Squashed 'libs/protobuf/' content from commit fcd3b9a85
git-subtree-dir: libs/protobuf git-subtree-split: fcd3b9a85ef36e46643dc30176cea1a7ad62e02b
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Henry Winkel
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python/google/protobuf/internal/numpy_test.py
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python/google/protobuf/internal/numpy_test.py
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# Protocol Buffers - Google's data interchange format
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# Copyright 2008 Google Inc. All rights reserved.
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# https://developers.google.com/protocol-buffers/
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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
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# met:
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#
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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
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# copyright notice, this list of conditions and the following disclaimer
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# in the documentation and/or other materials provided with the
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# distribution.
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# * Neither the name of Google Inc. nor the names of its
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# contributors may be used to endorse or promote products derived from
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# 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
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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# 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
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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"""Test use of numpy types with repeated and non-repeated scalar fields."""
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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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if __name__ == '__main__':
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unittest.main()
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