Closed realharryhero closed 1 month ago
What was the command that triggered this error?
python generation/main.py fit --config generation/confs/cli_lean4_novel_premises.yaml --trainer.logger.name train_generator_novel_premises --trainer.logger.save_dir logs/train_generator_novel_premises # LeanDojo Benchmark 4, `novel_premises` split
I wasn't able to reproduce the error. From the logs, it looks like the error is in PyTorch Lightning or DeepSpeed. So I don't think adding a . contiguous()
in ReProver would actually help. Have you tried creating a new conda environment and re-install those dependencies?
The error still remains, even when using CUDA 12.1 (and python 3.11). It does seem to be a common issue with DeepSpeed according to this link, but I'm still not sure why it then only doesn't work for me. The full logs, after installing PyTorch but before installing DeepSpeed, are below:
```
(ReProver) mfan@localhost:~/ReProver$ pip install tqdm loguru deepspeed "pytorch-lightning[extra]" transformers wandb openai rank_bm25 lean-dojo vllm
Collecting tqdm
Using cached tqdm-4.66.4-py3-none-any.whl.metadata (57 kB)
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Using cached loguru-0.7.2-py3-none-any.whl.metadata (23 kB)
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Using cached deepspeed-0.14.4-py3-none-any.whl
Collecting transformers
Using cached transformers-4.43.3-py3-none-any.whl.metadata (43 kB)
Collecting wandb
Using cached wandb-0.17.5-py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (10 kB)
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Using cached openai-1.37.1-py3-none-any.whl.metadata (22 kB)
Collecting rank_bm25
Using cached rank_bm25-0.2.2-py3-none-any.whl.metadata (3.2 kB)
Collecting lean-dojo
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Collecting vllm
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Requirement already satisfied: numpy in /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages (from deepspeed) (2.0.1)
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โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ 61.0/61.0 kB 2.8 MB/s eta 0:00:00
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Installing collected packages: sentencepiece, pytz, pyairports, py-spy, py-cpuinfo, opencensus-context, nvidia-ml-py, ninja, hjson, distlib, colorful, antlr4-python3-runtime, xxhash, wrapt, websockets, uvloop, urllib3, uc-micro-py, tzdata, types-toml, types-psutil, triton, tqdm, toml, sniffio, smmap, shellingham, setproctitle, safetensors, rpds-py, regex, pyzmq, PyYAML, python-multipart, python-dotenv, python-dateutil, pyparsing, pyjwt, pydantic-core, pycparser, pycountry, pyasn1, psutil, protobuf, prometheus-client, platformdirs, packaging, nvidia-cudnn-cu12, numpy, nest-asyncio, multidict, msgpack, mdurl, lxml, loguru, llvmlite, lark, kiwisolver, interegular, importlib-resources, idna, httptools, h11, grpcio, frozenlist, fonttools, docstring-parser, docker-pycreds, dnspython, distro, diskcache, dill, cycler, cmake, cloudpickle, click, charset-normalizer, certifi, cachetools, attrs, annotated-types, aiohappyeyeballs, yarl, virtualenv, uvicorn, typeshed-client, tensorboardX, smart-open, sentry-sdk, rsa, requests, referencing, rank_bm25, pydantic, pyasn1-modules, pyarrow, proto-plus, pandas, omegaconf, numba, multiprocess, markdown-it-py, linkify-it-py, lightning-utilities, jsonargparse, httpcore, googleapis-common-protos, gitdb, email_validator, Deprecated, contourpy, cffi, anyio, aiosignal, watchfiles, torch, tiktoken, starlette, rich, pynacl, mdit-py-plugins, matplotlib, lm-format-enforcer, jsonschema-specifications, hydra-core, huggingface-hub, httpx, google-auth, gitpython, cryptography, aiohttp, xformers, wandb, vllm-flash-attn, typer, torchvision, torchmetrics, tokenizers, prometheus-fastapi-instrumentator, openai, jsonschema, google-api-core, deepspeed, bitsandbytes, aiohttp-cors, transformers, textual, ray, pytorch-lightning, pygithub, opencensus, fastapi-cli, datasets, outlines, memray, fastapi, vllm, lean-dojo
Attempting uninstall: triton
Found existing installation: triton 3.0.0
Uninstalling triton-3.0.0:
Successfully uninstalled triton-3.0.0
Attempting uninstall: nvidia-cudnn-cu12
Found existing installation: nvidia-cudnn-cu12 9.1.0.70
Uninstalling nvidia-cudnn-cu12-9.1.0.70:
Successfully uninstalled nvidia-cudnn-cu12-9.1.0.70
Attempting uninstall: numpy
Found existing installation: numpy 2.0.1
Uninstalling numpy-2.0.1:
Successfully uninstalled numpy-2.0.1
Attempting uninstall: torch
Found existing installation: torch 2.4.0
Uninstalling torch-2.4.0:
Successfully uninstalled torch-2.4.0
Attempting uninstall: torchvision
Found existing installation: torchvision 0.19.0
Uninstalling torchvision-0.19.0:
Successfully uninstalled torchvision-0.19.0
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
torchaudio 2.4.0 requires torch==2.4.0, but you have torch 2.3.1 which is incompatible.
