Comments (5)
可以尝试使用 2.13-rc 版本
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IOS端的代码本身就有很多问题(feed和fetch的代码都没写完的地方),我自己也没环境,懒得看了,不建议使用。
from paddle-lite.
IOS负责的程序员应该很早就离职了,想解决只能靠自己了
from paddle-lite.
IOS端的代码本身就有很多问题(feed和fetch的代码都没写完的地方),我自己也没环境,懒得看了,不建议使用。
你说的是 metal ?用户报的错误是 cpu ,完全不搭噶,我不清楚你想表达什么。
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用 paddle ocr rec v3 模型(opt 2.10 转成 nb 模型),用 paddle lite 2.10 库推理出现如下错误(偶现):
Caused by:Attempted to dereference garbage 0x....
void paddle::lite::arm::math::gemv_int8(signed char const*, signed char const*,float*,bool,int ,int,float const*,bool,float const*,paddle::lite::operators::ActivationParam,paddle::lite::Context<(paddle::lite_api::TargetType)4>*)
@teletian 可以访问 https://github.com/PaddlePaddle/Paddle-Lite/releases 下载最新的 2.13rc 的库,如果仍然有问题,可以基于 develop 代码参考 https://www.paddlepaddle.org.cn/lite/v2.12/source_compile/macos_compile_ios.html 文档编译 cpu only 的库。
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Related Issues (20)
- arm的推理结果正确,opencl的结果不正确,请问如何做逐层的精度对比分析? HOT 3
- Object Detection运行run脚本的时候报错 HOT 6
- 华为Atlas300I(3010,昇腾310)安装Paddle-Lite运行例程出错 HOT 4
- Paddle-Lite通过X2Paddle转化出的nb模型出错 HOT 2
- [BUG] sort_cpuid_by_max_freq()中的bubble sort代码逻辑错误 HOT 4
- 基于Paddle Lite框架下的编译问题 HOT 3
- Android端推理LightGlue模型crash了 HOT 1
- ubuntu 22.04 x64 编译paddle-lite x86出错 lite/CMakeFiles/publish_inference.dir/rule HOT 2
- .pdmodel转换.nb失败,报错Check failed: it != outputs_.end(): HOT 18
- 3399 编译with_opencl后运行示例mobilenetv1_light_api显示不支持opencl HOT 1
- 使用华为NPU推理pp-yoloe-r模型报错,提示cann版本不匹配 HOT 15
- could not create a descriptor for a pooling forward propagation primitive HOT 1
- "树莓派5 编译错误"- v2.13 编译报错、环境信息: (Linux raspberrypi 6.6.28+rpt-rpi-2712 #1 SMP PREEMPT Debian 1:6.6.28-1+rpt1 (2024-04-22) aarch64 GNU/Linux) HOT 21
- 预编译库的V2,12下载的压缩包里没有找到python,我要怎么继续下一步得到python--->install--->dist--->paddlelite-*.whl HOT 1
- "树莓派5 编译错误"- v2.13 编译报错 cd09a8e01、环境信息:(Debian arm64 ----armv8 ) ,经检查“cd09a8e01”是git describe --always 值 HOT 3
- 编译无法生成inference_lite_lib.armlinux.armv8.opencl包 HOT 5
- Linux x86平台推理Paddle-OCRv4出错 HOT 1
- Excel file returning empty with no error [URGENT] HOT 1
- 调用nb格式模型时候报错:Segmentation fault (core dumped)
- 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。
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