Protocol Buffers - Google's data interchange format (grpc依赖)
https://developers.google.com/protocol-buffers/
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214 lines
8.7 KiB
214 lines
8.7 KiB
# 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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