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EleutherAI / gpt-neox

An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
https://www.eleuther.ai/
Apache License 2.0
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Sparse attention map::at triton error #472

Closed pwstegman closed 2 years ago

pwstegman commented 2 years ago

Describe the bug When training with sparse attention, Triton throws IndexError: map::at.

This is the full traceback 
Traceback (most recent call last):
  File "train.py", line 27, in 
    pretrain(neox_args=neox_args)
  File "/home/gpt-neox/megatron/training.py", line 103, in pretrain
    iteration = train(
  File "/home/gpt-neox/megatron/training.py", line 552, in train
    loss_dict, skipped_iter = train_step(
  File "/home/gpt-neox/megatron/training.py", line 459, in train_step
    reduced_loss = train_step_pipe(
  File "/home/gpt-neox/megatron/training.py", line 508, in train_step_pipe
    loss = model.train_batch(data_iter=data_iterator)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/pipe/engine.py", line 305, in train_batch
    self._exec_schedule(sched)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/pipe/engine.py", line 1308, in _exec_schedule
    self._exec_instr(**cmd.kwargs)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/pipe/engine.py", line 681, in _exec_forward_pass
    outputs = super().forward(inputs)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/engine.py", line 987, in forward
    loss = self.module(*inputs, **kwargs)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/pipe/module.py", line 350, in forward
    x = self.activation_checkpoint_func(
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/activation_checkpointing/checkpointing.py", line 692, in checkpoint
    CheckpointFunction.apply(function, all_outputs, *args)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/activation_checkpointing/checkpointing.py", line 491, in forward
    outputs = run_function(*inputs_cuda)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/runtime/pipe/module.py", line 328, in exec_func
    inputs = layer(inputs)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/gpt-neox/megatron/model/transformer.py", line 679, in forward
    return super().forward(hidden_states, attention_mask), attention_mask
  File "/home/gpt-neox/megatron/model/transformer.py", line 639, in forward
    attention_output, attention_bias = self.attention(
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/gpt-neox/megatron/model/transformer.py", line 499, in forward
    context_layer = self.sparse_attention(
  File "/home/gpt-neox/megatron/model/transformer.py", line 421, in sparse_attention
    return self.sparse_attn(
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/ops/sparse_attention/sparse_self_attention.py", line 162, in forward
    attn_output_weights = sparse_dot_sdd_nt(query, key)
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/ops/sparse_attention/matmul.py", line 720, in __call__
    c = _sparse_matmul.apply(a,
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/ops/sparse_attention/matmul.py", line 537, in forward
    c = _sparse_matmul.fn[mode](a,
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/deepspeed/ops/sparse_attention/matmul.py", line 204, in _sdd_matmul
    current = kernel(
  File "/root/.virtualenvs/gptneox/lib/python3.8/site-packages/triton/kernel.py", line 116, in __call__
    kernel = self.fn.autotune(params, grid, self.stream)
IndexError: map::at
Killing subprocess 243

To Reproduce

I cloned GPT-NeoX into my home directory.

Then I started and attached to a docker container with CUDA 10.2:

docker run --gpus all -ti -d --name gptneox -v ~/:/home pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel
docker attach gptneox

The container had Python 3.6 installed, so I installed Python 3.8. I also installed libopenmpi-dev, as it's required to install all the GPT-NeoX dependencies:

apt update
apt install python3.8 python3.8-dev and python3.8-venv libopenmpi-dev

I created and activated a new Python 3.8 virtual env and then pip installed PyTorch 1.8 and the latest version of Apex (commit aa756cec4359aff3df1d9abb68dc6e6e92920e0c):

python3.8 -m venv ~/.virtualenvs/gptneox
. ~/.virtualenvs/gptneox/bin/activate
python -m pip install --upgrade pip wheel
pip install torch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0
git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

Then I installed the GPT-NeoX dependencies:

pip install -r requirements/requirements.txt
pip install -r requirements/requirements-sparseattention.txt

I downloaded a dataset:

python prepare_data.py --vocab-file /home/data/gpt2-vocab.json --merge-file /home/data/gpt2-merges.txt enron

Then I started training without sparse attention, which worked fine:

python ./deepy.py train.py -d configs small.yml local_setup.yml

However, once I added in the sparse attention config, it threw the error mentioned above. This is the command that caused the error:

python ./deepy.py train.py -d configs small.yml sparse.yml local_setup.yml

Expected behavior

Training should run when sparse attention is enabled.

Proposed solution

I'm not sure how to fix this. I did run into this same issue when trying Microsoft's DeepSpeed examples, so this may be an issue inherited from DeepSpeed, rather than something introduced by DeeperSpeed.

