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