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lean-dojo / ReProver

Retrieval-Augmented Theorem Provers for Lean
https://leandojo.org
MIT License
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"ValueError: Tensors must be contiguous" when training ReProver (CUDA 12.4) #66

Closed realharryhero closed 1 month ago

realharryhero commented 1 month ago

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: ๐Ÿš€ View run at https://wandb.ai/[REDACTED]/lightning_logs/runs/iykqoyqi 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 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%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 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: ๐Ÿš€ 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!

yangky11 commented 1 month ago

What was the command that triggered this error?

realharryhero commented 1 month ago

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

yangky11 commented 1 month ago

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?

realharryhero commented 1 month ago

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:

Logs

``` (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) Collecting loguru Using cached loguru-0.7.2-py3-none-any.whl.metadata (23 kB) Collecting deepspeed 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) Collecting openai 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 Using cached lean_dojo-2.0.3-py3-none-any.whl.metadata (7.9 kB) Collecting vllm Using cached vllm-0.5.3.post1-cp38-abi3-manylinux1_x86_64.whl.metadata (1.8 kB) Collecting pytorch-lightning[extra] Using cached pytorch_lightning-2.3.3-py3-none-any.whl.metadata (21 kB) Collecting hjson (from deepspeed) Using cached hjson-3.1.0-py3-none-any.whl.metadata (2.6 kB) Collecting ninja (from deepspeed) Using cached ninja-1.11.1.1-py2.py3-none-manylinux1_x86_64.manylinux_2_5_x86_64.whl.metadata (5.3 kB) Requirement already satisfied: numpy in /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages (from deepspeed) (2.0.1) Collecting nvidia-ml-py (from deepspeed) Using cached nvidia_ml_py-12.555.43-py3-none-any.whl.metadata (8.6 kB) Collecting packaging>=20.0 (from deepspeed) Using cached packaging-24.1-py3-none-any.whl.metadata (3.2 kB) Collecting psutil (from deepspeed) Using cached psutil-6.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (21 kB) Collecting py-cpuinfo (from deepspeed) Using cached py_cpuinfo-9.0.0-py3-none-any.whl.metadata (794 bytes) Collecting pydantic (from deepspeed) Using cached pydantic-2.8.2-py3-none-any.whl.metadata (125 kB) Requirement already satisfied: torch in /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages (from deepspeed) (2.4.0) Collecting PyYAML>=5.4 (from pytorch-lightning[extra]) Using cached PyYAML-6.0.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.1 kB) Requirement already satisfied: fsspec>=2022.5.0 in /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages (from fsspec[http]>=2022.5.0->pytorch-lightning[extra]) (2024.6.1) Collecting torchmetrics>=0.7.0 (from pytorch-lightning[extra]) Using cached torchmetrics-1.4.0.post0-py3-none-any.whl.metadata (19 kB) Requirement already satisfied: typing-extensions>=4.4.0 in /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages (from pytorch-lightning[extra]) (4.11.0) Collecting lightning-utilities>=0.10.0 (from pytorch-lightning[extra]) Using cached lightning_utilities-0.11.6-py3-none-any.whl.metadata (5.2 kB) Collecting matplotlib>3.1 (from pytorch-lightning[extra]) Using cached matplotlib-3.9.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (11 kB) Collecting omegaconf>=2.2.3 (from pytorch-lightning[extra]) Using cached omegaconf-2.3.0-py3-none-any.whl.metadata (3.9 kB) Collecting hydra-core>=1.2.0 (from pytorch-lightning[extra]) Using cached hydra_core-1.3.2-py3-none-any.whl.metadata (5.5 kB) Collecting jsonargparse>=4.27.7 (from jsonargparse[signatures]>=4.27.7; extra == "extra"->pytorch-lightning[extra]) Using cached jsonargparse-4.32.0-py3-none-any.whl.metadata (12 kB) Collecting rich>=12.3.0 (from pytorch-lightning[extra]) Using cached rich-13.7.1-py3-none-any.whl.metadata (18 kB) Collecting tensorboardX>=2.2 (from pytorch-lightning[extra]) Using cached tensorboardX-2.6.2.2-py2.py3-none-any.whl.metadata (5.8 kB) Collecting bitsandbytes>=0.42.0 (from pytorch-lightning[extra]) Downloading bitsandbytes-0.43.3-py3-none-manylinux_2_24_x86_64.whl.metadata (3.5 kB) Requirement already satisfied: filelock in /home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages (from transformers) (3.15.4) Collecting huggingface-hub<1.0,>=0.23.2 (from transformers) Downloading huggingface_hub-0.24.5-py3-none-any.whl.metadata (13 kB) Collecting regex!=2019.12.17 (from transformers) Using cached regex-2024.7.24-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (40 kB) Collecting requests (from transformers) Using cached requests-2.32.3-py3-none-any.whl.metadata (4.6 kB) Collecting safetensors>=0.4.1 (from transformers) Using cached safetensors-0.4.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.8 kB) Collecting tokenizers<0.20,>=0.19 (from transformers) Using cached tokenizers-0.19.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.7 kB) Collecting click!=8.0.0,>=7.1 (from wandb) Using cached click-8.1.7-py3-none-any.whl.metadata (3.0 kB) Collecting docker-pycreds>=0.4.0 (from wandb) Using cached 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pydantic-core==2.20.1 (from pydantic->deepspeed) Using cached pydantic_core-2.20.