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fix pad outliers err #34979

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merged 7 commits into from
Aug 18, 2021
Merged

fix pad outliers err #34979

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a695dbd
fix pad outliers err
littletomatodonkey Aug 17, 2021
5624761
fix pad api input type and doc
littletomatodonkey Aug 17, 2021
217e07c
fix example of pad
littletomatodonkey Aug 17, 2021
4ae7875
add unittest for pad3d
littletomatodonkey Aug 18, 2021
5eabd17
fix unittest
littletomatodonkey Aug 18, 2021
2a597f8
fix error format
littletomatodonkey Aug 18, 2021
e98a7f1
fix pad doc
littletomatodonkey Aug 18, 2021
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7 changes: 7 additions & 0 deletions paddle/fluid/operators/pad3d_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -567,6 +567,13 @@ class Pad3dCPUKernel : public framework::OpKernel<T> {
in_width, pads[1]));
}

if (mode == "circular") {
PADDLE_ENFORCE_NE(
in_depth * in_height * in_width, 0,
platform::errors::InvalidArgument(
"The input tensor size can not be 0 for circular padding mode."));
}

const int pad_left = pads[0];
const int pad_top = pads[2];
const int pad_front = pads[4];
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7 changes: 7 additions & 0 deletions paddle/fluid/operators/pad3d_op.cu
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Expand Up @@ -620,6 +620,13 @@ class Pad3dCUDAKernel : public framework::OpKernel<T> {
in_width, pads[1]));
}

if (mode == "circular") {
PADDLE_ENFORCE_NE(
in_depth * in_height * in_width, 0,
platform::errors::InvalidArgument(
"The input tensor size can not be 0 for circular padding mode."));
}

const int pad_left = pads[0];
const int pad_top = pads[2];
const int pad_front = pads[4];
Expand Down
64 changes: 41 additions & 23 deletions python/paddle/fluid/tests/unittests/test_pad3d_op.py
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Expand Up @@ -682,46 +682,64 @@ def test_class(self):


class TestPad3dOpError(unittest.TestCase):
def setUp(self):
self.places = [paddle.CPUPlace()]
if core.is_compiled_with_cuda():
self.places.append(paddle.CUDAPlace(0))

def test_errors(self):
def test_variable():
input_shape = (1, 2, 3, 4, 5)
data = np.random.rand(*input_shape).astype(np.float32)
F.pad(x=data, paddings=[1, 1, 1, 1, 1, 1])
y = F.pad(x=data, pad=[1, 1, 1, 1, 1, 1], data_format="NCDHW")

def test_reflect_1():
input_shape = (1, 2, 3, 4, 5)
data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.fluid.data(name="x", shape=input_shape)
y = F.pad(x, pad=[5, 6, 1, 1, 1, 1], value=1, mode='reflect')
place = paddle.CPUPlace()
exe = Executor(place)
outputs = exe.run(feed={'x': data}, fetch_list=[y.name])
x = paddle.to_tensor(data)
y = F.pad(x,
pad=[5, 6, 1, 1, 1, 1],
value=1,
mode='reflect',
data_format="NCDHW")

def test_reflect_2():
input_shape = (1, 2, 3, 4, 5)
data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.fluid.data(name="x", shape=input_shape)
y = F.pad(x, pad=[1, 1, 4, 3, 1, 1], value=1, mode='reflect')
place = paddle.CPUPlace()
exe = Executor(place)
outputs = exe.run(feed={'x': data}, fetch_list=[y.name])
x = paddle.to_tensor(data)
y = F.pad(x,
pad=[1, 1, 4, 3, 1, 1],
value=1,
mode='reflect',
data_format="NCDHW")

def test_reflect_3():
input_shape = (1, 2, 3, 4, 5)
data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.fluid.data(name="x", shape=input_shape)
y = F.pad(x, pad=[1, 1, 1, 1, 2, 3], value=1, mode='reflect')
place = paddle.CPUPlace()
exe = Executor(place)
outputs = exe.run(feed={'x': data}, fetch_list=[y.name])

self.assertRaises(TypeError, test_variable)

self.assertRaises(Exception, test_reflect_1)

self.assertRaises(Exception, test_reflect_2)
x = paddle.to_tensor(data)
y = F.pad(x,
pad=[1, 1, 1, 1, 2, 3],
value=1,
mode='reflect',
data_format="NCDHW")

def test_circular_1():
input_shape = (1, 2, 0, 4, 5)
data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.to_tensor(data)
y = F.pad(x,
pad=[1, 1, 1, 1, 2, 3],
mode='circular',
data_format="NCDHW")

self.assertRaises(Exception, test_reflect_3)
paddle.disable_static()
for place in self.places:
self.assertRaises(ValueError, test_variable)
self.assertRaises(Exception, test_reflect_1)
self.assertRaises(Exception, test_reflect_2)
self.assertRaises(Exception, test_reflect_3)
self.assertRaises(Exception, test_circular_1)
paddle.enable_static()


class TestPadDataformatError(unittest.TestCase):
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32 changes: 25 additions & 7 deletions python/paddle/nn/functional/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1160,12 +1160,13 @@ def pad(x, pad, mode='constant', value=0, data_format="NCHW", name=None):

