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【PIR API adaptor No.300、305、306】Migrate SigmoidTransform、StackTransform、StickBreakingTransform into pir #60325

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Merged
changeyoung98 merged 4 commits into from
Dec 27, 2023
Merged

【PIR API adaptor No.300、305、306】Migrate SigmoidTransform、StackTransform、StickBreakingTransform into pir #60325

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fe32845
SigmoidTransform pir passed
changeyoung98 Dec 25, 2023
40f7694
StackTransform and StickBreakingTransform pir passed
changeyoung98 Dec 25, 2023
3da8dc3
move tests to _static.py
changeyoung98 Dec 26, 2023
a0901fb
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
changeyoung98 Dec 26, 2023
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18 changes: 13 additions & 5 deletions python/paddle/distribution/transform.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -166,7 +166,9 @@ def forward(self, x):
Returns:
Tensor: Outcome of forward transformation.
"""
if not isinstance(x, paddle.base.framework.Variable):
if not isinstance(
x, (paddle.base.framework.Variable, paddle.pir.Value)
):
raise TypeError(
f"Expected 'x' is a Tensor or Real, but got {type(x)}."
)
Expand All @@ -187,7 +189,9 @@ def inverse(self, y):
Returns:
Tensor: Outcome of inverse transform.
"""
if not isinstance(y, paddle.base.framework.Variable):
if not isinstance(
y, (paddle.base.framework.Variable, paddle.pir.Value)
):
raise TypeError(
f"Expected 'y' is a Tensor or Real, but got {type(y)}."
)
Expand All @@ -209,12 +213,14 @@ def forward_log_det_jacobian(self, x):
Returns:
Tensor: The log of the absolute value of Jacobian determinant.
"""
if not isinstance(x, paddle.base.framework.Variable):
if not isinstance(
x, (paddle.base.framework.Variable, paddle.pir.Value)
):
raise TypeError(
f"Expected 'y' is a Tensor or Real, but got {type(x)}."
)
if (
isinstance(x, paddle.base.framework.Variable)
isinstance(x, (paddle.base.framework.Variable, paddle.pir.Value))
and x.dim() < self._domain.event_rank
):
raise ValueError(
Expand All @@ -241,7 +247,9 @@ def inverse_log_det_jacobian(self, y):
Returns:
Tensor: The value of :math:`log|det J_{f^{-1}}(y)|`.
"""
if not isinstance(y, paddle.base.framework.Variable):
if not isinstance(
y, (paddle.base.framework.Variable, paddle.pir.Value)
):
raise TypeError(f"Expected 'y' is a Tensor, but got {type(y)}.")
if y.dim() < self._codomain.event_rank:
raise ValueError(
Expand Down
213 changes: 213 additions & 0 deletions test/distribution/test_distribution_transform.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@

import paddle
from paddle.distribution import transform, variable
from paddle.pir_utils import test_with_pir_api

np.random.seed(2022)
paddle.seed(2022)
Expand Down Expand Up @@ -1067,6 +1068,31 @@ def test_forward(self, input, expected):
atol=config.ATOL.get(str(input.dtype)),
)

@param.param_func(
((np.ones((5, 10)), 1 / (1 + np.exp(-np.ones((5, 10))))),)
)
@test_with_pir_api
def test_forward_static(self, input, expected):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.SigmoidTransform()
out = model.forward(x)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
np.testing.assert_allclose(
result,
expected,
rtol=config.RTOL.get(str(input.dtype)),
atol=config.ATOL.get(str(input.dtype)),
)
paddle.disable_static()

@param.param_func(
((np.ones(10), np.log(np.ones(10)) - np.log1p(-np.ones(10))),)
)
Expand All @@ -1078,6 +1104,31 @@ def test_inverse(self, input, expected):
atol=config.ATOL.get(str(input.dtype)),
)

@param.param_func(
((np.ones(10), np.log(np.ones(10)) - np.log1p(-np.ones(10))),)
)
@test_with_pir_api
def test_inverse_static(self, input, expected):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.SigmoidTransform()
out = model.inverse(x)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
np.testing.assert_allclose(
result,
expected,
rtol=config.RTOL.get(str(input.dtype)),
atol=config.ATOL.get(str(input.dtype)),
)
paddle.disable_static()

@param.param_func(
(
(
Expand All @@ -1094,6 +1145,36 @@ def test_forward_log_det_jacobian(self, input, expected):
atol=config.ATOL.get(str(input.dtype)),
)

@param.param_func(
(
(
np.ones(10),
-_np_softplus(-np.ones(10)) - _np_softplus(np.ones(10)),
),
)
)
@test_with_pir_api
def test_forward_log_det_jacobian_static(self, input, expected):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.SigmoidTransform()
out = model.forward_log_det_jacobian(x)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
np.testing.assert_allclose(
result,
expected,
rtol=config.RTOL.get(str(input.dtype)),
atol=config.ATOL.get(str(input.dtype)),
)
paddle.disable_static()