Successfully installed Deprecated-1.2.14 PyYAML-6.0.1 aiohappyeyeballs-2.3.2 aiohttp-3.10.0 aiohttp-cors-0.7.0 aiosignal-1.3.1 annotated-types-0.7.0 antlr4-python3-runtime-4.9.3 anyio-4.4.0 attrs-23.2.0 bitsandbytes-0.43.3 cachetools-5.4.0 certifi-2024.7.4 cffi-1.16.0 charset-normalizer-3.3.2 click-8.1.7 cloudpickle-3.0.0 cmake-3.30.1 colorful-0.5.6 contourpy-1.2.1 cryptography-43.0.0 cycler-0.12.1 datasets-2.14.4 deepspeed-0.14.4 dill-0.3.7 diskcache-5.6.3 distlib-0.3.8 distro-1.9.0 dnspython-2.6.1 docker-pycreds-0.4.0 docstring-parser-0.16 email_validator-2.2.0 fastapi-0.111.1 fastapi-cli-0.0.4 fonttools-4.53.1 frozenlist-1.4.1 gitdb-4.0.11 gitpython-3.1.43 google-api-core-2.19.1 google-auth-2.32.0 googleapis-common-protos-1.63.2 grpcio-1.65.2 h11-0.14.0 hjson-3.1.0 httpcore-1.0.5 httptools-0.6.1 httpx-0.27.0 huggingface-hub-0.24.5 hydra-core-1.3.2 idna-3.7 importlib-resources-6.4.0 interegular-0.3.3 jsonargparse-4.32.0 jsonschema-4.23.0 jsonschema-specifications-2023.12.1 kiwisolver-1.4.5 lark-1.1.9 lean-dojo-2.0.3 lightning-utilities-0.11.6 linkify-it-py-2.0.3 llvmlite-0.43.0 lm-format-enforcer-0.10.3 loguru-0.7.2 lxml-5.2.2 markdown-it-py-3.0.0 matplotlib-3.9.1 mdit-py-plugins-0.4.1 mdurl-0.1.2 memray-1.13.4 msgpack-1.0.8 multidict-6.0.5 multiprocess-0.70.15 nest-asyncio-1.6.0 ninja-1.11.1.1 numba-0.60.0 numpy-1.26.4 nvidia-cudnn-cu12-8.9.2.26 nvidia-ml-py-12.555.43 omegaconf-2.3.0 openai-1.37.1 opencensus-0.11.4 opencensus-context-0.1.3 outlines-0.0.46 packaging-24.1 pandas-2.2.2 platformdirs-4.2.2 prometheus-client-0.20.0 prometheus-fastapi-instrumentator-7.0.0 proto-plus-1.24.0 protobuf-5.27.2 psutil-6.0.0 py-cpuinfo-9.0.0 py-spy-0.3.14 pyairports-2.1.1 pyarrow-17.0.0 pyasn1-0.6.0 pyasn1-modules-0.4.0 pycountry-24.6.1 pycparser-2.22 pydantic-2.8.2 pydantic-core-2.20.1 pygithub-2.3.0 pyjwt-2.8.0 pynacl-1.5.0 pyparsing-3.1.2 python-dateutil-2.9.0.post0 python-dotenv-1.0.1 python-multipart-0.0.9 pytorch-lightning-2.3.3 pytz-2024.1 pyzmq-26.0.3 rank_bm25-0.2.2 ray-2.34.0 referencing-0.35.1 regex-2024.7.24 requests-2.32.3 rich-13.7.1 rpds-py-0.19.1 rsa-4.9 safetensors-0.4.3 sentencepiece-0.2.0 sentry-sdk-2.12.0 setproctitle-1.3.3 shellingham-1.5.4 smart-open-7.0.4 smmap-5.0.1 sniffio-1.3.1 starlette-0.37.2 tensorboardX-2.6.2.2 textual-0.74.0 tiktoken-0.7.0 tokenizers-0.19.1 toml-0.10.2 torch-2.3.1 torchmetrics-1.4.0.post0 torchvision-0.18.1 tqdm-4.66.4 transformers-4.43.3 triton-2.3.1 typer-0.12.3 types-psutil-6.0.0.20240621 types-toml-0.10.8.20240310 typeshed-client-2.7.0 tzdata-2024.1 uc-micro-py-1.0.3 urllib3-2.2.2 uvicorn-0.30.3 uvloop-0.19.0 virtualenv-20.26.3 vllm-0.5.3.post1 vllm-flash-attn-2.5.9.post1 wandb-0.17.5 watchfiles-0.22.0 websockets-12.0 wrapt-1.16.0 xformers-0.0.27 xxhash-3.4.1 yarl-1.9.4
(ReProver) mfan@localhost:~/ReProver$ export PYTHONPATH=$PYTHONPATH:/home/mfan/ReProver
