python -m torch.distributed.launch --nproc_per_node=8 --use_env train.py\ --model mobilenet_v3_small --epochs 600 --opt rmsprop --batch-size 128 --lr 0.064\ --wd 0.00001 --lr-step-size 2 --lr-gamma 0.973 --auto-augment imagenet --random-erase 0.2 Submitted batch job 35753749 T...
22、选用的深度学习框架为 pytorch1.10 版本,编程语言为 python,环境设置为python3.8 版本,集成开发环境为 pycharm2020.2.1,程序运行电脑配置为 intel® core®gold5320 cpu@2.20ghz,内存为32gb,gpu为 nvidiartx a4000,显存为 16 gb,操作系统为 64 位 windows10; 模型共训练 200 个 epoch,试验批处理大小( ba...
PyTorch Implementation of MobileNet V3 Reproduction of MobileNet V3 architecture as described inSearching for MobileNetV3by Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, Hartwig Adam on ILSVR...
This work is implemented in PyTorch. All experiments were conducted on a PC equipped with an Intel Core i7-12700K CPU and an Nvidia RTX 3090 GPU. In this study, we selected the lightweight MobileNetV3 as the backbone network for feature extraction, which was pre-trained and fine-tuned on...
Experimental Environment The configuration used for model training and testing in this paper is as follows: Intel Core i5-10210U CPU @ 1.60 GHz/2.11 GHz; 16 GB RAM; Nvidia GeForce MX250 graphics card; Windows 10 Home Chinese version; CUDA version 10.1; and PyTorch 3.8. 4.2. Evaluation ...