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mirror of https://github.com/osmarks/nanogpt-experiments.git synced 2024-11-10 20:09:58 +00:00
Commit Graph

45 Commits

Author SHA1 Message Date
Andrej Karpathy
e108ffb973 very slight refactor, bit cleaner 2023-02-04 19:34:24 +00:00
Nan Yang
b8286f343e Pin memory only when training on GPU 2023-02-04 11:16:26 -08:00
Andrej Karpathy
77e7e04c26 padding 50257 -> 50304 vocab_size, the nerest multiple of 64. the biggest deal smallest optimization i've made in recent past, about 25% faster. this is because the last layer is a major latency bottleneck consuming about 40% of latency due to the very high channel count. 2023-02-04 16:06:18 +00:00
Andrej Karpathy
b3c17c6c6a slight tweak compressing LOC 2023-02-04 15:57:29 +00:00
Ramtin Gharleghi
9da1627c7f
Explicitly set ddp device 2023-02-04 15:07:36 +11:00
Andrej Karpathy
3fd4c0c5ef who needs a dataloader? overlap the prefetching of the next batch with GPU compute, ehiding the data loading latency entirely. this saves about 1ms lol 2023-02-04 02:52:48 +00:00
Andrej
7d44bdf6b5
Merge pull request #106 from YassineYousfi/master
use the ``enabled`` arg in GradScaler
2023-02-02 17:23:22 -08:00
Andrej Karpathy
d8b1a94519 change grad accum to default off because i think it just confuses everyone 2023-02-02 18:38:49 +00:00
Yassine Yousfi
40f4d6ff70 use the enabled arg in GradScaler 2023-01-31 21:12:49 -08:00
Andrej Karpathy
038ce89438 rename iter to it, because iter is a concrete Python builtin 2023-01-31 23:34:02 +00:00
Andrej Karpathy
924a0873eb merge, make cleaner, careful with gradient clipping when using grad scaler fp16 training 2023-01-30 23:40:35 +00:00
Andrej Karpathy
0e90ee9d48 based on my experiments these biases are indeed not needed. code runs faster, identical results. keeping the option just because it deviates from the gpt-2 setup 2023-01-30 08:07:58 +00:00
Andrej Karpathy
001c1e7be7 stay true to the README file and set grad accum to 5, so the default batch size is about 0.5M and is reproducing gpt2 2023-01-27 20:51:50 +00:00
Andrej Karpathy
79dbe0086d let me set bias=True until I validate it properly, but this should be ok to merge to master for now, is equivalent to previous functionality 2023-01-27 20:45:28 +00:00
Andrej Karpathy
e808a67149 bunch of plumbing of bias all around. measuring bias=False to be about 6% faster 2023-01-27 20:41:17 +00:00
Andrej Karpathy
3cb3fc059c grad clipping seems to slightly speed up training in the beginning but i can't see a big difference later in the training. it costs non-negligeable compute to clip. adding it for now because it is standard, and i think more necessary as the model becomes larger. practitioners may consider turning it off for minor efficiency gains 2023-01-27 16:45:09 +00:00
johnwildauer
e0e94a1094 use GradScaler in model only if dtype is float16 2023-01-24 15:53:31 -07:00
Andrej
3611338959
Merge pull request #71 from cchan/patch-1
Zero-grad more aggressively to save memory
2023-01-20 14:38:10 -08:00
Andrej Karpathy
1f77d03024 make mentions of mps in docs. ty good people in issue #28 2023-01-20 21:28:20 +00:00
Clive Chan
67166079c9
Zero-grad more aggressively to save memory 2023-01-19 22:10:44 -08:00
Andrej Karpathy
46ce9971df small tweaks to docs and variable names stylistically 2023-01-16 16:56:05 +00:00
Andrej Karpathy
684800dd87 clarify that these should be run on two separate machines 2023-01-16 06:02:46 +00:00
Andrej Karpathy
9352df23de docs for multinode ddp 2023-01-16 05:57:33 +00:00
Andrej Karpathy
