Merge branch 'main' into ensemble_manager

views_pipeline_core/templates/model/template_config_deployment.py

@@ -3,20 +3,18 @@
 from pathlib import Path
 import logging
 
-logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-
 def generate(
-    script_dir: Path,
+    script_path: Path,
     deployment_type: str = "shadow",
     additional_settings: Dict[str, any] = None,
 ) -> bool:
     """
     Generates a script that defines the `get_deployment_config` function for configuring the deployment status and settings.
 
     Parameters:
-        script_dir (Path): The directory where the generated deployment configuration script will be saved.
+        script_path (Path): The path where the generated deployment configuration script will be saved.
                            This should be a valid writable path.
         deployment_type (str, optional):
             The type of deployment. Must be one of "shadow", "deployed", "baseline", or "deprecated".
@@ -72,4 +70,4 @@ def get_deployment_config():
     deployment_config = {deployment_config}
     return deployment_config
 """
-    return save_script(script_dir, code)
+    return save_script(script_path, code)

views_pipeline_core/templates/model/template_config_hyperparameters.py

@@ -1,15 +1,17 @@
 from views_pipeline_core.templates.utils import save_script
 from pathlib import Path
+import logging
 
+logger = logging.getLogger(__name__)
 
-def generate(script_dir: Path) -> bool:
+def generate(script_path: Path) -> bool:
     """
     Generates a script that defines a function for obtaining hyperparameter configurations
     necessary for model training.
 
     Parameters:
-        script_dir (Path):
-            The directory where the generated deployment configuration script will be saved.
+        script_path (Path):
+            The path where the generated deployment configuration script will be saved.
             This should be a valid writable path.
 
     Returns:
@@ -32,4 +34,4 @@ def get_hp_config():
     }}
     return hyperparameters
 """
-    return save_script(script_dir, code)
+    return save_script(script_path, code)

views_pipeline_core/templates/model/template_config_meta.py

@@ -1,14 +1,15 @@
 from views_pipeline_core.templates.utils import save_script
 from pathlib import Path
+import logging
+logger = logging.getLogger(__name__)
 
-
-def generate(script_dir: Path, model_name: str, model_algorithm: str) -> bool:
+def generate(script_path: Path, model_name: str, model_algorithm: str) -> bool:
     """
     Generates a script that defines the `get_meta_config` function for model metadata.
 
     Parameters:
-        script_dir (Path):
-            The directory where the generated deployment configuration script will be saved.
+        script_path (Path):
+            The path where the generated deployment configuration script will be saved.
             This should be a valid writable path.
 
         model_name (str):
@@ -41,4 +42,4 @@ def generate(script_dir: Path, model_name: str, model_algorithm: str) -> bool:
     }}
     return meta_config
 """
-    return save_script(script_dir, code)
+    return save_script(script_path, code)

views_pipeline_core/templates/model/template_config_queryset.py

@@ -1,14 +1,15 @@
 from views_pipeline_core.templates.utils import save_script
 from pathlib import Path
+import logging
+logger = logging.getLogger(__name__)
 
-
-def generate(script_dir: Path, model_name: str) -> bool:
+def generate(script_path: Path, model_name: str) -> bool:
     """
     Generates a Python script that defines the `generate` function for configuring input data for model training
     using the viewser library.
 
     Args:
-        script_dir (Path): The directory where the generated deployment configuration script will be saved.
+        script_path (Path): The path where the generated deployment configuration script will be saved.
                            This should be a valid writable path.
         model_name (str): The name of the model for which the input data configuration is being generated.
                           This name is used to identify the relevant data in the viewser queryset.
@@ -58,4 +59,4 @@ def generate():
 
     return queryset_base
 """
-    return save_script(script_dir, code)
+    return save_script(script_path, code)

views_pipeline_core/templates/model/template_config_sweep.py

@@ -1,14 +1,15 @@
 from views_pipeline_core.templates.utils import save_script
 from pathlib import Path
+import logging
+logger = logging.getLogger(__name__)
 
-
-def generate(script_dir: Path, model_name: str, model_algorithm: str) -> bool:
+def generate(script_path: Path, model_name: str, model_algorithm: str) -> bool:
     """
     Generates a script that defines the `get_sweep_config` function for hyperparameter sweeps.
 
     Parameters:
-        script_dir (Path):
-            The directory where the generated deployment configuration script will be saved.
+        script_path (Path):
+            The path where the generated deployment configuration script will be saved.
             This should be a valid writable path.
 
         model_name (str):
@@ -52,4 +53,4 @@ def get_sweep_config():
 
     return sweep_config
 """
-    return save_script(script_dir, code)
+    return save_script(script_path, code)

views_pipeline_core/templates/model/template_main.py

@@ -1,8 +1,9 @@
 from views_pipeline_core.templates.utils import save_script
 from pathlib import Path
+import logging
+logger = logging.getLogger(__name__)
 
-
-def generate(script_dir: Path) -> bool:
+def generate(script_path: Path) -> bool:
     """
     Generates a Python script that sets up and executes model runs with Weights & Biases (WandB) integration.
 
