# Copyright (c) 2009-2021, Google LLC # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # * Neither the name of Google LLC nor the # names of its contributors may be used to endorse or promote products # derived from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL Google LLC BE LIABLE FOR ANY # DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND # ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import unittest # begin:google_only # from google.protobuf.internal.numpy_test import * # end:google_only # begin:github_only # TODO(b/240447513) Delete workaround after numpy_test is open-sourced in # protobuf github. import unittest import numpy as np from google.protobuf import unittest_pb2 from google.protobuf.internal import testing_refleaks message = unittest_pb2.TestAllTypes() np_float_scalar = np.float64(0.0) np_1_float_array = np.zeros(shape=(1,), dtype=np.float64) np_2_float_array = np.zeros(shape=(2,), dtype=np.float64) np_11_float_array = np.zeros(shape=(1, 1), dtype=np.float64) np_22_float_array = np.zeros(shape=(2, 2), dtype=np.float64) np_int_scalar = np.int64(0) np_1_int_array = np.zeros(shape=(1,), dtype=np.int64) np_2_int_array = np.zeros(shape=(2,), dtype=np.int64) np_11_int_array = np.zeros(shape=(1, 1), dtype=np.int64) np_22_int_array = np.zeros(shape=(2, 2), dtype=np.int64) np_uint_scalar = np.uint64(0) np_1_uint_array = np.zeros(shape=(1,), dtype=np.uint64) np_2_uint_array = np.zeros(shape=(2,), dtype=np.uint64) np_11_uint_array = np.zeros(shape=(1, 1), dtype=np.uint64) np_22_uint_array = np.zeros(shape=(2, 2), dtype=np.uint64) np_bool_scalar = np.bool_(False) np_1_bool_array = np.zeros(shape=(1,), dtype=np.bool_) np_2_bool_array = np.zeros(shape=(2,), dtype=np.bool_) np_11_bool_array = np.zeros(shape=(1, 1), dtype=np.bool_) np_22_bool_array = np.zeros(shape=(2, 2), dtype=np.bool_) @testing_refleaks.TestCase class NumpyIntProtoTest(unittest.TestCase): # Assigning dim 1 ndarray of ints to repeated field should pass def testNumpyDim1IntArrayToRepeated_IsValid(self): message.repeated_int64[:] = np_1_int_array message.repeated_int64[:] = np_2_int_array message.repeated_uint64[:] = np_1_uint_array message.repeated_uint64[:] = np_2_uint_array # Assigning dim 2 ndarray of ints to repeated field should fail def testNumpyDim2IntArrayToRepeated_RaisesTypeError(self): with self.assertRaises(TypeError): message.repeated_int64[:] = np_11_int_array with self.assertRaises(TypeError): message.repeated_int64[:] = np_22_int_array with self.assertRaises(TypeError): message.repeated_uint64[:] = np_11_uint_array with self.assertRaises(TypeError): message.repeated_uint64[:] = np_22_uint_array # Assigning any ndarray of floats to repeated int field should fail def testNumpyFloatArrayToRepeated_RaisesTypeError(self): with self.assertRaises(TypeError): message.repeated_int64[:] = np_1_float_array with self.assertRaises(TypeError): message.repeated_int64[:] = np_11_float_array with self.assertRaises(TypeError): message.repeated_int64[:] = np_22_float_array # Assigning any np int to scalar field should pass def testNumpyIntScalarToScalar_IsValid(self): message.optional_int64 = np_int_scalar message.optional_uint64 = np_uint_scalar # Assigning any ndarray of ints to scalar field should fail def testNumpyIntArrayToScalar_RaisesTypeError(self): with self.assertRaises(TypeError): message.optional_int64 = np_1_int_array with self.assertRaises(TypeError): message.optional_int64 = np_11_int_array with self.assertRaises(TypeError): message.optional_int64 = np_22_int_array with self.assertRaises(TypeError): message.optional_uint64 = np_1_uint_array with self.assertRaises(TypeError): message.optional_uint64 = np_11_uint_array with self.assertRaises(TypeError): message.optional_uint64 = np_22_uint_array # Assigning any ndarray of floats to scalar field should fail def testNumpyFloatArrayToScalar_RaisesTypeError(self): with self.assertRaises(TypeError): message.optional_int64 = np_1_float_array with self.assertRaises(TypeError): message.optional_int64 = np_11_float_array with self.assertRaises(TypeError): message.optional_int64 = np_22_float_array @testing_refleaks.TestCase class NumpyFloatProtoTest(unittest.TestCase): # Assigning dim 1 ndarray of floats to repeated field should pass def testNumpyDim1FloatArrayToRepeated_IsValid(self): message.repeated_float[:] = np_1_float_array message.repeated_float[:] = np_2_float_array # Assigning dim 2 ndarray of floats to repeated field should fail def testNumpyDim2FloatArrayToRepeated_RaisesTypeError(self): with self.assertRaises(TypeError): message.repeated_float[:] = np_11_float_array with self.assertRaises(TypeError): message.repeated_float[:] = np_22_float_array # Assigning any np float to scalar field should pass def testNumpyFloatScalarToScalar_IsValid(self): message.optional_float = np_float_scalar # Assigning any ndarray of float to scalar field should fail def testNumpyFloatArrayToScalar_RaisesTypeError(self): with self.assertRaises(TypeError): message.optional_float = np_1_float_array with self.assertRaises(TypeError): message.optional_float = np_11_float_array with self.assertRaises(TypeError): message.optional_float = np_22_float_array @testing_refleaks.TestCase class NumpyBoolProtoTest(unittest.TestCase): # Assigning dim 1 ndarray of bool to repeated field should pass def testNumpyDim1BoolArrayToRepeated_IsValid(self): message.repeated_bool[:] = np_1_bool_array message.repeated_bool[:] = np_2_bool_array # Assigning dim 2 ndarray of bool to repeated field should fail def testNumpyDim2BoolArrayToRepeated_RaisesTypeError(self): with self.assertRaises(TypeError): message.repeated_bool[:] = np_11_bool_array with self.assertRaises(TypeError): message.repeated_bool[:] = np_22_bool_array # Assigning any np bool to scalar field should pass def testNumpyBoolScalarToScalar_IsValid(self): message.optional_bool = np_bool_scalar # Assigning any ndarray of bool to scalar field should fail def testNumpyBoolArrayToScalar_RaisesTypeError(self): with self.assertRaises(TypeError): message.optional_bool = np_1_bool_array with self.assertRaises(TypeError): message.optional_bool = np_11_bool_array with self.assertRaises(TypeError): message.optional_bool = np_22_bool_array @testing_refleaks.TestCase class NumpyProtoIndexingTest(unittest.TestCase): def testNumpyIntScalarIndexing_Passes(self): data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2]) self.assertEqual(0, data.repeated_int64[np.int64(0)]) def testNumpyNegative1IntScalarIndexing_Passes(self): data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2]) self.assertEqual(2, data.repeated_int64[np.int64(-1)]) def testNumpyFloatScalarIndexing_Fails(self): data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2]) with self.assertRaises(TypeError): _ = data.repeated_int64[np.float64(0.0)] def testNumpyIntArrayIndexing_Fails(self): data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2]) with self.assertRaises(TypeError): _ = data.repeated_int64[np.array([0])] with self.assertRaises(TypeError): _ = data.repeated_int64[np.ndarray((1,), buffer=np.array([0]), dtype=int)] with self.assertRaises(TypeError): _ = data.repeated_int64[np.ndarray((1, 1), buffer=np.array([0]), dtype=int)] # end:github_only if __name__ == '__main__': unittest.main(verbosity=2)