
Ainavo Jul 7, 2022
27ebf80
删除无用的导入
Ainavo Jul 7, 2022
57cec0c
remove the test case for undefined behavior
SigureMo Jul 8, 2022
5bfe9de
refine docs
SigureMo Jul 9, 2022
504a3b6
Merge branch 'develop' into api_for_pairwise_distance
SigureMo Jul 17, 2022
a523910
Merge remote-tracking branch 'upstream/develop' into api_for_pairwise…
SigureMo Jul 26, 2022
34a2575
remove a blank line
SigureMo Jul 26, 2022
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335 changes: 293 additions & 42 deletions python/paddle/fluid/tests/unittests/test_pairwise_distance.py
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Expand Up @@ -20,24 +20,65 @@
import unittest


def pairwise_distance(x, y, p=2.0, epsilon=1e-6, keepdim=False):
return np.linalg.norm(x - y, ord=p, axis=1, keepdims=keepdim)
def np_pairwise_distance(x, y, p=2.0, epsilon=1e-6, keepdim=False):

distance = np.linalg.norm(x - y + epsilon, ord=p, axis=-1, keepdims=keepdim)
# Paddle currently has not supported for 0-d Tensors, so even if keep_dim is False,
# and neither x nor y is batched, a Tensor of shape (1, ) is returned
if distance.ndim == 0:
distance = np.expand_dims(distance, axis=0)
return distance

def test_static(x_np, y_np, p=2.0, epsilon=1e-6, keepdim=False):

def call_pairwise_distance_layer(x, y, p=2., epsilon=1e-6, keepdim='False'):
pairwise_distance = paddle.nn.PairwiseDistance(p=p,
epsilon=epsilon,
keepdim=keepdim)
distance = pairwise_distance(x=x, y=y)
return distance


def call_pairwise_distance_functional(x,
y,
p=2.,
epsilon=1e-6,
keepdim='False'):
distance = paddle.nn.functional.pairwise_distance(x=x,
y=y,
p=p,
epsilon=epsilon,
keepdim=keepdim)
return distance


def test_static(place,
x_np,
y_np,
p=2.0,
epsilon=1e-6,
keepdim=False,
functional=False):
prog = paddle.static.Program()
startup_prog = paddle.static.Program()

place = fluid.CUDAPlace(
0) if paddle.fluid.core.is_compiled_with_cuda() else fluid.CPUPlace()

paddle.enable_static()
with paddle.static.program_guard(prog, startup_prog):
x = paddle.fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
y = paddle.fluid.data(name='y', shape=y_np.shape, dtype=x_np.dtype)
dist = paddle.nn.layer.distance.PairwiseDistance(p=p,

if functional:
distance = call_pairwise_distance_functional(x=x,
y=y,
p=p,
epsilon=epsilon,
keepdim=keepdim)
distance = dist(x, y)
else:
distance = call_pairwise_distance_layer(x=x,
y=y,
p=p,
epsilon=epsilon,
keepdim=keepdim)
exe = paddle.static.Executor(place)
static_ret = exe.run(prog,
feed={
Expand All @@ -46,69 +87,279 @@ def test_static(x_np, y_np, p=2.0, epsilon=1e-6, keepdim=False):
},
fetch_list=[distance])
static_ret = static_ret[0]
paddle.disable_static()
return static_ret


def test_dygraph(x_np, y_np, p=2.0, epsilon=1e-6, keepdim=False):
paddle.disable_static()
def test_dygraph(place,
x_np,
y_np,
p=2.0,
epsilon=1e-6,
keepdim=False,
functional=False):
x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
dist = paddle.nn.layer.distance.PairwiseDistance(p=p,
epsilon=epsilon,
keepdim=keepdim)
distance = dist(x, y)
dygraph_ret = distance.numpy()
paddle.enable_static()
if functional:
dy_distance = call_pairwise_distance_functional(x=x,
y=y,
p=p,
epsilon=epsilon,
keepdim=keepdim)
else:
dy_distance = call_pairwise_distance_layer(x=x,
y=y,
p=p,
epsilon=epsilon,
keepdim=keepdim)
dygraph_ret = dy_distance.numpy()
return dygraph_ret


def test_legacy_dygraph(place,
x_np,
y_np,
p=2.0,
epsilon=1e-6,
keepdim=False,
functional=False):
paddle.fluid.framework._enable_legacy_dygraph()
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@SigureMo SigureMo Jul 7, 2022 •
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image

