Tested it’s best to use the Service Principal method: We don’t want to do interactive authentication in the middle of script runs. East USįor Issue #1, the code sample of using AzureML SDK: The GPU enabled NC-series is only available on certain regions. # Let DDP initialize with default optionsĭef learn_localization(rank,world_size,opt,setup_params):įor Azure ML Compute Cluster VM selection, here’s the official documentation for VM series suggestion.įound the lowest unit price is NC6_Promo series 0.4USD/Hour Learn_localization(rank,world_size,opt,setup_params) Parser.add_argument('-training_data_path', type=str, default=trainset_path, help='path for training and validation data') Parser.add_argument('-saveEpoch', type=int, default=3, help='save model per saveEpoch') Parser.add_argument('-ma圎poch', type=int, default=30, help='number of training epoches') Parser = argparse.ArgumentParser(description='training project') Rpsf_trainset_path = mount_ctx.mount_point # Create mountcontext and mount the dataset #dataset.download(target_path='./data/train', overwrite=True) Subscription_id="4616643d-xxxx-xxxx-xxxx-0467f4bac6bf",ĭataset = Dataset.get_by_name(ws, name='rpsf-trainset') Service_principal_password='~.xxxxx-c~xxx-p4FAiQGfP0DbgEOg53V.') #To resolve Issue #2, perform Service Principal Authentication here ![]() ![]() From re import Workspace, Datasetįrom import ServicePrincipalAuthentication
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