Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

【PIR API adaptor No.266、269】 Migrate ldexp, logaddexp into pir #59582

Merged
merged 6 commits into from
Dec 7, 2023
Merged

【PIR API adaptor No.266、269】 Migrate ldexp, logaddexp into pir #59582

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
0942a55
fix
enkilee Dec 1, 2023
6287de5
fix
enkilee Dec 1, 2023
c2fb6f9
fix
enkilee Dec 1, 2023
7294657
fix
enkilee Dec 5, 2023
8aa8b8b
fix value
enkilee Dec 6, 2023
b5b506a
fix value
enkilee Dec 6, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 4 additions & 2 deletions python/paddle/tensor/math.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6987,12 +6987,14 @@ def ldexp(x, y, name=None):
[4. , 8. , 12.])

"""
if not isinstance(x, (paddle.Tensor, Variable)):
if not isinstance(x, (paddle.Tensor, Variable, paddle.pir.Value)):
raise TypeError(f"x must be tensor type, but got {type(x)}")
if not isinstance(y, (paddle.Tensor, Variable)):
if not isinstance(y, (paddle.Tensor, Variable, paddle.pir.Value)):
raise TypeError(f"y must be tensor type, but got {type(y)}")
if x.dtype == paddle.float64 or y.dtype == paddle.float64:
out_dtype = paddle.float64
elif x.dtype == DataType.FLOAT64 or y.dtype == DataType.FLOAT64:
out_dtype = DataType.FLOAT64
else:
out_dtype = paddle.get_default_dtype()
x = paddle.cast(x, dtype=out_dtype)
Expand Down
177 changes: 110 additions & 67 deletions test/legacy_test/test_ldexp.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,58 +18,64 @@

import paddle
from paddle.base import core
from paddle.static import Program, program_guard
from paddle.pir_utils import test_with_pir_api

DYNAMIC = 1
STATIC = 2


def _run_ldexp(mode, x, y, device='cpu'):
def _run_ldexp_dynamic(x, y, device='cpu'):
# dynamic mode
if mode == DYNAMIC:
paddle.disable_static()
# Set device
paddle.set_device(device)
x_ = paddle.to_tensor(x)
# y is scalar
if isinstance(y, (int)):
y_ = y
# y is tensor
else:
y_ = paddle.to_tensor(y)
res = paddle.ldexp(x_, y_)
return res.numpy()
paddle.disable_static()
# Set device
paddle.set_device(device)
x_ = paddle.to_tensor(x)
# y is scalar
if isinstance(y, (int)):
y_ = y
# y is tensor
else:
y_ = paddle.to_tensor(y)
res = paddle.ldexp(x_, y_)
return res.numpy()


def _run_ldexp_static(x, y, device='cpu'):
# static graph mode
elif mode == STATIC:
paddle.enable_static()
# y is scalar
if isinstance(y, (int)):
with program_guard(Program(), Program()):
x_ = paddle.static.data(name="x", shape=x.shape, dtype=x.dtype)
y_ = y
res = paddle.ldexp(x_, y_)
place = (
paddle.CPUPlace()
if device == 'cpu'
else paddle.CUDAPlace(0)
)
exe = paddle.static.Executor(place)
outs = exe.run(feed={'x': x, 'y': y}, fetch_list=[res])
return outs[0]
# y is tensor
else:
with program_guard(Program(), Program()):
x_ = paddle.static.data(name="x", shape=x.shape, dtype=x.dtype)
y_ = paddle.static.data(name="y", shape=y.shape, dtype=y.dtype)
res = paddle.ldexp(x_, y_)
place = (
paddle.CPUPlace()
if device == 'cpu'
else paddle.CUDAPlace(0)
)
exe = paddle.static.Executor(place)
outs = exe.run(feed={'x': x, 'y': y}, fetch_list=[res])
return outs[0]
paddle.enable_static()
# y is scalar
if isinstance(y, (int)):
with paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
):
x_ = paddle.static.data(name="x", shape=x.shape, dtype=x.dtype)
y_ = y
res = paddle.ldexp(x_, y_)
place = (
paddle.CPUPlace() if device == 'cpu' else paddle.CUDAPlace(0)
)
exe = paddle.static.Executor(place)
outs = exe.run(
paddle.static.default_main_program(),
feed={'x': x, 'y': y},
fetch_list=[res],
)
return outs[0]
# y is tensor
else:
with paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
):
x_ = paddle.static.data(name="x", shape=x.shape, dtype=x.dtype)
y_ = paddle.static.data(name="y", shape=y.shape, dtype=y.dtype)
res = paddle.ldexp(x_, y_)
place = (
paddle.CPUPlace() if device == 'cpu' else paddle.CUDAPlace(0)
)
exe = paddle.static.Executor(place)
outs = exe.run(
paddle.static.default_main_program(),
feed={'x': x, 'y': y},
fetch_list=[res],
)
return outs[0]


