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92 lines
2.7 KiB
92 lines
2.7 KiB
# Copyright (c) 2020 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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from __future__ import print_function
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import paddle
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import paddle.fluid as fluid
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import unittest
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import numpy as np
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from op_test import OpTest
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class TestArangeOp(OpTest):
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def setUp(self):
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self.op_type = "range"
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self.init_config()
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self.inputs = {
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'Start': np.array([self.case[0]]).astype(self.dtype),
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'End': np.array([self.case[1]]).astype(self.dtype),
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'Step': np.array([self.case[2]]).astype(self.dtype)
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}
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self.outputs = {
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'Out': np.arange(self.case[0], self.case[1],
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self.case[2]).astype(self.dtype)
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}
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def init_config(self):
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self.dtype = np.float32
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self.case = (0, 1, 0.2)
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def test_check_output(self):
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self.check_output()
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class TestFloatArangeOpCase0(TestArangeOp):
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def init_config(self):
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self.dtype = np.float32
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self.case = (0, 5, 1)
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class TestInt32ArangeOpCase0(TestArangeOp):
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def init_config(self):
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self.dtype = np.int32
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self.case = (0, 5, 2)
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class TestInt32ArangeOpCase1(TestArangeOp):
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def init_config(self):
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self.dtype = np.int32
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self.case = (10, 1, -2)
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class TestInt32ArangeOpCase2(TestArangeOp):
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def init_config(self):
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self.dtype = np.int32
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self.case = (-1, -10, -2)
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class TestArangeAPI(unittest.TestCase):
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def test_out(self):
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with fluid.program_guard(fluid.Program()):
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data = paddle.arange(0, 5, 1)
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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result, = exe.run(fetch_list=[data])
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expected_data = np.arange(0, 5, 1).astype(np.float32)
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self.assertEqual((result == expected_data).all(), True)
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with fluid.program_guard(fluid.Program()):
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data = paddle.arange(0.0, 5.0, 1.0, 'int32')
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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result, = exe.run(fetch_list=[data])
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expected_data = np.arange(0, 5, 1).astype(np.int32)
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self.assertEqual((result == expected_data).all(), True)
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if __name__ == "__main__":
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unittest.main()
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