wehub-resource-sync
104 lines
3.4 KiB
Python
104 lines
3.4 KiB
Python
# Copyright (c) 2025 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 numpy as np
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from op_test import get_device_place, is_custom_device
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import paddle
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from paddle import base
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from paddle.base import core
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class TestMsortOnCPU(unittest.TestCase):
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def setUp(self):
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self.place = core.CPUPlace()
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def test_api_0(self):
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with base.program_guard(base.Program()):
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x = paddle.static.data(
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name="input", shape=[2, 3, 4], dtype="float32"
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)
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output = paddle.msort(input=x)
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exe = base.Executor(self.place)
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data = np.array(
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[
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[[5, 8, 9, 5], [0, 0, 1, 7], [6, 9, 2, 4]],
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[[5, 2, 4, 2], [4, 7, 7, 9], [1, 7, 0, 6]],
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],
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dtype='float32',
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)
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(result,) = exe.run(feed={'input': data}, fetch_list=[output])
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np_result = np.sort(result, axis=0)
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self.assertEqual((result == np_result).all(), True)
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def test_api_1(self):
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with base.program_guard(base.Program()):
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x = paddle.static.data(
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name="input", shape=[2, 3, 4], dtype="float32"
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)
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output = paddle.empty_like(x)
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paddle.msort(input=x, out=output)
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exe = base.Executor(self.place)
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data = np.array(
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[
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[[5, 8, 9, 5], [0, 0, 1, 7], [6, 9, 2, 4]],
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[[5, 2, 4, 2], [4, 7, 7, 9], [1, 7, 0, 6]],
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],
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dtype='float32',
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)
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(result,) = exe.run(feed={'input': data}, fetch_list=[output])
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np_result = np.sort(result, axis=0)
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self.assertEqual((result == np_result).all(), True)
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class TestMsortOnGPU(TestMsortOnCPU):
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def init_place(self):
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if core.is_compiled_with_cuda() or is_custom_device():
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self.place = get_device_place()
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else:
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self.place = core.CPUPlace()
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class TestMsortDygraph(unittest.TestCase):
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def setUp(self):
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self.input_data = np.random.rand(10, 10)
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if core.is_compiled_with_cuda() or is_custom_device():
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self.place = get_device_place()
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else:
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self.place = core.CPUPlace()
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def test_api_0(self):
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paddle.disable_static(self.place)
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var_x = paddle.to_tensor(self.input_data)
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out = paddle.msort(input=var_x)
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self.assertEqual(
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(np.sort(self.input_data, axis=0) == out.numpy()).all(), True
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)
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paddle.enable_static()
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def test_api_1(self):
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paddle.disable_static(self.place)
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var_x = paddle.to_tensor(self.input_data)
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out = paddle.empty_like(var_x)
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paddle.msort(input=var_x, out=out)
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self.assertEqual(
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(np.sort(self.input_data, axis=0) == out.numpy()).all(), True
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)
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paddle.enable_static()
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if __name__ == '__main__':
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unittest.main()
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