Comments (2)
JonasGeiping
commented on June 25, 2024
1
Hi! Thanks for trying the new version. Sorry, the installation command still refered to the older version, this is fixed now.
For the dataset, you should be warned that impl.forbid_dataset_preprocessing=True is set, and no new dataset is generated. Just, in case, I've flipped that flag to a default state of False now.
Finally, for Unexpected optimization option max_autotune_gemm, what PyTorch version do you have. This variant of the inductor should have been merged by now, but maybe this is still only in the nightlies.
In any case, you can disable this setting via impl._inductor_vars=null.
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tatami-galaxy
commented on June 25, 2024
Thanks it works now 👍🏽
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Related Issues (20)
- RuntimeError: CUDA error: CUBLAS_STATUS_NOT_INITIALIZED when calling `cublasCreate(handle)` while running evaluation HOT 10
- Pretraining on a single RTX 3060 HOT 2
- GLUE evaluation numbers are very poor, if increase the sequence length to 512 and float 32 HOT 5
- Evaluation failed on MNLI and STSB Datasets for Last1.13release HOT 3
- I run the test command,got this error,how to fix it?looks like no dataset HOT 12
- Tutorial for pretrain RoBERTa with custom data HOT 2
- Issue with torch.compile / dynamo HOT 5
- Question about sparse token prediction HOT 1
- Uploading trained model to HF/saving in HF format locally HOT 8
- Finetuning for SQuAD task HOT 2
- try it on Mac M1 but failed HOT 2
- can't import cramming HOT 2
- TypeError: _load_optimizer() missing 1 required positional argument: 'initial_time' HOT 1
- torch._dynamo error on step 2: calling compiler function 'inductor' HOT 7
- Finetuning for token classification HOT 3
- Configs for GPT? HOT 2
- From PR 43 HOT 5
- Unable to replicate the results using the default command HOT 15
- How to load local data HOT 2
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