Big thanks to for his post (would not have succeeded without it). I thought I’d post the exact steps I took for other new folks like myself. I’m new to fastai and managed to get Lesson 1 working in a Jupyter Notebook locally on my M1 Max. TypeError: Operation 'neg_out_mps()' does not support input type 'int64' in MPS backend. Getting this error for lesson 4 on mac m1 studio:įile ~/.pyenv/versions/3.9.7/envs/learning/lib/python3.9/site-packages/transformers/models/deberta_v2/modeling_deberta_v2.py:845, in DisentangledSelfAttention.disentangled_attention_bias(self, query_layer, key_layer, relative_pos, rel_embeddings, scale_factor) Num_train_epochs=epochs, weight_decay=0.01, report_to='none') Learning_rate=lr, warmup_ratio=0.1, lr_scheduler_type='cosine',Įvaluation_strategy="epoch", per_device_train_batch_size=bs, per_device_eval_batch_size=bs*2, # this ensures that the current current PyTorch installation was built with MPS activated.Īrgs = TrainingArgumentsWithMPSSupport('outputs', # this ensures that the current MacOS version is at least 12.3+ Let’s hope pytorch 1.12.2 has the fix merged and we can get rolling. Presumably nightly version of pytorch has this resolved but coudn’t make it work together with fastai, got back to the stage when cpu nor gpu didn’t do anything during training. Now, fine_tuning takes ages for me, doesn’t use nor gpu or cpu, can’t move forward.ĮDIT: OK, it didn’t appear to do anything so I played few times with new conda environment and well, I can confirm that 02-saving-a-basic-fastai-model.ipynb is working well using gpu (I checked, python process uses 99% gpu), it’s fast and working! Happy to see some benchmarks versus beefy nvidia gpus!ĮDIT2: OK, false positive, exporting the model fails and it seems to be pytorch issue. The missing part has been released within pytorch 1.12.0 MPS: Add adaptive max pool2d op by kulinseth Īlso, fastai added initial support for mps backend in v2.7.6 Regarding the NotImplementedError: The operator ‘aten::adaptive_max_pool2d.out’ is not current implemented for the MPS device.
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