yangli18
yangli18
@zzh-tech Sorry for the late reply. I'm currently busy with other things, so I may not have time to work on this right now. However, I expect that this API's...
We used RTX 3090 and V100 GPUs with CUDA 11.
@Mr-Bigworth > > We used RTX 3090 and V100 GPUs with CUDA 11. > > 请问四卡v100训练大概多长时间哇 这个看你的数据集多大，这个工作的训练都还比较快，训练时间应该不用怎么担心。 > 如果有两卡A100能复现训练过程不 两卡A100应该显存是够用，可以训练的。
@Mr-Bigworth 可以试试梯度累积，一个大batch分成两份进行梯度求导。
@LeungWaiHo A1: Yes, it can be understood as a similarity function, which measures how relevant each visual feature is to the content described in the text. A2: The output of...
It's just a matter of implementation. The inside part of Eq. 1 essentially computes the inner product of two feature vectors. Actually, you can use *bmm* after transposing the matrix/vector...
@wildwolff Hi, it's just a matter of implementation. The inside part of Eq. 1 essentially computes the inner product of two feature vectors. Actually, you can use *bmm* after transposing...
The first dimension 400 a flattened 20x20 (the resolution of the downsampled feature map). You can reshape the tensor to recover the spatial dimensions for visualization. You can visualize the...