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Steps to reproduce the behavior:
Please use: 2 node(s), each with 8 GPUs. Image "INTERNAL_IMAGE:20241025" Training script:
python /opt/pytorch/lightning-thunder/thunder/benchmarks/benchmark_litgpt.py \ --model_name vicuna-33b-v1.3 \ --distributed_mode fsdp \ --shard_mode zero3 \ --compile dynamo_thunder \ --checkpoint_activations False \ --low_precision_mode none \ --micro_batch_size 2
system.device_product_name DGXH100 system.gpu_driver_version 535.129.03 libraries.cuda 12.6.2.004 libraries.pip.lightning 2.4.0.dev20240728 libraries.pip.lightning-thunder 0.2.0.dev0 libraries.pip.lightning-utilities 0.11.8 libraries.pip.litgpt 0.4.11 libraries.pip.nvfuser 0.2.20+git85c22a2 libraries.pip.pytorch-lightning 2.4.0 libraries.pip.torch 2.6.0a0+git96b30dc libraries.pip.torchmetrics 1.5.1 libraries.pip.torchvision 0.19.0a0+d23a6e1
The text was updated successfully, but these errors were encountered:
Recent comparison to torch.compile. There are some new models:
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IvanYashchuk
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🐛 Bug
To Reproduce
Steps to reproduce the behavior:
Please use:
2 node(s), each with 8 GPUs.
Image "INTERNAL_IMAGE:20241025"
Training script:
Environment
system.device_product_name DGXH100
system.gpu_driver_version 535.129.03
libraries.cuda 12.6.2.004
libraries.pip.lightning 2.4.0.dev20240728
libraries.pip.lightning-thunder 0.2.0.dev0
libraries.pip.lightning-utilities 0.11.8
libraries.pip.litgpt 0.4.11
libraries.pip.nvfuser 0.2.20+git85c22a2
libraries.pip.pytorch-lightning 2.4.0
libraries.pip.torch 2.6.0a0+git96b30dc
libraries.pip.torchmetrics 1.5.1
libraries.pip.torchvision 0.19.0a0+d23a6e1
The text was updated successfully, but these errors were encountered: