Merge branch 'mlmodel' of github.com:Hestia-Homes/Model into mlmodel

.github/workflows/cml.yml

@@ -0,0 +1,27 @@
+name: model-training
+on: 
+  push:
+    branches:
+      - mlmodel
+jobs:
+  run:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - uses: actions/setup-python@v4
+      - uses: iterative/setup-cml@v1
+      - name: Train model
+        env:
+          REPO_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          ls
+          cd model_data/simulation_system 
+          pip install -r requirements.txt
+          python3 training.py --train-filepath ./model_build_data/change_data/rdsap_full/train_validation_data.parquet --test-filepath ./model_build_data/change_data/rdsap_full/test_data.parquet
+
+          cd model_directory/RDSAP_CHANGE
+          echo "## MODEL METRICS from registry" > report.md
+          cat model_registry.csv >> report.md
+
+          cml comment create report.md
+          

model_data/simulation_system/training.py

@@ -1,6 +1,6 @@
 
 import argparse
-import boto3
+# import boto3
 import os 
 from pathlib import Path
 from datetime import datetime
@@ -152,7 +152,7 @@ def training(
     logger.info("--- Optimising model for deployment ---")
 
     deployment_model_path = model.optimise_model_for_deployment(deployment_path= output_base / DEPLOYMENT_FOLDER)
-    logger.info("Optimised version of best model can be found at: {deployment_model_path}")
+    logger.info(f"Optimised version of best model can be found at: {deployment_model_path}")
 
     # TODO: Need a model registry - for now have this as a CSV
     # Save this in the model directory
@@ -204,4 +204,4 @@ if __name__ == "__main__":
         test_filepath=args.test_filepath, 
         target_column=args.target_column, 
         model_type=args.model_type
-        )
+        )