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2026-07-13 12:40:42 +08:00

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Python

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
import numpy as np
from op_test import get_device_place, is_custom_device
import paddle
import paddle.base.dygraph as dg
import paddle.nn.functional as F
from paddle import base
class AffineGridTestCase(unittest.TestCase):
def __init__(
self,
methodName='runTest',
theta_shape=(20, 2, 3),
output_shape=[20, 2, 5, 7],
align_corners=True,
dtype="float32",
invalid_theta=False,
variable_output_shape=False,
):
super().__init__(methodName)
self.theta_shape = theta_shape
self.output_shape = output_shape
self.align_corners = align_corners
self.dtype = dtype
self.invalid_theta = invalid_theta
self.variable_output_shape = variable_output_shape
def setUp(self):
self.theta = np.random.randn(*(self.theta_shape)).astype(self.dtype)
def base_layer(self, place):
paddle.enable_static()
with (
base.unique_name.guard(),
paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
),
):
theta_var = paddle.static.data(
"input", self.theta_shape, dtype=self.dtype
)
y_var = paddle.nn.functional.affine_grid(
theta_var, self.output_shape
)
feed_dict = {"input": self.theta}
exe = paddle.static.Executor(place)
(y_np,) = exe.run(
paddle.static.default_main_program(),
feed=feed_dict,
fetch_list=[y_var],
)
return y_np
def functional(self, place):
paddle.enable_static()
with (
base.unique_name.guard(),
paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
),
):
theta_var = paddle.static.data(
"input", self.theta_shape, dtype=self.dtype
)
y_var = F.affine_grid(
theta_var,
self.output_shape,
align_corners=self.align_corners,
)
feed_dict = {"input": self.theta}
exe = paddle.static.Executor(place)
(y_np,) = exe.run(
paddle.static.default_main_program(),
feed=feed_dict,
fetch_list=[y_var],
)
return y_np
def test_static_api(self):
place = base.CPUPlace()
paddle.enable_static()
with (
base.unique_name.guard(),
paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
),
):
align_corners = True
theta_var = paddle.static.data(
"input", self.theta_shape, dtype=self.dtype
)
y_var = paddle.nn.functional.affine_grid(
theta_var, self.output_shape
)
y_var2 = F.affine_grid(
theta_var,
self.output_shape,
align_corners=align_corners,
)
feed_dict = {"input": self.theta}
exe = paddle.static.Executor(place)
(y_np, y_np2) = exe.run(
paddle.static.default_main_program(),
feed=feed_dict,
fetch_list=[y_var, y_var2],
)
np.testing.assert_array_almost_equal(y_np, y_np2)
def paddle_dygraph_layer(self):
paddle.disable_static()
theta_var = (
paddle.to_tensor(self.theta)
if not self.invalid_theta
else "invalid"
)
output_shape = (
paddle.to_tensor(self.output_shape)
if self.variable_output_shape
else self.output_shape
)
y_var = F.affine_grid(
theta_var, output_shape, align_corners=self.align_corners
)
y_np = y_var.numpy()
return y_np
def _test_equivalence(self, place):
place = base.CPUPlace()
result1 = self.base_layer(place)
result2 = self.functional(place)
result3 = self.paddle_dygraph_layer()
if self.align_corners:
np.testing.assert_array_almost_equal(result1, result2)
np.testing.assert_array_almost_equal(result2, result3)
def runTest(self):
place = base.CPUPlace()
self._test_equivalence(place)
if base.core.is_compiled_with_cuda() or is_custom_device():
place = get_device_place()
self._test_equivalence(place)
class AffineGridErrorTestCase(AffineGridTestCase):
def runTest(self):
place = base.CPUPlace()
with dg.guard(place), self.assertRaises(TypeError):
self.paddle_dygraph_layer()
def add_cases(suite):
suite.addTest(AffineGridTestCase(methodName='runTest'))
suite.addTest(AffineGridTestCase(methodName='runTest', align_corners=True))
suite.addTest(AffineGridTestCase(methodName='runTest', align_corners=False))
suite.addTest(
AffineGridTestCase(methodName='runTest', variable_output_shape=True)
)
suite.addTest(
AffineGridTestCase(
methodName='runTest',
theta_shape=(20, 2, 3),
output_shape=[20, 1, 7, 7],
align_corners=True,
)
)
def add_error_cases(suite):
suite.addTest(
AffineGridErrorTestCase(methodName='runTest', output_shape="not_valid")
)
suite.addTest(
AffineGridErrorTestCase(methodName='runTest', invalid_theta=True)
) # to test theta not variable error checking
def load_tests(loader, standard_tests, pattern):
suite = unittest.TestSuite()
add_cases(suite)
add_error_cases(suite)
return suite
if __name__ == '__main__':
unittest.main()