A Python package to manage kube secrets.
Project description
delphai-ml-utils
Installation
pip install delphai-ml-utils
Usage
- Upload to Azure Blob
The delphai-hybrid
cluster allows model training with gpu. This feature allows uploading the trained model from inside the cluster to Azure blobs.
This works by adding a config file to your project config/ml-config.yml
.
With this yaml file you can configure to which storage account you want to upload your trained model.
cluster: delphai-hybrid
training_dir: model-gpu
model_name: test-model
dest:
storage_account_secret: azure-storage/connection-string
training_dir
: is the output directory of your trained model (model directory)
model_name
: Name your model and with it name the new created azure container to save the model into it (Note if the container name already exists will throw an error)
storage_account_secret
: Here add the kubernetes secret name that contains the connection string to the storage account. example azure-storage/conenction-string
How to use with python:
from ml_utils import upload
# Train Model
model.train_model(train_df, use_cuda=True)
# Upload to Azure blob with delphai-ml-utils
upload.upload_to_azure_blob()
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