GPT - gMLP
This repository will attempt to crack long context autoregressive language modeling (GPT) using variations of gMLPs. Specifically, it will contain a variant that does gMLP for local sliding windows. The hope is to be able to stretch a single GPU to be able to train context lengths of 4096 and above efficiently and well.
GPT is technically a misnomer now, since there will be no attention (transformer) at all contained in the architecture.
Install
$ pip install g-mlp-gpt
Usage
import torch
from g_mlp_gpt import gMLPGPT
model = gMLPGPT(
num_tokens = 20000,
dim = 512,
depth = 4,
seq_len = 1024,
window_size = (128, 256, 512, 1024) # window sizes for each depth
)
x = torch.randint(0, 20000, (1, 1000))
logits = model(x) # (1, 1000, 20000)
16k context length
import torch
from g_mlp_gpt import gMLPGPT
model = gMLPGPT(
num_tokens = 20000,
dim = 512,
seq_len = 16384,
depth = 8,
reversible = True,
window = (128, 128, 256, 512, 1024, 1024, 2048, 2048, 4096, 4096, 8192, 8192),
axial = (1, 1, 1, 1, 1, 1, 2, 2, 4, 4, 8, 8)
).cuda()
x = torch.randint(0, 20000, (1, 16384)).cuda()
logits = model(x) # (1, 16384, 20000)
Citations
@misc{liu2021pay,
title = {Pay Attention to MLPs},
author = {Hanxiao Liu and Zihang Dai and David R. So and Quoc V. Le},
year = {2021},
eprint = {2105.08050},
archivePrefix = {arXiv},
primaryClass = {cs.LG}
}
9 Nov 16, 2022
24 Oct 26, 2022
331 Jan 3, 2023
74 Dec 5, 2022
28 Feb 20, 2022
81 Nov 26, 2022
39 Nov 30, 2022
49 Dec 22, 2022
120 Dec 12, 2022
55 Dec 30, 2022
36 Dec 30, 2022
500 Jan 06, 2023
451 Dec 27, 2022
68 Jan 03, 2023
387 Jan 08, 2023
6 Feb 24, 2022
108 Dec 31, 2022
175 Jan 01, 2023
20 Jun 29, 2022
159 Dec 16, 2022
1.9k Jan 06, 2023
5.9k Jan 04, 2023
40 Dec 22, 2022
203 Jan 05, 2023
191 Dec 03, 2022
2.6k Jan 08, 2023
232 Dec 24, 2022
19 Dec 13, 2022
3 Nov 14, 2022