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.6 kB) Collecting msgpack<2.0.0,>=1.0.0 (from ray>=2.8->ray[default]>=2.8->lean-dojo) Using cached msgpack-1.0.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (9.1 kB) Collecting aiohttp-cors (from ray[default]>=2.8->lean-dojo) Using cached aiohttp_cors-0.7.0-py3-none-any.whl.metadata (20 kB) Collecting colorful (from ray[default]>=2.8->lean-dojo) Using cached colorful-0.5.6-py2.py3-none-any.whl.metadata (16 kB) Collecting py-spy>=0.2.0 (from ray[default]>=2.8->lean-dojo) Using cached py_spy-0.3.14-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (16 kB) Collecting opencensus (from ray[default]>=2.8->lean-dojo) Using cached opencensus-0.11.4-py2.py3-none-any.whl.metadata (12 kB) Collecting smart-open (from ray[default]>=2.8->lean-dojo) Using cached smart_open-7.0.4-py3-none-any.whl.metadata (23 kB) 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Using cached charset_normalizer-3.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (140 kB) Using cached contourpy-1.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (306 kB) Using cached cycler-0.12.1-py3-none-any.whl (8.3 kB) Using cached docstring_parser-0.16-py3-none-any.whl (36 kB) Using cached email_validator-2.2.0-py3-none-any.whl (33 kB) Using cached fastapi_cli-0.0.4-py3-none-any.whl (9.5 kB) Using cached fonttools-4.53.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.9 MB) Using cached frozenlist-1.4.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (272 kB) Using cached gitdb-4.0.11-py3-none-any.whl (62 kB) Downloading grpcio-1.65.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.7 MB) โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” 5.7/5.7 MB 16.4 MB/s eta 0:00:00 Using cached h11-0.14.0-py3-none-any.whl (58 kB) Using cached httptools-0.6.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (318 kB) Using cached idna-3.7-py3-none-any.whl (66 kB) Using cached interegular-0.3.3-py37-none-any.whl (23 kB) Using cached kiwisolver-1.4.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.4 MB) Using cached markdown_it_py-3.0.0-py3-none-any.whl (87 kB) Using cached msgpack-1.0.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (409 kB) Using cached multidict-6.0.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (128 kB) Using cached py_spy-0.3.14-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (3.0 MB) Using cached PyJWT-2.8.0-py3-none-any.whl (22 kB) Using cached PyNaCl-1.5.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (856 kB) Using cached pyparsing-3.1.2-py3-none-any.whl (103 kB) Using cached python_dateutil-2.9.0.post0-py2.py3-none-any.whl 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โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” 519.3/519.3 kB 19.0 MB/s eta 0:00:00 Using cached Deprecated-1.2.14-py2.py3-none-any.whl (9.6 kB) Using cached diskcache-5.6.3-py3-none-any.whl (45 kB) Using cached jsonschema-4.23.0-py3-none-any.whl (88 kB) Using cached referencing-0.35.1-py3-none-any.whl (26 kB) Using cached lark-1.1.9-py3-none-any.whl (111 kB) Using cached memray-1.13.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.4 MB) Using cached nest_asyncio-1.6.0-py3-none-any.whl (5.2 kB) Using cached numba-0.60.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (3.7 MB) Using cached opencensus-0.11.4-py2.py3-none-any.whl (128 kB) Using cached pyairports-2.1.1-py3-none-any.whl (371 kB) Using cached pycountry-24.6.1-py3-none-any.whl (6.3 MB) Using cached smart_open-7.0.4-py3-none-any.whl (61 kB) Using cached cffi-1.16.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (464 kB) Using cached cryptography-43.0.0-cp39-abi3-manylinux_2_28_x86_64.whl (4.0 MB) Using cached dill-0.3.7-py3-none-any.whl (115 kB) Using cached distlib-0.3.8-py2.py3-none-any.whl (468 kB) Using cached dnspython-2.6.1-py3-none-any.whl (307 kB) Using cached google_api_core-2.19.1-py3-none-any.whl (139 kB) Using cached importlib_resources-6.4.0-py3-none-any.whl (38 kB) Using cached jsonschema_specifications-2023.12.1-py3-none-any.whl (18 kB) Using cached llvmlite-0.43.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (43.9 MB) Using cached mdurl-0.1.2-py3-none-any.whl (10.0 kB) Using cached opencensus_context-0.1.3-py2.py3-none-any.whl (5.1 kB) Using cached pyarrow-17.0.0-cp311-cp311-manylinux_2_28_x86_64.whl (39.9 MB) Using cached rpds_py-0.19.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (355 kB) Using cached smmap-5.0.1-py3-none-any.whl (24 kB) Using cached textual-0.74.0-py3-none-any.whl (566 kB) Using cached typer-0.12.3-py3-none-any.whl (47 kB) Using cached wrapt-1.16.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (80 kB) Downloading multiprocess-0.70.15-py311-none-any.whl (135 kB) โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” 135.4/135.4 kB 12.9 MB/s eta 0:00:00 Using cached pandas-2.2.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB) Using cached xxhash-3.