does M1 max can use all of his memory in training???

[wildbrother]

m1 max has 64 GB RAM.

Q1.
if who want to train model with m1 max, his the biggest reason of choosing m1 max is the huge VRAM not the throughput.
I also want to know how large memory can be used in training model with m1 max. (60? 55???)

Q2.
do you have any problem with tensorflow-metal???
do you have any plan to improve this post with some experience about problem&solution in M1 training with TF. (some code or compatibilities with major packages in ML/Deep Learning)
It is just my suggestion. but I think many people want this experience sharing.

Thank you!

[tlkh]

Q1:

I only have the 32GB version, so I cannot answer with absolute certainty. I observe that about ~3GB is required for the OS etc, so in theory you would have about ~60GB for training.

That said, I do not believe it makes sense to train large models, because it will be even slower than the smaller models, which is already 8x-10x slower than the usual GPUs we would use for training (V100, 3090, A100 etc.). VRAM issue can be mitigated through a variety of strategies (mixed precision, activation checkpointing, gradient accumulation, DeepSpeed, or even optimizer choice (Adafactor vs Adam).

Q2:

I have not encounter any problems so far, it is surprisingly painless.

[st8tikratio]

Q2:

TF/Python tapped 57.19 GB of memory during training and 95.7% of the GPU.