test_arange.py 3.6 KB
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#   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import unittest
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import numpy as np
from op_test import OpTest

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import paddle
from paddle.fluid import core
from paddle.static import Program, program_guard

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class TestArangeOp(OpTest):
    def setUp(self):
        self.op_type = "range"
        self.init_config()
        self.inputs = {
            'Start': np.array([self.case[0]]).astype(self.dtype),
            '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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        }

        self.outputs = {
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            'Out': np.arange(self.case[0], self.case[1], self.case[2]).astype(
                self.dtype
            )
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        }

    def init_config(self):
        self.dtype = np.float32
        self.case = (0, 1, 0.2)

    def test_check_output(self):
        self.check_output()


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class TestFloatArangeOp(TestArangeOp):
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    def init_config(self):
        self.dtype = np.float32
        self.case = (0, 5, 1)


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class TestInt32ArangeOp(TestArangeOp):
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    def init_config(self):
        self.dtype = np.int32
        self.case = (0, 5, 2)


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class TestFloat64ArangeOp(TestArangeOp):
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    def init_config(self):
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        self.dtype = np.float64
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        self.case = (10, 1, -2)


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class TestInt64ArangeOp(TestArangeOp):
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    def init_config(self):
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        self.dtype = np.int64
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        self.case = (-1, -10, -2)


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class TestZeroSizeArangeOp(TestArangeOp):
    def init_config(self):
        self.dtype = np.int32
        self.case = (0, 0, 1)


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class TestArangeOpError(unittest.TestCase):
    def test_errors(self):
        with program_guard(Program(), Program()):
            self.assertRaises(TypeError, paddle.arange, 10, dtype='int8')


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class TestArangeAPI(unittest.TestCase):
    def test_out(self):
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        with program_guard(Program(), Program()):
            x1 = paddle.arange(0, 5, 1, 'float32')

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            place = (
                paddle.CUDAPlace(0)
                if core.is_compiled_with_cuda()
                else paddle.CPUPlace()
            )
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            exe = paddle.static.Executor(place)
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            out = exe.run(fetch_list=[x1])

        expected_data = np.arange(0, 5, 1).astype(np.float32)
        self.assertEqual((out == expected_data).all(), True)


class TestArangeImperative(unittest.TestCase):
    def test_out(self):
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        place = (
            paddle.CUDAPlace(0)
            if core.is_compiled_with_cuda()
            else paddle.CPUPlace()
        )
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        paddle.disable_static(place)
        x1 = paddle.arange(0, 5, 1)
        x2 = paddle.tensor.arange(5)
        x3 = paddle.tensor.creation.arange(5)

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        start = paddle.to_tensor(np.array([0], 'float32'))
        end = paddle.to_tensor(np.array([5], 'float32'))
        step = paddle.to_tensor(np.array([1], 'float32'))
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        x4 = paddle.arange(start, end, step, 'int64')
        paddle.enable_static()
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        expected_data = np.arange(0, 5, 1).astype(np.int64)
        for i in [x1, x2, x3, x4]:
            self.assertEqual((i.numpy() == expected_data).all(), True)
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if __name__ == "__main__":
    unittest.main()