def check_dtype(input, desired_dtype):
Expand All @@ -81,54 +87,94 @@ def check_dtype(input, desired_dtype):
)


class TestLdexpAPI(unittest.TestCase):
class TestLdexpAPIWithDynamic(unittest.TestCase):
def setUp(self):
self.places = ['cpu']
if core.is_compiled_with_cuda():
self.places.append('gpu')

def test_ldexp(self):
def test_ldexp_dynamic(self):
np.random.seed(7)
for place in self.places:
# test 1-d float tensor and 1-d int tensor
dims = (np.random.randint(200, 300),)
x = (np.random.rand(*dims) * 10).astype(np.float64)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp(DYNAMIC, x, y, place)
check_dtype(res, np.float64)
np.testing.assert_allclose(res, np.ldexp(x, y))
res = _run_ldexp(STATIC, x, y, place)
res = _run_ldexp_dynamic(x, y, place)
check_dtype(res, np.float64)
np.testing.assert_allclose(res, np.ldexp(x, y))

dims = (np.random.randint(200, 300),)
x = (np.random.rand(*dims) * 10).astype(np.float32)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp(DYNAMIC, x, y, place)
check_dtype(res, np.float32)
np.testing.assert_allclose(res, np.ldexp(x, y))
res = _run_ldexp(STATIC, x, y, place)
res = _run_ldexp_dynamic(x, y, place)
check_dtype(res, np.float32)
np.testing.assert_allclose(res, np.ldexp(x, y))

# test 1-d int tensor and 1-d int tensor
dims = (np.random.randint(200, 300),)
x = (np.random.randint(-10, 10, dims)).astype(np.int64)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp(DYNAMIC, x, y, place)
res = _run_ldexp_dynamic(x, y, place)
check_dtype(res, np.float32)
np.testing.assert_allclose(res, np.ldexp(x, y))
res = _run_ldexp(STATIC, x, y, place)

dims = (np.random.randint(200, 300),)
x = (np.random.randint(-10, 10, dims)).astype(np.int32)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp_dynamic(x, y, place)
check_dtype(res, np.float32)
np.testing.assert_allclose(res, np.ldexp(x, y))

# test broadcast
dims = (
np.random.randint(1, 10),
np.random.randint(5, 10),
np.random.randint(5, 10),
)
x = (np.random.rand(*dims) * 10).astype(np.float64)
y = (np.random.randint(-10, 10, dims[-1])).astype(np.int32)
res = _run_ldexp_dynamic(x, y)
check_dtype(res, np.float64)
np.testing.assert_allclose(res, np.ldexp(x, y))


class TestLdexpAPIWithStatic(unittest.TestCase):
def setUp(self):
self.places = ['cpu']
if core.is_compiled_with_cuda():
self.places.append('gpu')

@test_with_pir_api
def test_ldexp_static(self):
np.random.seed(7)
for place in self.places:
dims = (np.random.randint(200, 300),)
x = (np.random.randint(-10, 10, dims)).astype(np.int32)
x = (np.random.rand(*dims) * 10).astype(np.float64)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp_static(x, y, place)
check_dtype(res, np.float64)
np.testing.assert_allclose(res, np.ldexp(x, y))

dims = (np.random.randint(200, 300),)
x = (np.random.rand(*dims) * 10).astype(np.float32)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp(DYNAMIC, x, y, place)
res = _run_ldexp_static(x, y, place)
check_dtype(res, np.float32)
np.testing.assert_allclose(res, np.ldexp(x, y))
res = _run_ldexp(STATIC, x, y, place)

# test 1-d int tensor and 1-d int tensor
dims = (np.random.randint(200, 300),)
x = (np.random.randint(-10, 10, dims)).astype(np.int64)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp_static(x, y, place)
check_dtype(res, np.float32)
np.testing.assert_allclose(res, np.ldexp(x, y))

dims = (np.random.randint(200, 300),)
x = (np.random.randint(-10, 10, dims)).astype(np.int32)
y = (np.random.randint(-10, 10, dims)).astype(np.int32)
res = _run_ldexp_static(x, y, place)
check_dtype(res, np.float32)
np.testing.assert_allclose(res, np.ldexp(x, y))

Expand All @@ -140,10 +186,7 @@ def test_ldexp(self):
)
x = (np.random.rand(*dims) * 10).astype(np.float64)
y = (np.random.randint(-10, 10, dims[-1])).astype(np.int32)
res = _run_ldexp(DYNAMIC, x, y)
check_dtype(res, np.float64)
np.testing.assert_allclose(res, np.ldexp(x, y))
res = _run_ldexp(STATIC, x, y)
res = _run_ldexp_static(x, y)
check_dtype(res, np.float64)
np.testing.assert_allclose(res, np.ldexp(x, y))

Expand Down