Bug in the train-with-pytorch-trainer?
There may be a bug inFine-tune a pretrained modelFrom that link I select, “Open in Colab”.  The I selected from the menu, “Runtime->Run All”.  Everything appears to work file until I get to the section:from transformers import TrainingArgumentstraining_args = TrainingArguments(output_dir=“test_trainer”)I get the following output:/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py:3553 in run_code        ││                                                                                                  ││   3550 │   │   │   │   elif async_ :                                                             ││   3551 │   │   │   │   │   await eval(code_obj, self.user_global_ns, self.user_ns)               ││   3552 │   │   │   │   else:                                                                     ││ ❱ 3553 │   │   │   │   │   exec(code_obj, self.user_global_ns, self.user_ns)                     ││   3554 │   │   │   finally:                                                                      ││   3555 │   │   │   │   # Reset our crash handler in place                                        ││   3556 │   │   │   │   sys.excepthook = old_excepthook                                           ││ in <cell line: 3>:3                                                                              ││ ininit:114                                                                                  ││                                                                                                  ││ /usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1400 inpost_init││                                                                                                  ││   1397 │   │   if (                                                                              ││   1398 │   │   │   self.framework == “pt”                                                        ││   1399 │   │   │   and is_torch_available()                                                      ││ ❱ 1400 │   │   │   and (self.device.type != “cuda”)                                              ││   1401 │   │   │   and (self.device.type != “npu”)                                               ││   1402 │   │   │   and (get_xla_device_type(self.device) != “GPU”)                               ││   1403 │   │   │   and (self.fp16 or self.fp16_full_eval)                                        ││                                                                                                  ││ /usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1857 in device             ││                                                                                                  ││   1854 │   │   The device used by this process.                                                  ││   1855 │   │   “”"                                                                               ││   1856 │   │   requires_backends(self, [“torch”])                                                ││ ❱ 1857 │   │   return self._setup_devices                                                        ││   1858 │                                                                                         ││   1859 │@property││   1860 │   def n_gpu(self):                                                                      ││                                                                                                  ││ /usr/local/lib/python3.10/dist-packages/transformers/utils/generic.py:54 inget││                                                                                                  ││    51 │   │   attr = “_cached” + self.fget.name││    52 │   │   cached = getattr(obj, attr, None)                                                  ││    53 │   │   if cached is None:                                                                 ││ ❱  54 │   │   │   cached = self.fget(obj)                                                        ││    55 │   │   │   setattr(obj, attr, cached)                                                     ││    56 │   │   return cached                                                                      ││    57                                                                                            ││                                                                                                  ││ /usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1772 in _setup_devices     ││                                                                                                  ││   1769 │   │   logger.info(“PyTorch: setting up devices”)                                        ││   1770 │   │   if not is_sagemaker_mp_enabled():                                                 ││   1771 │   │   │   if not is_accelerate_available(min_version=“0.20.1”):                         ││ ❱ 1772 │   │   │   │   raise ImportError(                                                        ││   1773 │   │   │   │   │   "Using theTrainerwithPyTorchrequiresaccelerate>=0.20.1: P  ││   1774 │   │   │   │   )                                                                         ││   1775 │   │   │   AcceleratorState._reset_state(reset_partial_state=True)                       │╰──────────────────────────────────────────────────────────────────────────────────────────────────╯ImportError: Using theTrainerwithPyTorchrequiresaccelerate>=0.20.1: Please runpip install  transformers[torch]orpip install accelerate -UNothing runs after that.  Is it user error or is there a problem?Thanks
2023-09-01T17:50:41Z
huggingEars:Nothing runs after that. Is it user error or is there a problem?I’d recommend doing a quick search on the forums, this is a very popular question.pip install accelerate -Uand restart your runtime
2023-09-01T19:12:10Z
Thank you@muellerzrfor the quick and accurate response.  Sorry for the duplicate question, I had searched but was clearly using the wrong search terms.  I also noted that ‘evaluate’ had to be pip installed as well.  As a suggestion to huggingface team, maybe the model code could be updated or at least the text surrounding the accelerate and evaluate issues.