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB) Using cached google_auth-2.32.0-py2.py3-none-any.whl (195 kB) Using cached googleapis_common_protos-1.63.2-py2.py3-none-any.whl (220 kB) Using cached proto_plus-1.24.0-py3-none-any.whl (50 kB) Using cached pytz-2024.1-py2.py3-none-any.whl (505 kB) Using cached shellingham-1.5.4-py2.py3-none-any.whl (9.8 kB) Using cached tzdata-2024.1-py2.py3-none-any.whl (345 kB) Using cached pycparser-2.22-py3-none-any.whl (117 kB) Using cached cachetools-5.4.0-py3-none-any.whl (9.5 kB) Using cached linkify_it_py-2.0.3-py3-none-any.whl (19 kB) Using cached pyasn1_modules-0.4.0-py3-none-any.whl (181 kB) Using cached rsa-4.9-py3-none-any.whl (34 kB) Using cached mdit_py_plugins-0.4.1-py3-none-any.whl (54 kB) Using cached pyasn1-0.6.0-py2.py3-none-any.whl (85 kB) Using cached uc_micro_py-1.0.3-py3-none-any.whl (6.2 kB) 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: โ€˜data/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) - โ€˜data/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: ๐Ÿš€ View run at https://wandb.ai/greathero1user/lightning_logs/runs/e4q048jk 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 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 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 2000/2000 [00:00<00:00, 559987.18it/s] 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 main() File "/home/mfan/ReProver/generation/main.py", line 20, in main cli = CLI(RetrievalAugmentedGenerator, GeneratorDataModule) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/cli.py", line 394, in __init__ self._run_subcommand(self.subcommand) File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/cli.py", line 701, in _run_subcommand fn(**fn_kwargs) File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py", line 543, in fit call._call_and_handle_interrupt( File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 105, in launch return function(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py", line 579, in _fit_impl self._run(model, ckpt_path=ckpt_path) File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py", line 962, in _run self.strategy.setup(self) File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/deepspeed.py", line 350, in setup self.init_deepspeed() File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/deepspeed.py", line 451, in init_deepspeed self._initialize_deepspeed_train(self.model) File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/deepspeed.py", line 423, in _setup_model_and_optimizer deepspeed_engine, deepspeed_optimizer, _, _ = deepspeed.initialize( ^^^^^^^^^^^^^^^^^^^^^ File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/__init__.py", line 181, in initialize engine = DeepSpeedEngine(args=args, ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 262, in __init__ self._configure_distributed_model(model) File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 1148, in _configure_distributed_model self._broadcast_model() File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/cli.py", line 394, in __init__ [rank0]: self._run_subcommand(self.subcommand) [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/cli.py", line 701, in _run_subcommand [rank0]: fn(**fn_kwargs) [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py", line 543, in fit [rank0]: call._call_and_handle_interrupt( [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 105, in launch [rank0]: return function(*args, **kwargs) [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py", line 579, in _fit_impl [rank0]: self._run(model, ckpt_path=ckpt_path) [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py", line 962, in _run [rank0]: self.strategy.setup(self) [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/deepspeed.py", line 350, in setup [rank0]: self.init_deepspeed() [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/deepspeed.py", line 451, in init_deepspeed [rank0]: self._initialize_deepspeed_train(self.model) [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/pytorch_lightning/strategies/deepspeed.py", line 423, in _setup_model_and_optimizer [rank0]: deepspeed_engine, deepspeed_optimizer, _, _ = deepspeed.initialize( [rank0]: ^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/__init__.py", line 181, in initialize [rank0]: engine = DeepSpeedEngine(args=args, [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 262, in __init__ [rank0]: self._configure_distributed_model(model) [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 1148, in _configure_distributed_model [rank0]: self._broadcast_model() [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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/miniconda3/envs/ReProver/lib/python3.11/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper [rank0]: return func(*args, **kwargs) [rank0]: ^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn [rank0]: return fn(*args, **kwargs) [rank0]: ^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/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]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [rank0]: return func(*args, **kwargs) [rank0]: ^^^^^^^^^^^^^^^^^^^^^ [rank0]: File "/home/mfan/miniconda3/envs/ReProver/lib/python3.11/site-packages/torch/distributed/distributed_c10d.py", line 2140, in broadcast [rank0]: work = group.broadcast([tensor], opts) [rank0]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [rank0]: ValueError: Tensors must be contiguous wandb: ๐Ÿš€ View run train_generator_novel_premises at: https://wandb.ai/greathero1user/lightning_logs/runs/e4q048jk wandb: โญ๏ธ View project at: https://wandb.ai/greathero1user/lightning_logs wandb: Synced 6 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s) wandb: Find logs at: /tmp/wandb/run-20240731_150444-e4q048jk/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'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.)

realharryhero commented 1 month ago

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!

huolongguo1O commented 3 weeks ago

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?

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yifan123 commented 2 weeks ago

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!