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75 lines
3.2 KiB
75 lines
3.2 KiB
# 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 os, shutil
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import unittest
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import numpy as np
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import paddle.fluid as fluid
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from paddle.fluid.core import PaddleTensor
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from paddle.fluid.core import PaddleDType
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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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value32 = np.array(paddletensor32.data.int32_data()).reshape(*[20, 2])
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dtype32 = paddletensor32.dtype
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self.assertEqual(value32.all(), tensor32.all())
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self.assertEqual(dtype32, PaddleDType.INT32)
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self.assertEqual(
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type(paddletensor32.data.tolist('int32')), type(tensor32.tolist()))
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self.assertEqual(
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paddletensor32.data.tolist('int32'), tensor32.ravel().tolist())
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self.assertEqual(type(paddletensor32.as_ndarray()), type(tensor32))
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paddletensor32.data.reset(tensor32)
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self.assertEqual(paddletensor32.as_ndarray().all(), tensor32.all())
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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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value64 = np.array(paddletensor64.data.int64_data()).reshape(*[20, 2])
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dtype64 = paddletensor64.dtype
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self.assertEqual(value64.all(), tensor64.all())
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self.assertEqual(dtype64, PaddleDType.INT64)
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self.assertEqual(
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type(paddletensor64.data.tolist('int64')), type(tensor64.tolist()))
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self.assertEqual(
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paddletensor64.data.tolist('int64'), tensor64.ravel().tolist())
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self.assertEqual(type(paddletensor64.as_ndarray()), type(tensor64))
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paddletensor64.data.reset(tensor64)
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self.assertEqual(paddletensor64.as_ndarray().all(), tensor64.all())
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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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value_float = np.array(paddletensor_float.data.float_data()).reshape(
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*[20, 2])
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dtype_float = paddletensor_float.dtype
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self.assertEqual(value_float.all(), tensor_float.all())
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self.assertEqual(dtype_float, PaddleDType.FLOAT32)
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self.assertEqual(
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type(paddletensor_float.data.tolist('float32')),
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type(tensor_float.tolist()))
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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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self.assertEqual(
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type(paddletensor_float.as_ndarray()), type(tensor_float))
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paddletensor_float.data.reset(tensor_float)
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self.assertEqual(paddletensor_float.as_ndarray().all(),
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tensor_float.all())
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if __name__ == '__main__':
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unittest.main()
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