718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
74 lines
2.0 KiB
Python
74 lines
2.0 KiB
Python
# Tencent is pleased to support the open source community by making ncnn available.
|
|
#
|
|
# Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
|
|
#
|
|
# Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
|
|
# in compliance with the License. You may obtain a copy of the License at
|
|
#
|
|
# https://opensource.org/licenses/BSD-3-Clause
|
|
#
|
|
# 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 torch
|
|
import torch.nn as nn
|
|
import torch.nn.functional as F
|
|
|
|
def hardswish_forward_0(x):
|
|
return x * F.hardsigmoid(x)
|
|
|
|
def hardswish_forward_1(x):
|
|
return x * F.hardtanh(x + 3, 0., 6.) / 6.
|
|
|
|
def hardswish_forward_2(x):
|
|
out = F.relu6(x + 3., True) / 6.
|
|
return out * x
|
|
|
|
class Model(nn.Module):
|
|
def __init__(self):
|
|
super(Model, self).__init__()
|
|
|
|
def forward(self, x, y, z, w):
|
|
x = F.hardswish(x)
|
|
y = hardswish_forward_0(y)
|
|
z = hardswish_forward_1(z)
|
|
w = hardswish_forward_2(w)
|
|
return x, y, z, w
|
|
|
|
def test():
|
|
net = Model()
|
|
net.eval()
|
|
|
|
torch.manual_seed(0)
|
|
x = torch.rand(1, 16)
|
|
y = torch.rand(12, 2, 16)
|
|
z = torch.rand(1, 3, 12, 16)
|
|
w = torch.rand(1, 5, 7, 9, 11)
|
|
|
|
a = net(x, y, z, w)
|
|
|
|
# export torchscript
|
|
mod = torch.jit.trace(net, (x, y, z, w))
|
|
mod.save("test_F_hardswish.pt")
|
|
|
|
# torchscript to pnnx
|
|
import os
|
|
os.system("../src/pnnx test_F_hardswish.pt inputshape=[1,16],[12,2,16],[1,3,12,16],[1,5,7,9,11]")
|
|
|
|
# pnnx inference
|
|
import test_F_hardswish_pnnx
|
|
b = test_F_hardswish_pnnx.test_inference()
|
|
|
|
for a0, b0 in zip(a, b):
|
|
if not torch.allclose(a0, b0, 1e-4, 1e-4):
|
|
return False
|
|
return True
|
|
|
|
if __name__ == "__main__":
|
|
if test():
|
|
exit(0)
|
|
else:
|
|
exit(1)
|