Comments (18)
看你的这个报错,应该是模型文件与 paddlelite 版本不兼容导致的,您使用的 paddlelite 版本过低,建议使用最新代码分支或者 release/v2.13 试一下, 应该可以解决你的问题。
from paddle-lite.
更新至2.13版本后报错如下:
Loading topology data from model.pdmodel
Loading params data from model.pdiparams
- Model is successfully loaded!
进程已结束,退出代码为 -1073741819 (0xC0000005)
from paddle-lite.
因为进程直接结束了,也无法进行调试,并且没有错误信息,低版本的paddlelite会显示如题目的报错,高版本的直接就没有。开发网络的paddlepaddle版本为2.6.0,不知paddlelite是不支持哪部分。
from paddle-lite.
恩,是的,paddle 版本太高了,应该是哪里 paddlelite 没有适配。有两种办法:1.尝试使用低版本的 paddle 重新导出一下模型 2.可以在 paddlelite 里面增加一下打印,然后进行调试,但是这种对开发者要求较高。 3.其实如果模型比较小,也可以通过裁剪模型,看下哪个算子有差异。
from paddle-lite.
class Block(nn.Layer):
def __init__(self, in_channels=3, out_channels=3, kernel_size=3, *args):
super(Block, self).__init__()
self.nn = nn.Sequential(
nn.Conv1D(
in_channels=in_channels, # 输入通道
out_channels=out_channels, # 输出通道
kernel_size=kernel_size, # 卷积核大小
padding=0, # 填充大小
bias_attr=False # 是否包含偏置参数
),
nn.BatchNorm1D(num_features=out_channels),
nn.LeakyReLU(.2),
nn.Dropout(p=.2)
)
def forward(self, x):
return self.nn(x)
class FallNet(nn.Layer):
def __init__(self, in_channels=3, out_classes=5, hid=64, num=64):
super(FallNet, self).__init__()
self.cnn0 = Block(in_channels,hid,7,0)
self.cnn1 = Block(hid,hid,5,0)
self.cnn2 = Block(hid,hid,3,0)
self.cnn3 = Block(hid,hid,1,0)
self.avg = nn.AdaptiveAvgPool1D(output_size=num)
self.rnn0 = nn.GRU(input_size=145, hidden_size=num, num_layers=1, dropout=0.2)
self.rnn1 = Block(hid,hid,1,0)
self.rnn2 = Block(hid,4,3,0)
self.cls = nn.Sequential(
nn.Linear(in_features=1016, out_features=128),
nn.Dropout(p=.2),
nn.Linear(in_features=128, out_features=out_classes),
nn.Softmax(axis=1)
)
def forward(self, x):
x = self.cnn0(x)
y = self.cnn1(x)
y1 = self.avg(y)
y = self.cnn2(y)
y2 = self.avg(y)
y = self.cnn3(y)
y3 = self.avg(y)
r,t = self.rnn0(x)
x = paddle.concat([y1,y2,y3,r], axis=-1)
x = self.rnn1(x)
x = self.rnn2(x)
x = paddle.flatten(x, start_axis=1)
x = self.cls(x)
return x
这是整个网络的代码,是从Aistudio社区中的一个项目,现在还在学习阶段水平有限,不知道网络设计方面是否存在缺陷导致出现以上bug,如果可以的话希望您指导一下
from paddle-lite.
需要实现根据手机加速度传感器xyz轴数据对5种人体动作进行分类,训练集每条数据包含了xyz三轴各轴151条瞬时加速度数据,以上网络是根据社区项目和github开源的内容开发的,训练和eval都没有问题,模型转换时失败了
from paddle-lite.
您不用修改组网代码,先把 paddle 版本换成2.5/2.4 ,然后重新导出试一下。
from paddle-lite.
2.4与2.5版本依旧报错
Loading topology data from test.pdmodel
Loading params data from test.pdiparams
1. Model is successfully loaded!
进程已结束,退出代码为 -1073740791 (0xC0000409)
from paddle-lite.
方便的话可以上传一下您的 paddle 模型,我这边试下
from paddle-lite.
model.zip
这是导出的模型
from paddle-lite.
您好,定位到是您的模型中的第四个卷积触发了我们这边的一个 bug,sparse_conv_pass 在处理时出现了 segment fault 的错误,暂时帮您屏蔽了,所以附件中帮您使用 develop 版本重新编译了一个 opt 工具,您可以使用这个版本的 opt 工具重新产出一下 nb 模型,我亲测是可以的。注意:附件中是已经转换好的 nb 模型,和新编译的 opt 工具,但是这两个是基于 develop 版本编译的,您可以先试一下,如果需要 release 版本的我可以在帮你编译一下,但是应该是兼容的。
from paddle-lite.
from paddle-lite.
将转换好的.nb部署到Android后出现如下报错,无法打开.nb文件,不知是否是libpaddle_lite_jni.so文件有问题?
Abort message: '[F 5/ 9 20: 3: 6.399 ...d/Paddle-Lite/lite/core/model/base/io.cc:46 BinaryFileReader]
Check failed: file_: Unable to open file: /data/user/0/com.lhz.prolbs/cache/paddle/model.nb
'
2024-05-09 20:03:06.993 23690-23690 DEBUG crash_dump32 A #01 pc 0007a0ad
/data/app/~~9NEiVuHbUtKwMUZDSz0D6g==/com.lhz.prolbs-xx7Xg5gjQHcRF9fXYQ6F3g==/lib/arm/libpaddle_lite_jni.so (BuildId: 99342f670b057b9b0372e8d820eb3f64265d6b05)
from paddle-lite.
