当前位置:网站首页>onnxruntime-gpu 1.7 出现的警告“Force fallback to CPU execution for node: Gather_191”等
onnxruntime-gpu 1.7 出现的警告“Force fallback to CPU execution for node: Gather_191”等
2022-04-23 06:12:00 【wujpbb7】
使用 onnxruntime-gpu(简称ORT)1.7 推断 onnx模型时出现如下警告,
2021-12-01 15:50:30.792327215 [W:onnxruntime:Default, fallback_cpu_capability.cc:135 GetCpuPreferredNodes] Force fallback to CPU execution for node: Gather_191
2021-12-01 15:50:30.792374122 [W:onnxruntime:Default, fallback_cpu_capability.cc:135 GetCpuPreferredNodes] Force fallback to CPU execution for node: Unsqueeze_363
2021-12-01 15:50:30.792386144 [W:onnxruntime:Default, fallback_cpu_capability.cc:135 GetCpuPreferredNodes] Force fallback to CPU execution for node: Gather_188
2021-12-01 15:50:30.792413728 [W:onnxruntime:Default, fallback_cpu_capability.cc:135 GetCpuPreferredNodes] Force fallback to CPU execution for node: Unsqueeze_362
2021-12-01 15:50:30.792442104 [W:onnxruntime:Default, fallback_cpu_capability.cc:135 GetCpuPreferredNodes] Force fallback to CPU execution for node: Gather_182
2021-12-01 15:50:30.792453046 [W:onnxruntime:Default, fallback_cpu_capability.cc:135 GetCpuPreferredNodes] Force fallback to CPU execution for node: Unsqueeze_361
ORT 选择 cpu 去做,是由于这个操作 相对于 cuda 在 CPU 上做效率更高。
升级 ORT 到 1.8,出现了莫名其妙的错误:
[E:onnxruntime:, sequential_executor.cc:339 Execute] Non-zero status code returned while running Conv node. Name:'Conv_2' Status Message: /onnxruntime_src/onnxruntime/core/framework/bfc_arena.cc:330 void* onnxruntime::BFCArena::AllocateRawInternal(size_t, bool) Failed to allocate memory for requested buffer of size 409856
升级到 1.9,就没问题了。
版权声明
本文为[wujpbb7]所创,转载请带上原文链接,感谢
https://blog.csdn.net/blueblood7/article/details/121659794
边栏推荐
- PaddleOCR 图片文字提取
- [recommendation for new books in 2021] professional azure SQL managed database administration
- 【指标】Precision、Recall
- [8] Assertion failed: dims.nbDims == 4 || dims.nbDims == 5
- [2021 book recommendation] kubernetes in production best practices
- WebView displays a blank due to a certificate problem
- Some common data type conversion methods in pytorch are similar to list and NP Conversion method of ndarray
- Chapter 8 generative deep learning
- PyMySQL连接数据库
- PyTorch 11.正则化
猜你喜欢
PaddleOCR 图片文字提取
Machine learning notes 1: learning ideas
使用 trt 的int8 量化和推断 onnx 模型
[2021 book recommendation] practical node red programming
Raspberry Pie: two color LED lamp experiment
第8章 生成式深度学习
【点云系列】FoldingNet:Point Cloud Auto encoder via Deep Grid Deformation
【点云系列】Neural Opacity Point Cloud(NOPC)
【点云系列】Learning Representations and Generative Models for 3D pointclouds
Android interview Online Economic encyclopedia [constantly updating...]
随机推荐
【点云系列】DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds
torch.mm() torch.sparse.mm() torch.bmm() torch.mul() torch.matmul()的区别
Solution to slow compilation speed of Xcode
【动态规划】三角形最小路径和
Reading notes - activity
PyTorch中的一些常见数据类型转换方法,与list和np.ndarray的转换方法
PyTorch 13. 嵌套函数和闭包(狗头)
Machine learning III: classification prediction based on logistic regression
PyTorch 9. 优化器
SSL/TLS应用示例
[dynamic programming] different binary search trees
Chapter 2 pytoch foundation 2
Mysql database installation and configuration details
[recommendation of new books in 2021] enterprise application development with C 9 and NET 5
[2021 book recommendation] learn winui 3.0
机器学习——PCA与LDA
torch. mm() torch. sparse. mm() torch. bmm() torch. Mul () torch The difference between matmul()
[point cloud series] sg-gan: advantageous self attention GCN for point cloud topological parts generation
机器学习笔记 一:学习思路
c语言编写一个猜数字游戏编写