@@ -11,8 +12,8 @@ def generate(script_dir: Path) -> bool:
     generated script includes command-line argument parsing, validation, and runtime logging.
 
     Parameters:
-        script_dir (Path):
-            The directory where the generated Python script will be saved. This should be a valid writable
+        script_path (Path):
+            The path where the generated Python script will be saved. This should be a valid writable
             path that exists within the project structure.
 
     Returns:
@@ -62,4 +63,4 @@ def generate(script_dir: Path) -> bool:
     else:
         # YourModelManager(model_path=model_path).execute_single_run(args)
 '''
-    return save_script(script_dir, code)
+    return save_script(script_path, code)

views_pipeline_core/templates/model/template_run_sh.py

@@ -0,0 +1,87 @@
+from pathlib import Path
+
+def generate(script_path: Path, package_name: str) -> bool:
+    """
+    Generates a shell script to set up the environment and run a Python script.
+
+    This function creates a shell script that:
+    - Checks if the operating system is macOS (Darwin) and updates the user's `.zshrc` file with necessary environment variables for `libomp`.
+    - Determines the script's directory and the project's root directory.
+    - Sets up the path for the Conda environment specific to the project.
+    - Activates the Conda environment if it exists, or creates a new one if it doesn't.
+    - Installs any missing or outdated Python packages listed in `requirements.txt`.
+    - Runs the main Python script with any provided command-line arguments.
+
+    Parameters:
+        script_path (Path): 
+            The path where the generated shell script will be saved. This should be a valid writable path.
+        package_name (str):
+            The name of the package to be used in the script.
+
+    Returns:
+        bool: 
+            True if the script was successfully written to the specified directory, False otherwise.
+
+    The generated shell script includes the following steps:
+    - Checks if the operating system is macOS and updates the `.zshrc` file with necessary environment variables for `libomp`.
+    - Determines the script's directory and the project's root directory.
+    - Sets up the path for the Conda environment specific to the project.
+    - Activates the Conda environment if it exists, or creates a new one if it doesn't.
+    - Installs any missing or outdated Python packages listed in `requirements.txt`.
+    - Runs the main Python script with any provided command-line arguments.
+
+    Note:
+        - Ensure that the `requirements.txt` file is present in the same directory as the generated shell script.
+        - The generated shell script is designed to be executed in a zsh shell.
+    """
+    code = f"""#!/bin/zsh
+
+if [[ "$OSTYPE" == "darwin"* ]]; then
+  if ! grep -q 'export LDFLAGS="-L/opt/homebrew/opt/libomp/lib"' ~/.zshrc; then
+    echo 'export LDFLAGS="-L/opt/homebrew/opt/libomp/lib"' >> ~/.zshrc
+  fi
+  if ! grep -q 'export CPPFLAGS="-I/opt/homebrew/opt/libomp/include"' ~/.zshrc; then
+    echo 'export CPPFLAGS="-I/opt/homebrew/opt/libomp/include"' >> ~/.zshrc
+  fi
+  if ! grep -q 'export DYLD_LIBRARY_PATH="/opt/homebrew/opt/libomp/lib:$DYLD_LIBRARY_PATH"' ~/.zshrc; then
+    echo 'export DYLD_LIBRARY_PATH="/opt/homebrew/opt/libomp/lib:$DYLD_LIBRARY_PATH"' >> ~/.zshrc
+  fi
+  source ~/.zshrc
+fi
+
+script_path=$(dirname "$(realpath $0)")
+project_path="$( cd "$script_path/../../" >/dev/null 2>&1 && pwd )"
+env_path="$project_path/envs/{package_name}"
+
+eval "$(conda shell.bash hook)"
+
+if [ -d "$env_path" ]; then
+  echo "Conda environment already exists at $env_path. Checking dependencies..."
+  conda activate "$env_path"
+  echo "$env_path is activated"
+
+  missing_packages=$(pip install --dry-run -r $script_path/requirements.txt 2>&1 | grep -v "Requirement already satisfied" | wc -l)
+  if [ "$missing_packages" -gt 0 ]; then
+    echo "Installing missing or outdated packages..."
+    pip install -r $script_path/requirements.txt
+  else
+    echo "All packages are up-to-date."
+  fi
+else
+  echo "Creating new Conda environment at $env_path..."
+  conda create --prefix "$env_path" python=3.11 -y
+  conda activate "$env_path"
+  pip install -r $script_path/requirements.txt
+fi
+
+echo "Running $script_path/main.py "
+python $script_path/main.py "$@"
+"""
+
+    try:
+      with open(script_path, "w", encoding="utf-8") as script_file:
+          script_file.write(code)
+          return True
+    except IOError as e:
+        print(f"An error occurred while writing to {script_path}: {e}")
+        return False