wehub-resource-sync
87 lines
2.8 KiB
Python
87 lines
2.8 KiB
Python
# Copyright (c) 2022 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
|
|
import op_test
|
|
from op_test import get_device_place, is_custom_device
|
|
|
|
import paddle
|
|
from paddle.base import core
|
|
from paddle.distributed.models.moe import utils
|
|
|
|
|
|
def count(x, upper_num):
|
|
res = np.zeros((upper_num,)).astype(int)
|
|
for i in x.reshape(-1):
|
|
if i >= 0 and i < len(res):
|
|
res[i] += 1
|
|
return res
|
|
|
|
|
|
def number_count_wrapper(numbers, upper_num):
|
|
return paddle._legacy_C_ops.number_count(numbers, 'upper_range', upper_num)
|
|
|
|
|
|
@unittest.skipIf(
|
|
not (core.is_compiled_with_cuda() or is_custom_device()),
|
|
"core is not compiled with CUDA",
|
|
)
|
|
class TestNumberCountOpInt64(op_test.OpTest):
|
|
def setUp(self):
|
|
upper_num = 16
|
|
self.op_type = "number_count"
|
|
self.python_api = number_count_wrapper
|
|
x = np.random.randint(-1, upper_num, size=(1000, 2)).astype('int64')
|
|
self.inputs = {'numbers': x}
|
|
self.outputs = {'Out': count(x, upper_num)}
|
|
self.attrs = {"upper_range": upper_num}
|
|
|
|
def test_forward(self):
|
|
self.check_output_with_place(get_device_place())
|
|
|
|
|
|
@unittest.skipIf(
|
|
not (core.is_compiled_with_cuda() or is_custom_device()),
|
|
"core is not compiled with CUDA",
|
|
)
|
|
class TestNumberCountAPI(unittest.TestCase):
|
|
def setUp(self):
|
|
self.upper_num = 320
|
|
self.x = np.random.randint(-1, self.upper_num, size=(6000, 200)).astype(
|
|
'int64'
|
|
)
|
|
self.out = count(self.x, self.upper_num)
|
|
self.place = get_device_place()
|
|
|
|
def test_api_static(self):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(paddle.static.Program()):
|
|
x = paddle.static.data('x', self.x.shape, dtype="int64")
|
|
out = utils._number_count(x, self.upper_num)
|
|
exe = paddle.static.Executor(self.place)
|
|
(res,) = exe.run(feed={'x': self.x}, fetch_list=[out])
|
|
np.testing.assert_allclose(res, self.out)
|
|
|
|
def test_api_dygraph(self):
|
|
paddle.disable_static()
|
|
x = paddle.to_tensor(self.x)
|
|
out = utils._number_count(x, self.upper_num)
|
|
np.testing.assert_allclose(out.numpy(), self.out)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
paddle.enable_static()
|
|
unittest.main()
|