wehub-resource-sync
70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import paddle
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paddle.enable_static()
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import numpy as np
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from paddle.base.core import PaddleDType, PaddleTensor
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class TestInferenceApi(unittest.TestCase):
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def test_inference_api(self):
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tensor32 = np.random.randint(10, 20, size=[20, 2]).astype('int32')
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paddletensor32 = PaddleTensor(tensor32)
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dtype32 = paddletensor32.dtype
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self.assertEqual(dtype32, PaddleDType.INT32)
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self.assertEqual(
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paddletensor32.data.tolist('int32'), tensor32.ravel().tolist()
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)
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paddletensor32.data.reset(tensor32)
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self.assertEqual(
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paddletensor32.as_ndarray().ravel().tolist(),
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tensor32.ravel().tolist(),
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)
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tensor64 = np.random.randint(10, 20, size=[20, 2]).astype('int64')
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paddletensor64 = PaddleTensor(tensor64)
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dtype64 = paddletensor64.dtype
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self.assertEqual(dtype64, PaddleDType.INT64)
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self.assertEqual(
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paddletensor64.data.tolist('int64'), tensor64.ravel().tolist()
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)
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paddletensor64.data.reset(tensor64)
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self.assertEqual(
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paddletensor64.as_ndarray().ravel().tolist(),
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tensor64.ravel().tolist(),
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)
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tensor_float = np.random.randn(20, 2).astype('float32')
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paddletensor_float = PaddleTensor(tensor_float)
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dtype_float = paddletensor_float.dtype
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self.assertEqual(dtype_float, PaddleDType.FLOAT32)
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self.assertEqual(
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paddletensor_float.data.tolist('float32'),
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tensor_float.ravel().tolist(),
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)
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paddletensor_float.data.reset(tensor_float)
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self.assertEqual(
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paddletensor_float.as_ndarray().ravel().tolist(),
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tensor_float.ravel().tolist(),
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)
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if __name__ == '__main__':
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unittest.main()
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