(ReProver) mfan@localhost:~/ReProver$ python scripts/download_data.py
2024-07-31 15:00:20.559 | INFO | __main__:main:39 - Namespace(data_path='data')
2024-07-31 15:00:20.560 | INFO | __main__:main:45 - Downloading https://zenodo.org/records/12740403/files/leandojo_benchmark_4.tar.gz?download=1
--2024-07-31 15:00:20-- https://zenodo.org/records/12740403/files/leandojo_benchmark_4.tar.gz?download=1
Resolving zenodo.org (zenodo.org)... 188.184.98.238, 188.185.79.172, 188.184.103.159, ...
Connecting to zenodo.org (zenodo.org)|188.184.98.238|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 68141936 (65M) [application/octet-stream]
Saving to: โdata/leandojo_benchmark_4.tar.gz?download=1โ
data/leandojo_benchmark_4. 100%[======================================>] 64.98M 514KB/s in 2m 23s
2024-07-31 15:02:43 (466 KB/s) - โdata/leandojo_benchmark_4.tar.gz?download=1โ saved [68141936/68141936]
2024-07-31 15:02:43.999 | INFO | __main__:main:51 - Extracting data/leandojo_benchmark_4.tar.gz?download=1
2024-07-31 15:02:46.035 | INFO | __main__:main:54 - Removing data/leandojo_benchmark_4.tar.gz?download=1
2024-07-31 15:02:46.038 | INFO | __main__:main:57 - Done!
(ReProver) mfan@localhost:~/ReProver$ python scripts/trace_repos.py
2024-07-31 15:04:07.132 | INFO | __main__:main:12 - Namespace(data_path='data')
2024-07-31 15:04:14.821 | INFO | __main__:main:26 - Repos to trace: set()
(ReProver) mfan@localhost:~/ReProver$ wandb login
wandb: Currently logged in as: greathero (greathero1user). Use `wandb login --relogin` to force relogin
(ReProver) mfan@localhost:~/ReProver$ python generation/main.py fit --config generation/confs/cli_lean4_novel_premises.yaml --trainer.logger.name train_generator_novel_premises --trainer.logger.save_dir logs/train_generator_novel_premises # LeanDojo Benchmark 4, `novel_premises` split
[2024-07-31 15:04:30,247] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[WARNING] async_io requires the dev libaio .so object and headers but these were not found.
[WARNING] async_io: please install the libaio-dev package with apt
[WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.1), only 1.0.0 is known to be compatible
2024-07-31 15:04:30.832 | INFO | __main__:main:19 - PID: 4634
Seed set to 3407
2024-07-31 15:04:31.673 | INFO | common:__init__:200 - Building the corpus from data/leandojo_benchmark_4/corpus.jsonl
2024-07-31 15:04:43.509 | INFO | generation.datamodule:__init__:147 - Without retrieval data
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
[rank: 0] Seed set to 3407
initializing deepspeed distributed: GLOBAL_RANK: 0, MEMBER: 1/1
wandb: Currently logged in as: greathero (greathero1user). Use `wandb login --relogin` to force relogin
wandb: WARNING Path logs/train_generator_novel_premises/wandb/ wasn't writable, using system temp directory.