c3dddbff3d get rid of gpu_id, the world is more complicated than that when world_size > 8 2023-01-16 05:44:50 +00:00
Andrej Karpathy
f5e6ac8b02 local rank -> rank 2023-01-16 05:13:13 +00:00
Andrej Karpathy
cf99914886 add gradient accumulation support to simulate larger batch sizes. ty @VHellendoorn for original PR 2023-01-15 17:49:55 +00:00
Andrej Karpathy
57735f532d correctly propagate the vocab_size from the rendered dataset into the model args 2023-01-14 02:26:44 +00:00
Andrej Karpathy
8f85b83347 inference time mini-optimization low-hanging fruit ty @jxtps for raising: when we are running inference we can apply lm_head on only the very last token 2023-01-12 06:02:50 +00:00
Andrej Karpathy
d17350a31d add support for character-level language models, a new character-level shakespeare dataset, a new config file that shows how to train a character-level baby GPT on it, and adjust the sample function to figure out if it should decode with characters or GPT2 bpe tokens. The current implementation is a bit hacky and basically assumes just these two possibilities. In the future we may want to support more general encoders or decoders. 2023-01-11 05:27:19 +00:00
Andrej Karpathy
c2a402f7f7 guess the config from globals() and log all of it with wandb 2023-01-11 01:00:22 +00:00
Andrej Karpathy
a855d316fd add device and dtype support to train.py args 2023-01-08 19:20:38 +00:00
Luca Antiga
09f1f458e8 Move conditional import 2023-01-08 15:51:50 +01:00
Luca Antiga
aba47f0a35 Make wandb import conditioned to wandb_log=True 2023-01-08 15:42:08 +01:00
Andrej Karpathy
9629093e53 minor args re-arranging and removing some spurious ones like wandb entity ty @tcapelle 2023-01-05 01:14:02 +00:00
Andrej Karpathy
d562b3e550 shuttling the poor mans configurator aside into its own file and adding it to all of train,sample,bench. because i am leaving args in globals() so i can avoid having to prepend every single variable with an args., i have to exec the configurator and the optional configs. so we're left with something very gross by standard convention but also quite simple and functional. *ducks* 2023-01-05 00:44:35 +00:00
Andrej Karpathy
9f95aca93e better hyperparams for gpt2 124M model on A100 40GB. still uncertain about max_iters especially, and a bit about weight decay, betas 2023-01-03 17:45:49 +00:00
Andrej Karpathy
ec9b1f8182 add a patch to fix mysterious unwanted prefix in state dict? maybe remove later 2023-01-02 01:25:02 +00:00
Andrej Karpathy
35f51974c4 rename to compile it's shorter 2023-01-02 01:14:46 +00:00
Andrej Karpathy
2febf4463c candidate changes to apis, have to think through more 2023-01-01 01:29:48 +00:00
Andrej Karpathy
5a725d9098 add torch.compile by default, shows almost 1.8X improvement in throughput nice 2022-12-30 00:07:13 +00:00
Andrej Karpathy
682a0ac8f1 properly resume training, also loading iter_num and best_val_loss from checkpoints 2022-12-29 18:23:15 +00:00
Andrej Karpathy
dea1507252 add support for DDP training. the scaling timings right now do not look good by default, have to dig more into 2022-12-29 05:06:07 +00:00
Andrej Karpathy
5d2b4807bf adding a lightweight configurator that may be a terrible mistake lol. also adding configs to evaluate the baseline GPT2 versions released by OpenAI on OWT. we have some ways to go to match those numbers atm 2022-12-28 23:31:23 +00:00
Andrej Karpathy
c9fe00c0e9 small readme clarification and training script defaults changes 2022-12-28 01:45:55 +00:00
Andrej Karpathy
fe8042867c first very bad commit 2022-12-28 00:58:19 +00:00