# 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 if __name__ == '__main__': unittest.main()