wandb: WARNING Path logs/train_generator_novel_premises/wandb/ wasn't writable, using system temp directory
wandb: Tracking run with wandb version 0.17.5
wandb: Run data is saved locally in /tmp/wandb/run-20240731_150444-e4q048jk
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run train_generator_novel_premises
wandb: โญ๏ธ View project at https://wandb.ai/greathero1user/lightning_logs
wandb: ๐ View run at https://wandb.ai/greathero1user/lightning_logs/runs/e4q048jk
100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 118517/118517 [00:00<00:00, 621183.28it/s]
2024-07-31 15:04:58.114 | INFO | generation.datamodule:_load_data:60 - 246714 examples loaded
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2024-07-31 15:04:58.174 | INFO | generation.datamodule:_load_data:60 - 6240 examples loaded
Enabling DeepSpeed BF16. Model parameters and inputs will be cast to `bfloat16`.
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
2024-07-31 15:04:58.242 | INFO | common:get_optimizers:392 - Optimizing with FusedAdam
Using /home/mfan/.cache/torch_extensions/py311_cu121 as PyTorch extensions root...
Detected CUDA files, patching ldflags
Emitting ninja build file /home/mfan/.cache/torch_extensions/py311_cu121/fused_adam/build.ninja...
/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].
warnings.warn(
Building extension module fused_adam...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/3] /usr/local/cuda-12.1/bin/nvcc --generate-dependencies-with-compile --dependency-output multi_tensor_adam.cuda.o.d -DTORCH_EXTENSION_NAME=fused_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/ops/csrc/includes -I/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/ops/csrc/adam -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include/torch/csrc/api/include -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include/TH -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include/THC -isystem /usr/local/cuda-12.1/include -isystem /home/mfan/miniconda3/envs/ReProver/include/python3.11 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DVERSION_GE_1_5 -lineinfo --use_fast_math -gencode=arch=compute_86,code=sm_86 -gencode=arch=compute_86,code=compute_86 -DBF16_AVAILABLE -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -std=c++17 -c /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/ops/csrc/adam/multi_tensor_adam.cu -o multi_tensor_adam.cuda.o
[2/3] c++ -MMD -MF fused_adam_frontend.o.d -DTORCH_EXTENSION_NAME=fused_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/ops/csrc/includes -I/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/ops/csrc/adam -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include/torch/csrc/api/include -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include/TH -isystem /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/include/THC -isystem /usr/local/cuda-12.1/include -isystem /home/mfan/miniconda3/envs/ReProver/include/python3.11 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++17 -O3 -std=c++17 -g -Wno-reorder -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DVERSION_GE_1_5 -DBF16_AVAILABLE -c /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/ops/csrc/adam/fused_adam_frontend.cpp -o fused_adam_frontend.o
[3/3] c++ fused_adam_frontend.o multi_tensor_adam.cuda.o -shared -L/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/lib -lc10 -lc10_cuda -ltorch_cpu -ltorch_cuda -ltorch -ltorch_python -L/usr/local/cuda-12.1/lib64 -lcudart -o fused_adam.so
Loading extension module fused_adam...
Time to load fused_adam op: 16.516267776489258 seconds
Traceback (most recent call last):
File "/home/mfan/ReProver/generation/main.py", line 25, in
I'll search for a solution in the Github issue for DeepSpeed.
(I was previously using python 3.10; I installed CUDA 12.1 after installing driver version 545 instead of 530, due to bugs with 530 as in this link.)
According to this fix, I uninstalled DeepSpeed, cloned the DeepSpeed repository, made a change to broadcast a continuous tensor, and then downloaded DeepSpeed again from the cloned repository, and it works. Thank you!
I wasn't able to reproduce the error. From the logs, it looks like the error is in PyTorch Lightning or DeepSpeed. So I don't think adding a
. contiguous()
in ReProver would actually help. Have you tried creating a new conda environment and re-install those dependencies?
ๅจ4090ๅ3080Tiไธ้ๅฐๅๆ ท็้ฎ้ข๏ผ่ฝไธ่ฝๆฏๆไธไฝฟ็จdeepspeed
for param in model.parameters(): param.data = param.data.contiguous()
https://github.com/huggingface/transformers/issues/28293
After loading model, add the above line to convert weight to contiguous, it works for me!