截图来自 PR-CI-APPROVAL

这里利用 _enable_legacy_dygraph 开启 legacy 动态图的原因是原来的 PairwiseDistance（class API）是包含 legacy 动态图代码的，如果不添加相关测试的话，Coverage CI 过不了，因此利用该 API 添加了相关测试，如果该逻辑不再推荐添加的话，我们会删去相关逻辑，并删去相关测试代码

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这个到时可以让对应的同学 approve 就好。目前还不能删掉这个逻辑。

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好哒～明白～

x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
if functional:
legacy_distance = call_pairwise_distance_functional(x=x,
y=y,
p=p,
epsilon=epsilon,
keepdim=keepdim)
else:
legacy_distance = call_pairwise_distance_layer(x=x,
y=y,
p=p,
epsilon=epsilon,
keepdim=keepdim)
legacy_ret = legacy_distance.numpy()
paddle.fluid.framework._disable_legacy_dygraph()
return legacy_ret


class TestPairwiseDistance(unittest.TestCase):

def test_pairwise_distance(self):
all_shape = [[100, 100], [4, 5, 6, 7]]
epsilon = 1e-6
all_shape = [[5], [100, 100], [4, 5, 6, 7]]
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因为我们希望修改 paddle 的 PairwiseDistance 的行为，让它支持两个 1d 输入，我支持把 axis 改成 -1. 在文档所述的 defined behavior 范围内，这个修改不会破坏兼容性。

好的明白。

但是测试中又使用了高维的输入，这就是在测试 undefined behavior, 如果能 define 那就不是 undefined behavior 了，所以我觉得需要修改这个测试文件。

这里有一个同样的问题，原本的单测（fluid 下面的）也是对 undefined behavior（[4, 5, 6, 7]）进行了测试，这里是不是也应该删掉呀～

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好的呀。

dtypes = ['float32', 'float64']
p_list = [-1, 0, 1, 2, np.inf, -np.inf]
places = [paddle.CPUPlace()]
if paddle.device.is_compiled_with_cuda():
places.append(paddle.CUDAPlace(0))
keeps = [False, True]
for shape in all_shape:
for dtype in dtypes:
for keepdim in keeps:
x_np = np.random.random(shape).astype(dtype)
y_np = np.random.random(shape).astype(dtype)

static_ret = test_static(x_np, y_np, keepdim=keepdim)
dygraph_ret = test_dygraph(x_np, y_np, keepdim=keepdim)
excepted_value = pairwise_distance(x_np,
for place in places:
for shape in all_shape:
for dtype in dtypes:
for p in p_list:
for keepdim in keeps:
x_np = np.random.random(shape).astype(dtype)
y_np = np.random.random(shape).astype(dtype)

static_ret = test_static(place,
x_np,
y_np,
p,
epsilon=epsilon,
keepdim=keepdim)
dygraph_ret = test_dygraph(place,
x_np,
y_np,
p,
epsilon=epsilon,
keepdim=keepdim)
legacy_ret = test_legacy_dygraph(place,
x_np,
y_np,
p,
epsilon=epsilon,
keepdim=keepdim)
excepted_value = np_pairwise_distance(
x_np, y_np, p, epsilon=epsilon, keepdim=keepdim)

self.assertEqual(static_ret.shape,
excepted_value.shape)
self.assertEqual(dygraph_ret.shape,
excepted_value.shape)
self.assertEqual(legacy_ret.shape,
excepted_value.shape)

self.assertTrue(
np.allclose(static_ret, excepted_value))
self.assertTrue(
np.allclose(dygraph_ret, excepted_value))
self.assertTrue(
np.allclose(legacy_ret, excepted_value))

static_functional_ret = test_static(place,
x_np,
y_np,
p,
epsilon=epsilon,
keepdim=keepdim)
dygraph_functional_ret = test_dygraph(
place,
x_np,
y_np,
p,
epsilon=epsilon,
keepdim=keepdim)
legacy_functional_ret = test_legacy_dygraph(
place,
x_np,
y_np,
p,
epsilon=epsilon,
keepdim=keepdim)

self.assertTrue(np.allclose(static_ret, dygraph_ret))
self.assertTrue(np.allclose(static_ret, excepted_value))
self.assertTrue(np.allclose(dygraph_ret, excepted_value))
self.assertEqual(static_functional_ret.shape,
excepted_value.shape)
self.assertEqual(dygraph_functional_ret.shape,
excepted_value.shape)
self.assertEqual(legacy_functional_ret.shape,
excepted_value.shape)

