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