Hello,
When I follow all the instructions (including setting up a conda environment), I recieve the following error:
Log
``` [2024-07-26 19:20:55,224] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) [WARNING] async_io requires the dev libaio .so object and headers but these were not found. [WARNING] async_io: please install the libaio-dev package with apt [WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. [WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH [WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 [WARNING] using untested triton version (2.3.1), only 1.0.0 is known to be compatible 2024-07-26 19:20:55.838 | INFO | __main__:main:19 - PID: 108346 Seed set to 3407 2024-07-26 19:20:56.872 | INFO | common:__init__:200 - Building the corpus from data/leandojo_benchmark_4/corpus.jsonl 2024-07-26 19:21:10.642 | INFO | generation.datamodule:__init__:147 - Without retrieval data GPU available: True (cuda), used: True TPU available: False, using: 0 TPU cores HPU available: False, using: 0 HPUs [rank: 0] Seed set to 3407 initializing deepspeed distributed: GLOBAL_RANK: 0, MEMBER: 1/1 wandb: Currently logged in as: [REDACTED] ([REDACTED]). Use `wandb login --relogin` to force relogin wandb: WARNING Path logs/train_generator_novel_premises/wandb/ wasn't writable, using system temp directory. wandb: WARNING Path logs/train_generator_novel_premises/wandb/ wasn't writable, using system temp directory wandb: Tracking run with wandb version 0.17.5 wandb: Run data is saved locally in /tmp/wandb/run-20240726_192111-iykqoyqi wandb: Run `wandb offline` to turn off syncing. wandb: Syncing run train_generator_novel_premises wandb: โญ๏ธ View project at https://wandb.ai/[REDACTED]/lightning_logs wandb: ๐ View run at https://wandb.ai/[REDACTED]/lightning_logs/runs/iykqoyqi 100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 118517/118517 [00:00<00:00, 574149.48it/s] 2024-07-26 19:21:21.894 | INFO | generation.datamodule:_load_data:60 - 246714 examples loaded 100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 2000/2000 [00:00<00:00, 527088.16it/s] 2024-07-26 19:21:21.956 | INFO | generation.datamodule:_load_data:60 - 6240 examples loaded Enabling DeepSpeed BF16. Model parameters and inputs will be cast to `bfloat16`. LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0] 2024-07-26 19:21:22.041 | INFO | common:get_optimizers:392 - Optimizing with FusedAdam Using /home/mfan/.cache/torch_extensions/py310_cu121 as PyTorch extensions root... Detected CUDA files, patching ldflags Emitting ninja build file /home/mfan/.cache/torch_extensions/py310_cu121/fused_adam/build.ninja... /home/mfan/ReProver/lib/python3.10/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST']. warnings.warn( Building extension module fused_adam... Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) [1/2] /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output multi_tensor_adam.cuda.o.d -DTORCH_EXTENSION_NAME=fused_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/ops/csrc/includes -I/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/ops/csrc/adam -isystem /home/mfan/ReProver/lib/python3.10/site-packages/torch/include -isystem /home/mfan/ReProver/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /home/mfan/ReProver/lib/python3.10/site-packages/torch/include/TH -isystem /home/mfan/ReProver/lib/python3.10/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /usr/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DVERSION_GE_1_5 -lineinfo --use_fast_math -gencode=arch=compute_86,code=sm_86 -gencode=arch=compute_86,code=compute_86 -DBF16_AVAILABLE -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -std=c++17 -c /home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/ops/csrc/adam/multi_tensor_adam.cu -o multi_tensor_adam.cuda.o [2/2] c++ fused_adam_frontend.o multi_tensor_adam.cuda.o -shared -L/home/mfan/ReProver/lib/python3.10/site-packages/torch/lib -lc10 -lc10_cuda -ltorch_cpu -ltorch_cuda -ltorch -ltorch_python -L/usr/local/cuda/lib64 -lcudart -o fused_adam.so Loading extension module fused_adam... Time to load fused_adam op: 14.073747634887695 seconds Traceback (most recent call last): File "/home/mfan/ReProver/generation/main.py", line 25, in
main()
File "/home/mfan/ReProver/generation/main.py", line 20, in main
cli = CLI(RetrievalAugmentedGenerator, GeneratorDataModule)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/cli.py", line 394, in __init__
self._run_subcommand(self.subcommand)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/cli.py", line 701, in _run_subcommand
fn(**fn_kwargs)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 543, in fit
call._call_and_handle_interrupt(
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 43, in _call_and_handle_interrupt
return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 105, in launch
return function(*args, **kwargs)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 579, in _fit_impl
self._run(model, ckpt_path=ckpt_path)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 962, in _run
self.strategy.setup(self)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 350, in setup
self.init_deepspeed()
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 451, in init_deepspeed
