chore: import upstream snapshot with attribution

test/legacy_test/test_affine_grid_function.py

@@ -0,0 +1,205 @@
+# 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()