Screenshots

N/A

Environment (please complete the following information):

NVCC 10.2 
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89
Nvidia driver 495.44 
Sun Nov 28 20:46:07 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 495.44       Driver Version: 495.44       CUDA Version: 11.5     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2...  Off  | 00000000:00:04.0 Off |                    0 |
| N/A   36C    P0    37W / 300W |      0MiB / 16160MiB |      1%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
gcc 7.5.0 
gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
pip freeze 
aiohttp==3.8.1
aiosignal==1.2.0
apex==0.1
appdirs==1.4.4
async-timeout==4.0.1
attrs==21.2.0
best-download==0.0.7
black==20.8b1
certifi==2021.10.8
chardet==4.0.0
charset-normalizer==2.0.8
click==8.0.3
colorama==0.4.4
configparser==5.1.0
cxxfilt==0.3.0
Cython==0.29.24
DataProperty==0.54.2
datasets==1.16.1
deepspeed @ git+git://github.com/EleutherAI/DeeperSpeed.git@eb7f5cff36678625d23db8a8fe78b4a93e5d2c75
dill==0.3.4
docker-pycreds==0.4.0
dyNET38==2.1
einops==0.3.0
filelock==3.4.0
frozenlist==1.2.0
fsspec==2021.11.1
ftfy==6.0.1
gitdb==4.0.9
GitPython==3.1.24
huggingface-hub==0.1.2
idna==3.3
iniconfig==1.1.1
jieba==0.42.1
joblib==1.1.0
jsonlines==2.0.0
lm-dataformat==0.0.19
lm-eval @ git+https://github.com/EleutherAI/lm-evaluation-harness.git@dc937d4b70af819c5695e09d94e59e4cdb1e40ad
mbstrdecoder==1.1.0
mock==4.0.3
mpi4py==3.0.3
msgfy==0.2.0
multidict==5.2.0
multiprocess==0.70.12.2
mypy-extensions==0.4.3
nagisa==0.2.7
ninja==1.10.2.3
numexpr==2.7.2
numpy==1.20.2
openai==0.6.4
packaging==21.3
pandas==1.3.4
pathspec==0.9.0
pathtools==0.1.2
pathvalidate==2.5.0
Pillow==8.4.0
pkg_resources==0.0.0
pluggy==0.13.1
portalocker==2.3.2
promise==2.3
protobuf==3.19.1
psutil==5.8.0
py==1.11.0
pyarrow==6.0.1
pybind11==2.6.2
pycountry==20.7.3
pyparsing==3.0.6
pytablewriter==0.58.0
pytest==6.2.3
python-dateutil==2.8.2
pytz==2021.3
PyYAML==6.0
regex==2021.11.10
rehash==1.0.0
requests==2.26.0
sacrebleu==1.5.0
sacremoses==0.0.46
scikit-learn==1.0.1
scipy==1.7.3
sentry-sdk==1.5.0
shortuuid==1.0.8
six==1.16.0
smmap==5.0.0
sqlitedict==1.6.0
subprocess32==3.5.4
tabledata==1.3.0
tcolorpy==0.1.1
tensorboardX==1.8
threadpoolctl==3.0.0
tokenizers==0.10.2
toml==0.10.2
torch==1.8.0
torchaudio==0.8.0
torchvision==0.9.0
tqdm==4.62.3
tqdm-multiprocess==0.0.11
transformers==4.5.0
triton==0.4.2
typed-ast==1.5.0
typepy==1.3.0
typing_extensions==4.0.0
ujson==4.3.0
urllib3==1.26.7
wandb==0.10.28
wcwidth==0.2.5
xxhash==2.0.2
yarl==1.7.2
zstandard==0.15.2

Additional context

None

StellaAthena commented 2 years ago

Thanks for bringing this to our attention! If you’re having the same issue with NVIDIA’s repo I recommend opening an issue on DeepSpeed as well, and linking the two. Personally, I have a lot going on right now but I can look into this in a week or so.

pwstegman commented 2 years ago

Thank you! I've opened an issue on the DeepSpeed repo: https://github.com/microsoft/DeepSpeed/issues/1595. I'll also look into it to see if I can find anything.

StellaAthena commented 2 years ago

map::at appears to be a C++ thing.

pwstegman commented 2 years ago

Downgrading my Nvidia driver fixed the issue!

sudo apt install nvidia-driver-440

This installed Nvidia driver 460.91.03 (not sure why it's not 440) but it works! I was previously on driver version 495.44.