GradCache
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luyug
Run Effective Large Batch Contrastive Learning Beyond GPU/TPU Memory Constraint
Dear writer, Your work is very good to me, I want to mix the SimCLR,but I don't know how to do because I find the gradcache without batchsize, but the...
Hi @luyug, any idea on how to fix this? 04/14/2022 15:48:04 - INFO - tevatron.trainer - Initializing Gradient Cache Trainer Traceback (most recent call last): File "/home/odunayo/anaconda3/envs/tevatron_env/lib/python3.9/runpy.py", line 197, in...
Do you have example of this with pytorch lightning by any chance? Thanks for the beautiful work.
Looking through the code, I notice that there are mini-batches consisting of just negative examples that appear to be ignored entirely. If the code ignores certain combinations, how does using...
Thank you for the great work! Could you please provide some examples about functional approach with distributed multi-gpu training?
BatchNorm is very common in CV models, when training = True, the running statistics in BatchNorm layers is changing in every chunk.
Hello, When reading the implementation, I noticed that in the forward-backward pass, you used a dot-product before running the backward pass, specifically in the following line: https://github.com/luyug/GradCache/blob/0c33638cb27c2519ad09c476824d550589a8ec38/src/grad_cache/grad_cache.py#L241 I can't understand...
Hi, it's a great work! We have three inputs designated as `i1`, `i2`, and `i3`, which are to be processed by the llama-7b. For input `i1`, I will extract two...
Hello, Suppose my model returns multiple outputs. How should the functional approach be modified to handle this? Thanks.
