diff --git a/Dockerfile.wandb b/Dockerfile.wandb
new file mode 100644
index 0000000..4736f1d
--- /dev/null
+++ b/Dockerfile.wandb
@@ -0,0 +1,15 @@
+# syntax=docker/dockerfile:1.4
+
+FROM python:3.9-slim
+RUN apt update && apt install gcc -y
+
+WORKDIR /launch
+
+COPY --link requirements.txt ./
+RUN pip install -r requirements.txt
+
+COPY --link data_loader.py ./
+RUN python data_loader.py  # loads the keras data
+
+COPY --link job.py configs/ ./
+ENTRYPOINT ["python", "job.py"]
diff --git a/runner.py b/runner.py
new file mode 100644
index 0000000..4c956c1
--- /dev/null
+++ b/runner.py
@@ -0,0 +1,32 @@
+# runner.py - Place this in your current working directory
+
+import sys
+import importlib.util
+import os
+
+def run_script(script_path, args=[]):
+    # Backup the original sys.argv
+    original_argv = sys.argv
+    
+    # Determine module name and path
+    module_name = os.path.basename(script_path).replace('.py', '')
+    spec = importlib.util.spec_from_file_location(module_name, script_path)
+    module = importlib.util.module_from_spec(spec)
+    
+    try:
+        # Mimic command line arguments
+        sys.argv = [script_path] + args
+        
+        # Load and execute the module
+        spec.loader.exec_module(module)
+        
+        # If the module has a main function, call it
+        if hasattr(module, 'main'):
+            module.main()
+    finally:
+        # Restore the original sys.argv
+        sys.argv = original_argv
+
+if __name__ == "__main__":
+    # Pass all arguments except the first (the script name itself) to run_script
+    run_script('./jobs/fashion_mnist_train/job.py', sys.argv[1:])