mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-12-24 13:28:13 +08:00
43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
# Copyright (c) 2025 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 paddle
|
|
from paddleformers.transformers.activations import ACT2FN
|
|
|
|
from fastdeploy.model_executor.ops.gpu import gelu_tanh
|
|
|
|
|
|
class TestGeluTanh(unittest.TestCase):
|
|
def setUp(self):
|
|
paddle.set_device("gpu")
|
|
np.random.seed(42)
|
|
|
|
def test_gelu_tanh(self):
|
|
x = paddle.randn(2048, 4096)
|
|
y0 = ACT2FN["gelu_new"](x)
|
|
y1 = gelu_tanh(x)
|
|
np.testing.assert_allclose(
|
|
y0.cast("float32").numpy(),
|
|
y1.cast("float32").numpy(),
|
|
rtol=1e-04,
|
|
atol=1e-04,
|
|
)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|