Metadata-Version: 2.1
Name: delphai-ml-utils
Version: 1.0.1
Summary: A Python package to manage kube secrets.
Home-page: https://github.com/delphai/delphai-ml-utils
Author: ahmed
Author-email: ahmed.mahmoud@delphai.com
License: MIT
Description: # delphai-ml-utils
        
        ## Installation
        
        ```bash
        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.
        
        ```yaml
        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:
        
        ```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()
        ```
        
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