Parameters:
x (Tensor): The input tensor with data type float32/double/int32/int64_t.
pad (Tensor | List[int32]): The padding size with data type int32. [len(padding)/2] dimensions
of input will be padded. 1. If input dimension is 3, then the pad has the form (pad_left,
pad (Tensor | List[int] | Tuple[int]): The padding size with data type int.
If mode is 'constant' and length of pad is twice as length of x dimension, then x will
be padded from the first dimension to the last dimension.
Else: 1. If input dimension is 3, then the pad has the form (pad_left,
pad_right). 2. If the input dimension is 4, then the pad has the form (pad_left, pad_right,
pad_top, pad_bottom). 3. If the input dimension is 5, then the pad has the form
(pad_left, pad_right, pad_top, pad_bottom, pad_front, pad_back).

mode (str): Four modes: 'constant' (default), 'reflect', 'replicate', 'circular'.
When in 'constant' mode, this op uses a constant value to pad the input tensor.
When in 'reflect' mode, uses reflection of the input boundaries to pad the input tensor.
Expand All @@ -1189,6 +1190,15 @@ def pad(x, pad, mode='constant', value=0, data_format="NCHW", name=None):
[4., 5., 6.]]]]]

Case 0:
pad = [0, 0, 0, 0, 0, 0, 1, 1, 0, 0],
mode = 'constant'
value = 0
Out = [[[[[0., 0., 0.],
[1., 2., 3.],
[4., 5., 6.],
[0., 0., 0.]]]]]

Case 1:
pad = [2, 2, 1, 1, 0, 0],
mode = 'constant'
value = 0
Expand All @@ -1197,23 +1207,23 @@ def pad(x, pad, mode='constant', value=0, data_format="NCHW", name=None):
[0. 0. 4. 5. 6. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]]]]

Case 1:
Case 2:
pad = [2, 2, 1, 1, 0, 0],
mode = 'reflect'
Out = [[[[[6. 5. 4. 5. 6. 5. 4.]
[3. 2. 1. 2. 3. 2. 1.]
[6. 5. 4. 5. 6. 5. 4.]
[3. 2. 1. 2. 3. 2. 1.]]]]]

Case 2:
Case 3:
pad = [2, 2, 1, 1, 0, 0],
mode = 'replicate'
Out = [[[[[1. 1. 1. 2. 3. 3. 3.]
[1. 1. 1. 2. 3. 3. 3.]
[4. 4. 4. 5. 6. 6. 6.]
[4. 4. 4. 5. 6. 6. 6.]]]]]

Case 3:
Case 4:
pad = [2, 2, 1, 1, 0, 0],
mode = 'circular'
Out = [[[[[5. 6. 4. 5. 6. 4. 5.]
Expand All @@ -1231,11 +1241,18 @@ def pad(x, pad, mode='constant', value=0, data_format="NCHW", name=None):
# example 1
x_shape = (1, 1, 3)
x = paddle.arange(np.prod(x_shape), dtype="float32").reshape(x_shape) + 1
y = F.pad(x, [2, 3], value=1, mode='constant', data_format="NCL")
y = F.pad(x, [0, 0, 0, 0, 2, 3], value=1, mode='constant', data_format="NCL")
print(y)
# [[[1. 1. 1. 2. 3. 1. 1. 1.]]]

# example 2
x_shape = (1, 1, 3)
x = paddle.arange(np.prod(x_shape), dtype="float32").reshape(x_shape) + 1
y = F.pad(x, [2, 3], value=1, mode='constant', data_format="NCL")
print(y)
# [[[1. 1. 1. 2. 3. 1. 1. 1.]]]

# example 3
x_shape = (1, 1, 2, 3)
x = paddle.arange(np.prod(x_shape), dtype="float32").reshape(x_shape) + 1
y = F.pad(x, [1, 2, 1, 1], value=1, mode='circular')
Expand Down Expand Up @@ -1295,6 +1312,7 @@ def pad(x, pad, mode='constant', value=0, data_format="NCHW", name=None):
unsqueezed_dim = [1]
x = unsqueeze(x, axis=unsqueezed_dim)
else:
pad = list(pad)
if data_format in ["NCL", "NCHW", "NCDHW"]:
data_format = "NCDHW"
if x_dim == 3:
Expand Down
2 changes: 1 addition & 1 deletion python/paddle/nn/layer/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@


def _npairs(x, n):
if isinstance(x, (paddle.Tensor, list)):
if isinstance(x, (paddle.Tensor, list, tuple)):
return x
x = [x] * (n * 2)
return x
Expand Down