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

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merged 6 commits into from
Dec 7, 2023
Merged

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

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0942a55
fix
enkilee Dec 1, 2023
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enkilee Dec 1, 2023
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enkilee Dec 1, 2023
7294657
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enkilee Dec 5, 2023
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enkilee Dec 6, 2023
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12 changes: 8 additions & 4 deletions python/paddle/tensor/math.py
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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.OpResult))):
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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.OpResult))):
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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 All @@ -7006,12 +7008,14 @@ def ldexp_(x, y, name=None):
Inplace version of ``polygamma`` API, the output Tensor will be inplaced with input ``x``.
Please refer to :ref:`api_paddle_polygamma`.
"""
if not isinstance(x, (paddle.Tensor, Variable)):
if not isinstance(x, (paddle.Tensor, (Variable, paddle.pir.OpResult))):
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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.OpResult))):
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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:
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out_dtype = DataType.FLOAT64
else:
out_dtype = paddle.get_default_dtype()
x = paddle.cast_(x, dtype=out_dtype)
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177 changes: 110 additions & 67 deletions test/legacy_test/test_ldexp.py
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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