def test_pairwise_distance_broadcast(self):
self.assertTrue(
np.allclose(static_functional_ret,
excepted_value))
self.assertTrue(
np.allclose(dygraph_functional_ret,
excepted_value))
self.assertTrue(
np.allclose(legacy_functional_ret,
excepted_value))

def test_pairwise_distance_broadcast_1(self):
shape_x = [100, 100]
shape_y = [100, 1]
epsilon = 1e-6
keepdim = False
place = paddle.CPUPlace()
x_np = np.random.random(shape_x).astype('float32')
y_np = np.random.random(shape_y).astype('float32')
static_ret = test_static(x_np, y_np, keepdim=keepdim)
dygraph_ret = test_dygraph(x_np, y_np, keepdim=keepdim)
excepted_value = pairwise_distance(x_np, y_np, keepdim=keepdim)
self.assertTrue(np.allclose(static_ret, dygraph_ret))
static_ret = test_static(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim)
dygraph_ret = test_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim)
legacy_ret = test_legacy_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim)
excepted_value = np_pairwise_distance(x_np,
y_np,
epsilon=epsilon,
keepdim=keepdim)

self.assertEqual(static_ret.shape, excepted_value.shape)
self.assertEqual(dygraph_ret.shape, excepted_value.shape)
self.assertEqual(legacy_ret.shape, excepted_value.shape)

self.assertTrue(np.allclose(static_ret, excepted_value))
self.assertTrue(np.allclose(dygraph_ret, excepted_value))
self.assertTrue(np.allclose(legacy_ret, excepted_value))

static_functional_ret = test_static(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim,
functional=True)
dygraph_functional_ret = test_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim,
functional=True)
legacy_functional_ret = test_legacy_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim,
functional=True)

self.assertEqual(static_functional_ret.shape, excepted_value.shape)
self.assertEqual(dygraph_functional_ret.shape, excepted_value.shape)
self.assertEqual(legacy_functional_ret.shape, excepted_value.shape)

def test_pairwise_distance_different_p(self):
shape = [100, 100]
self.assertTrue(np.allclose(static_functional_ret, excepted_value))
self.assertTrue(np.allclose(dygraph_functional_ret, excepted_value))
self.assertTrue(np.allclose(legacy_functional_ret, excepted_value))

def test_pairwise_distance_broadcast_2(self):
shape_x = [100, 100]
shape_y = [100]
epsilon = 1e-6
keepdim = False
p = 3.0
x_np = np.random.random(shape).astype('float32')
y_np = np.random.random(shape).astype('float32')
static_ret = test_static(x_np, y_np, p=p, keepdim=keepdim)
dygraph_ret = test_dygraph(x_np, y_np, p=p, keepdim=keepdim)
excepted_value = pairwise_distance(x_np, y_np, p=p, keepdim=keepdim)
self.assertTrue(np.allclose(static_ret, dygraph_ret))
place = paddle.CPUPlace()
x_np = np.random.random(shape_x).astype('float32')
y_np = np.random.random(shape_y).astype('float32')
static_ret = test_static(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim)
dygraph_ret = test_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim)
legacy_ret = test_legacy_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim)
excepted_value = np_pairwise_distance(x_np,
y_np,
epsilon=epsilon,
keepdim=keepdim)

self.assertEqual(static_ret.shape, excepted_value.shape)
self.assertEqual(dygraph_ret.shape, excepted_value.shape)
self.assertEqual(legacy_ret.shape, excepted_value.shape)

self.assertTrue(np.allclose(static_ret, excepted_value))
self.assertTrue(np.allclose(dygraph_ret, excepted_value))
self.assertTrue(np.allclose(legacy_ret, excepted_value))

static_functional_ret = test_static(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim,
functional=True)
dygraph_functional_ret = test_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim,
functional=True)
legacy_functional_ret = test_legacy_dygraph(place=place,
x_np=x_np,
y_np=y_np,
epsilon=epsilon,
keepdim=keepdim,
functional=True)

self.assertEqual(static_functional_ret.shape, excepted_value.shape)
self.assertEqual(dygraph_functional_ret.shape, excepted_value.shape)
self.assertEqual(legacy_functional_ret.shape, excepted_value.shape)

self.assertTrue(np.allclose(static_functional_ret, excepted_value))
self.assertTrue(np.allclose(dygraph_functional_ret, excepted_value))
self.assertTrue(np.allclose(legacy_functional_ret, excepted_value))


if __name__ == "__main__":
Expand Down