(2022). Moreover, we also overlap the computation of activations and the communication between GPUs over the network (due to all_reduce operations) as much as possible. 为了进一步提高训练效率,我们减少了在带有检查点的后向传球过程中重新计算的激活次数。更准确地说,我们保存了昂贵计算的激活,例如线性...
[ICLR] Incremental few-shot learning via vector quantization in deep embedded space. [qnn] [ICLR] Degree-Quant: Quantization-Aware Training for Graph Neural Networks. [qnn] [ICLR] BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization. [qnn] [ICLR] Simple ...
For instance, NASNet [39] based on RL strategy demands 450GPUs for 4 days resulting in 1800 GPU-hours and MnasNet [40] used 64TPUs for 4.5 days in CIFAR-10. Similarly, Hier-Evolution [38] based on EL strategy needs to spend 300 GPU days to acquire a satisfying architecture in CIFAR...
In this paper, we propose an end-to-end object detector for fire, smoke, and human detection based on Deformable DETR (DEtection TRansformer) called FSH-DETR. To effectively process multi-scale fire and smoke features, we propose a novel Mixed Encoder, which integrates SSFI (Separate Single-...