wehub-resource-sync
130 lines
4.4 KiB
Python
130 lines
4.4 KiB
Python
# 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
|
|
|
|
import numpy as np
|
|
from op_test import get_device_place, is_custom_device
|
|
|
|
import paddle
|
|
from paddle import base
|
|
from paddle.base import core
|
|
|
|
|
|
class TestSortOnCPU(unittest.TestCase):
|
|
def setUp(self):
|
|
self.place = core.CPUPlace()
|
|
|
|
def test_api_0(self):
|
|
with base.program_guard(base.Program()):
|
|
input = paddle.static.data(
|
|
name="input", shape=[2, 3, 4], dtype="float32"
|
|
)
|
|
output = paddle.sort(x=input)
|
|
exe = base.Executor(self.place)
|
|
data = np.array(
|
|
[
|
|
[[5, 8, 9, 5], [0, 0, 1, 7], [6, 9, 2, 4]],
|
|
[[5, 2, 4, 2], [4, 7, 7, 9], [1, 7, 0, 6]],
|
|
],
|
|
dtype='float32',
|
|
)
|
|
(result,) = exe.run(feed={'input': data}, fetch_list=[output])
|
|
np_result = np.sort(result)
|
|
self.assertEqual((result == np_result).all(), True)
|
|
|
|
def test_api_1(self):
|
|
with base.program_guard(base.Program()):
|
|
input = paddle.static.data(
|
|
name="input", shape=[2, 3, 4], dtype="float32"
|
|
)
|
|
output = paddle.sort(x=input, axis=1)
|
|
exe = base.Executor(self.place)
|
|
data = np.array(
|
|
[
|
|
[[5, 8, 9, 5], [0, 0, 1, 7], [6, 9, 2, 4]],
|
|
[[5, 2, 4, 2], [4, 7, 7, 9], [1, 7, 0, 6]],
|
|
],
|
|
dtype='float32',
|
|
)
|
|
(result,) = exe.run(feed={'input': data}, fetch_list=[output])
|
|
np_result = np.sort(result, axis=1)
|
|
self.assertEqual((result == np_result).all(), True)
|
|
|
|
def test_api_2(self):
|
|
with base.program_guard(base.Program()):
|
|
input = paddle.static.data(
|
|
name="input", shape=[30], dtype="float32"
|
|
)
|
|
output = paddle.sort(x=input, axis=0, stable=True)
|
|
exe = base.Executor(self.place)
|
|
data = np.array(
|
|
[100.0, 50.0, 10.0] * 10,
|
|
dtype='float32',
|
|
)
|
|
(result,) = exe.run(feed={'input': data}, fetch_list=[output])
|
|
np_result = np.sort(result, axis=0, kind='stable')
|
|
self.assertEqual((result == np_result).all(), True)
|
|
|
|
|
|
class TestSortOnGPU(TestSortOnCPU):
|
|
def init_place(self):
|
|
if core.is_compiled_with_cuda() or is_custom_device():
|
|
self.place = get_device_place()
|
|
else:
|
|
self.place = core.CPUPlace()
|
|
|
|
|
|
class TestSortDygraph(unittest.TestCase):
|
|
def setUp(self):
|
|
self.input_data = np.random.rand(10, 10)
|
|
if core.is_compiled_with_cuda() or is_custom_device():
|
|
self.place = get_device_place()
|
|
else:
|
|
self.place = core.CPUPlace()
|
|
|
|
def test_api_0(self):
|
|
with paddle.base.dygraph.guard(self.place):
|
|
var_x = paddle.to_tensor(self.input_data)
|
|
out = paddle.sort(var_x)
|
|
self.assertEqual(
|
|
(np.sort(self.input_data) == out.numpy()).all(), True
|
|
)
|
|
|
|
def test_api_1(self):
|
|
with paddle.base.dygraph.guard(self.place):
|
|
var_x = paddle.to_tensor(self.input_data)
|
|
out = paddle.sort(var_x, axis=-1)
|
|
self.assertEqual(
|
|
(np.sort(self.input_data, axis=-1) == out.numpy()).all(), True
|
|
)
|
|
|
|
def test_api_2(self):
|
|
paddle.disable_static(self.place)
|
|
var_x = paddle.to_tensor(np.array([100.0, 50.0, 10.0] * 10))
|
|
out = paddle.sort(var_x, axis=0)
|
|
self.assertEqual(
|
|
(
|
|
np.sort(
|
|
np.array([100.0, 50.0, 10.0] * 10), axis=0, kind='stable'
|
|
)
|
|
== out.numpy()
|
|
).all(),
|
|
True,
|
|
)
|
|
paddle.enable_static()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|