self._initialize_deepspeed_train(self.model)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 487, in _initialize_deepspeed_train
model, deepspeed_optimizer = self._setup_model_and_optimizer(model, optimizer, scheduler)
File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 423, in _setup_model_and_optimizer
deepspeed_engine, deepspeed_optimizer, _, _ = deepspeed.initialize(
File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/__init__.py", line 181, in initialize
engine = DeepSpeedEngine(args=args,
File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 262, in __init__
self._configure_distributed_model(model)
File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1148, in _configure_distributed_model
self._broadcast_model()
File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1068, in _broadcast_model
dist.broadcast(p.data, groups._get_broadcast_src_rank(), group=self.seq_data_parallel_group)
File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
return func(*args, **kwargs)
File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 224, in broadcast
return cdb.broadcast(tensor=tensor, src=src, group=group, async_op=async_op)
File "/home/mfan/ReProver/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
return fn(*args, **kwargs)
File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 199, in broadcast
return torch.distributed.broadcast(tensor=tensor, src=src, group=group, async_op=async_op)
File "/home/mfan/ReProver/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
return func(*args, **kwargs)
File "/home/mfan/ReProver/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 2140, in broadcast
work = group.broadcast([tensor], opts)
ValueError: Tensors must be contiguous
[rank0]: Traceback (most recent call last):
[rank0]: File "/home/mfan/ReProver/generation/main.py", line 25, in
[rank0]: main()
[rank0]: File "/home/mfan/ReProver/generation/main.py", line 20, in main
[rank0]: cli = CLI(RetrievalAugmentedGenerator, GeneratorDataModule)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/cli.py", line 394, in __init__
[rank0]: self._run_subcommand(self.subcommand)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/cli.py", line 701, in _run_subcommand
[rank0]: fn(**fn_kwargs)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 543, in fit
[rank0]: call._call_and_handle_interrupt(
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 43, in _call_and_handle_interrupt
[rank0]: return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 105, in launch
[rank0]: return function(*args, **kwargs)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 579, in _fit_impl
[rank0]: self._run(model, ckpt_path=ckpt_path)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 962, in _run
[rank0]: self.strategy.setup(self)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 350, in setup
[rank0]: self.init_deepspeed()
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 451, in init_deepspeed
[rank0]: self._initialize_deepspeed_train(self.model)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 487, in _initialize_deepspeed_train
[rank0]: model, deepspeed_optimizer = self._setup_model_and_optimizer(model, optimizer, scheduler)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/pytorch_lightning/strategies/deepspeed.py", line 423, in _setup_model_and_optimizer
[rank0]: deepspeed_engine, deepspeed_optimizer, _, _ = deepspeed.initialize(
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/__init__.py", line 181, in initialize
[rank0]: engine = DeepSpeedEngine(args=args,
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 262, in __init__
[rank0]: self._configure_distributed_model(model)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1148, in _configure_distributed_model
[rank0]: self._broadcast_model()
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1068, in _broadcast_model
[rank0]: dist.broadcast(p.data, groups._get_broadcast_src_rank(), group=self.seq_data_parallel_group)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank0]: return func(*args, **kwargs)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 224, in broadcast
[rank0]: return cdb.broadcast(tensor=tensor, src=src, group=group, async_op=async_op)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank0]: return fn(*args, **kwargs)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 199, in broadcast
[rank0]: return torch.distributed.broadcast(tensor=tensor, src=src, group=group, async_op=async_op)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[rank0]: return func(*args, **kwargs)
[rank0]: File "/home/mfan/ReProver/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 2140, in broadcast
[rank0]: work = group.broadcast([tensor], opts)
[rank0]: ValueError: Tensors must be contiguous
wandb: ๐ View run train_generator_novel_premises at: https://wandb.ai/[REDACTED]/lightning_logs/runs/iykqoyqi
wandb: โญ๏ธ View project at: https://wandb.ai/[REDACTED]/lightning_logs
wandb: Synced 5 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s)
wandb: Find logs at: /tmp/wandb/run-20240726_192111-iykqoyqi/logs
wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information.
```
I'm using CUDA 12.4, so that could be an issue. Otherwise, a result on StackOverflow seems to summarize what's occurring. If so, where would the .contiguous() function go? Thanks!