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Paddle/python/paddle/fluid/tests/unittests/test_grid_sample_function.py

142 lines
4.5 KiB

# 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 numpy as np
import paddle
from paddle import fluid, nn
import paddle.fluid.dygraph as dg
import paddle.nn.functional as F
import unittest
class GridSampleTestCase(unittest.TestCase):
def __init__(self,
methodName='runTest',
x_shape=[2, 2, 3, 3],
grid_shape=[2, 3, 3, 2],
mode="bilinear",
padding_mode="zeros",
align_corners=False):
super(GridSampleTestCase, self).__init__(methodName)
self.padding_mode = padding_mode
self.x_shape = x_shape
self.grid_shape = grid_shape
self.mode = mode
self.padding_mode = padding_mode
self.align_corners = align_corners
self.dtype = "float64"
def setUp(self):
self.x = np.random.randn(*(self.x_shape)).astype(self.dtype)
self.grid = np.random.uniform(-1, 1, self.grid_shape).astype(self.dtype)
def static_functional(self, place):
main = fluid.Program()
start = fluid.Program()
with fluid.unique_name.guard():
with fluid.program_guard(main, start):
x = fluid.data("x", self.x_shape, dtype=self.dtype)
grid = fluid.data("grid", self.grid_shape, dtype=self.dtype)
y_var = F.grid_sample(
x,
grid,
mode=self.mode,
padding_mode=self.padding_mode,
align_corners=self.align_corners)
feed_dict = {"x": self.x, "grid": self.grid}
exe = fluid.Executor(place)
exe.run(start)
y_np, = exe.run(main, feed=feed_dict, fetch_list=[y_var])
return y_np
def dynamic_functional(self):
x_t = paddle.to_tensor(self.x)
grid_t = paddle.to_tensor(self.grid)
y_t = F.grid_sample(
x_t,
grid_t,
mode=self.mode,
padding_mode=self.padding_mode,
align_corners=self.align_corners)
y_np = y_t.numpy()
return y_np
def _test_equivalence(self, place):
result1 = self.static_functional(place)
with dg.guard(place):
result2 = self.dynamic_functional()
np.testing.assert_array_almost_equal(result1, result2)
def runTest(self):
place = fluid.CPUPlace()
self._test_equivalence(place)
if fluid.core.is_compiled_with_cuda():
place = fluid.CUDAPlace(0)
self._test_equivalence(place)
class GridSampleErrorTestCase(GridSampleTestCase):
def runTest(self):
place = fluid.CPUPlace()
with self.assertRaises(ValueError):
self.static_functional(place)
def add_cases(suite):
suite.addTest(GridSampleTestCase(methodName='runTest'))
suite.addTest(
GridSampleTestCase(
methodName='runTest',
mode='bilinear',
padding_mode='reflection',
align_corners=True))
suite.addTest(
GridSampleTestCase(
methodName='runTest',
mode='bilinear',
padding_mode='zeros',
align_corners=True))
def add_error_cases(suite):
suite.addTest(
GridSampleErrorTestCase(
methodName='runTest', padding_mode="VALID"))
suite.addTest(
GridSampleErrorTestCase(
methodName='runTest', align_corners="VALID"))
suite.addTest(GridSampleErrorTestCase(methodName='runTest', mode="VALID"))
def load_tests(loader, standard_tests, pattern):
suite = unittest.TestSuite()
add_cases(suite)
add_error_cases(suite)
return suite
class TestGridSampleAPI(unittest.TestCase):
def test_errors(self):
with self.assertRaises(ValueError):
x = paddle.randn([1, 1, 3, 3])
F.grid_sample(x, 1.0)
with self.assertRaises(ValueError):
x = paddle.randn([1, 1, 3, 3])
F.grid_sample(1.0, x)
if __name__ == '__main__':
unittest.main()