@param.param_func([((), ()), ((2, 3, 5), (2, 3, 5))])
def test_forward_shape(self, shape, expected_shape):
self.assertEqual(self._t.forward_shape(shape), expected_shape)
Expand All @@ -1112,6 +1193,24 @@ def test_zerodim(self, input, expected):
self.assertEqual(self._t.forward_shape(x.shape), [])
self.assertEqual(self._t.inverse_shape(x.shape), [])

@param.param_func([(np.array(1.0), np.array(1.0))])
@test_with_pir_api
def test_zerodim_static(self, input, expected):
paddle.enable_static()
shape = ()
if paddle.framework.in_pir_mode():
shape = []
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, 'float32')
model = transform.SigmoidTransform()
self.assertEqual(model.forward(x).shape, shape)
self.assertEqual(model.inverse(x).shape, shape)
self.assertEqual(model.forward_log_det_jacobian(x).shape, shape)
self.assertEqual(model.inverse_log_det_jacobian(x).shape, shape)
self.assertEqual(model.forward_shape(x.shape), shape)
self.assertEqual(model.inverse_shape(x.shape), shape)
paddle.disable_static()


class TestSoftmaxTransform(unittest.TestCase):
def setUp(self):
Expand Down Expand Up @@ -1196,6 +1295,30 @@ def test_forward(self, input):
atol=config.ATOL.get(str(input.dtype)),
)

@param.param_func(((np.random.random(10),),))
@test_with_pir_api
def test_forward_static(self, input):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.StickBreakingTransform()
fwd = model.forward(x)
out = model.inverse(fwd)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
np.testing.assert_allclose(
result,
input,
rtol=config.RTOL.get(str(input.dtype)),
atol=config.ATOL.get(str(input.dtype)),
)
paddle.disable_static()

@param.param_func([((2, 3, 5), (2, 3, 6))])
def test_forward_shape(self, shape, expected_shape):
self.assertEqual(self._t.forward_shape(shape), expected_shape)
Expand All @@ -1210,6 +1333,24 @@ def test_forward_log_det_jacobian(self, x):
self._t.forward_log_det_jacobian(paddle.to_tensor(x)).shape, []
)

@param.param_func(((np.random.random(10),),))
@test_with_pir_api
def test_forward_log_det_jacobian_static(self, input):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.StickBreakingTransform()
out = model.forward_log_det_jacobian(x)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
self.assertEqual(result.shape, ())
paddle.disable_static()


# Todo
@param.place(config.DEVICES)
Expand Down Expand Up @@ -1243,6 +1384,29 @@ def test_forward(self, input):
tuple(self._t.forward(paddle.to_tensor(input)).shape), input.shape
)

@param.param_func(
[
(np.array([[0.0, 1.0, 2.0, 3.0]]),),
(np.array([[-5.0, 6.0, 7.0, 8.0]]),),
]
)
@test_with_pir_api
def test_forward_static(self, input):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.StackTransform(self.transforms, self.axis)
out = model.forward(x)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
self.assertEqual(tuple(result.shape), input.shape)
paddle.disable_static()

@param.param_func(
[
(np.array([[1.0, 2.0, 3.0]]),),
Expand All @@ -1258,6 +1422,33 @@ def test_inverse(self, input):
tuple(self._t.inverse(paddle.to_tensor(input)).shape), input.shape
)

@param.param_func(
[
(np.array([[1.0, 2.0, 3.0]]),),
(
np.array(
[[6.0, 7.0, 8.0]],
),
),
]
)
@test_with_pir_api
def test_inverse_static(self, input):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.StackTransform(self.transforms, self.axis)
out = model.inverse(x)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
self.assertEqual(tuple(result.shape), input.shape)
paddle.disable_static()

@param.param_func(
[(np.array([[1.0, 2.0, 3.0]]),), (np.array([[6.0, 7.0, 8.0]]),)]
)
Expand All @@ -1269,6 +1460,26 @@ def test_forward_log_det_jacobian(self, input):
input.shape,
)

@param.param_func(
[(np.array([[1.0, 2.0, 3.0]]),), (np.array([[6.0, 7.0, 8.0]]),)]
)
@test_with_pir_api
def test_forward_log_det_jacobian_static(self, input):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program()):
x = paddle.static.data('X', input.shape, input.dtype)
model = transform.StackTransform(self.transforms, self.axis)
out = model.forward_log_det_jacobian(x)
place = (
paddle.CUDAPlace(0)
if paddle.core.is_compiled_with_cuda()
else paddle.CPUPlace()
)
exe = paddle.static.Executor(place)
(result,) = exe.run(feed={'X': input}, fetch_list=[out])
self.assertEqual(tuple(result.shape), input.shape)
paddle.disable_static()

@param.param_func([((), ()), ((2, 3, 5), (2, 3, 5))])
def test_forward_shape(self, shape, expected_shape):
self.assertEqual(self._t.forward_shape(shape), expected_shape)
Expand All @@ -1287,10 +1498,12 @@ def test_axis(self):
([paddle.distribution.ExpTransform()], 'axis', TypeError),
]
)
@test_with_pir_api
def test_init_exception(self, transforms, axis, exc):
with self.assertRaises(exc):
paddle.distribution.StackTransform(transforms, axis)

@test_with_pir_api
def test_transforms(self):
self.assertIsInstance((self._t.transforms), typing.Sequence)

Expand Down