重新用 release/v2.13编译了一下,你再试试
issue_v2.tar.gz
from paddle-lite.
依旧出现了如下报错
A [F 5/ 9 22:17:53.353 ...odel_parser/naive_buffer/naive_buffer.cc:62 LoadFromFile] Check failed: fp: Unable to open file: /data/user/0/com.lhz.prolbs/cache/model.nb
2024-05-09 22:17:53.353 16263-16263 libc com.lhz.prolbs A FORTIFY: fseeko: null FILE*
2024-05-09 22:17:53.354 16263-16263 libc com.lhz.prolbs A Fatal signal 6 (SIGABRT), code -1 (SI_QUEUE) in tid 16263 (com.lhz.prolbs), pid 16263 (com.lhz.prolbs)
2024-05-09 22:17:53.609 16612-16612 DEBUG crash_dump32 A Cmdline: com.lhz.prolbs
2024-05-09 22:17:53.609 16612-16612 DEBUG crash_dump32 A pid: 16263, tid: 16263, name: com.lhz.prolbs >>> com.lhz.prolbs <<<
2024-05-09 22:17:53.609 16612-16612 DEBUG crash_dump32 A Abort message: '[F 5/ 9 22:17:53.353 ...odel_parser/naive_buffer/naive_buffer.cc:62 LoadFromFile] Check failed: fp: Unable to open file: /data/user/0/com.lhz.prolbs/cache/model.nb
'
2024-05-09 22:17:53.609 16612-16612 DEBUG crash_dump32 A #03 pc 001819ab /data/app/~~3hYhbkk4dT1HTuMR3tn-gw==/com.lhz.prolbs-CVj6vnBdtOKNeSoXBYnIAA==/lib/arm/libpaddle_lite_jni.so
2024-05-09 22:17:53.696 2778-2914 DollieAdapterService com.huawei.systemserver E notifyActivityState pkg:com.lhz.prolbs/com.lhz.prolbs.MainActivity state:19 fg:false mUid:10530
from paddle-lite.
我更换了不同版本的libpaddle_lite_jni.so尝试了,报错是相同的Unable to open file
from paddle-lite.
Android代码本身有些问题,调整问题后报错如下,这是Android端paddlelite版本的问题吧
warning: the version of opt that transformed this model is not consistent with current Paddle-Lite version.
version of opt:cd09a8e01
version of current Paddle-Lite:v2.10
2024-05-09 22:53:59.387 2701-2701 libc com.lhz.prolbs A Fatal signal 11 (SIGSEGV), code 1 (SEGV_MAPERR), fault addr 0x4 in tid 2701 (com.lhz.prolbs), pid 2701 (com.lhz.prolbs)
2024-05-09 22:54:00.194 3234-3234 DEBUG pid-3234 A Cmdline: com.lhz.prolbs
2024-05-09 22:54:00.194 3234-3234 DEBUG pid-3234 A pid: 2701, tid: 2701, name: com.lhz.prolbs >>> com.lhz.prolbs <<<
2024-05-09 22:54:00.194 3234-3234 DEBUG pid-3234 A #00 pc 00216834 /data/app/~~qWZP-5S3Gvt30qtt7dqgmg==/com.lhz.prolbs-S9o8myZgnUXOSqj6De4vdg==/lib/arm/libpaddle_lite_jni.so (BuildId: 99342f670b057b9b0372e8d820eb3f64265d6b05)
2024-05-09 22:54:00.265 2778-2914 DollieAdapterService com.huawei.systemserver E notifyActivityState pkg:com.lhz.prolbs/com.lhz.prolbs.MainActivity state:19 fg:false mUid:10530
from paddle-lite.
更换了release/v2.13的libpaddle_lite_jni.so程序可以跑通了,非常感谢您给予的帮助!
from paddle-lite.
Related Issues (20)
- 调用nb格式模型时候报错:Segmentation fault (core dumped) HOT 1
- 新人求助,能提供bert,pythonAPI推理部署示例嘛,我该如何做前处理和后处理。 HOT 2
- paddle推理模型转为nb失败 HOT 4
- Android studio高版本gradle编译失败 HOT 2
- RepSVTR可以使用paddlelite工具进行端化吗 HOT 1
- How to get qualcomm_qnn HOT 3
- Android内存分页变更适配 HOT 1
- PaddleLite metal backend concat 算子推理错误 HOT 1
- build_xcode.h 编译脚本无法支持metal构建, LITE_WITH_PRECISION_PROFILE 构建参数配置错误 HOT 1
- 模型推理时,CheckInputValid 函数报错 HOT 1
- Paddle-lite installtion process for Vim3 khadas for NPU inference HOT 8
- paddlelite转换基于SLaNet训练的表格模型报错 HOT 4
- develop 分支 opt 转换模型,当模型内含有 cast 算子,且 backend 为 metal 时,模型转换出错 HOT 2
- yolov8n.pt转换nb模型报错 HOT 4
- [Paddle-Lite/lite/operators/compare_op.cc:38 GetBroadcastDimsArrays] Check failed: (axis < max_dim): 1!<1 HOT 3
- paddle ocr rec v3 模型推理崩溃(iOS) HOT 7
- 关于PaddleOCR表格识别模型在安卓应用 HOT 5
- ocr-det rec 模型如何在hisi3599推理提速 HOT 2
- PP-ShiTuv2模型在RK3588上部署运行导致linux系统重启 HOT 8
- PaddleOCR V4 有nb模型可下载吗? HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from paddle-lite.