Setting the Working Directory and Entrypoint

When creating a Docker image for an ML project, after tasks such as establishing a base image, installing dependencies, and copying project files into the image using instructions like COPY or ADD, it becomes essential to define how the container will operate upon startup. This involves telling Docker where commands should be executed inside the container and what command should run by default. The WORKDIR, ENTRYPOINT, and CMD instructions in your Dockerfile accomplish this. These instructions are significant for making your containerized ML applications runnable and easy to use.

Setting the Execution Context with WORKDIR

The WORKDIR instruction sets the working directory for any subsequent RUN, CMD, ENTRYPOINT, COPY, and ADD instructions in the Dockerfile. Think of it as changing the current directory (cd) within the context of building and running your image.

If WORKDIR is not specified, Docker executes subsequent commands in the root directory (/). Explicitly setting a WORKDIR makes your Dockerfile instructions clearer and less reliant on absolute paths.

Benefits:

1. Readability: Avoids scattering absolute paths throughout your Dockerfile.
2. Portability: Makes it easier to restructure your project within the image later.
3. Consistency: Ensures commands like running Python scripts execute relative to a known project directory.

Example:

Consider an ML project structured like this on your host machine:

my_ml_project/
├── Dockerfile
├── requirements.txt
├── src/
│   ├── train.py
│   └── predict.py
└── data/
    └── dataset.csv

Instead of writing COPY src /app/src and then RUN python /app/src/train.py, you can use WORKDIR:

# Dockerfile snippet
# ... (FROM, install dependencies)

# Set the working directory
WORKDIR /app

# Copy application code relative to WORKDIR
COPY src/ ./src/
COPY requirements.txt .

# Install dependencies (pip install -r requirements.txt)

# Copy data (might be better handled with volumes, see Chapter 3)
COPY data/ ./data/

# Subsequent commands like CMD or ENTRYPOINT will run from /app
CMD ["python", "src/train.py"]

In this example, WORKDIR /app creates the /app directory if it doesn't exist and sets it as the current directory. The COPY instructions now use relative destinations (./src/, ., ./data/), copying files into /app. The final CMD executes python src/train.py assuming /app is the current directory.

Defining the Container's Executable with ENTRYPOINT

The ENTRYPOINT instruction configures a container to run as an executable. It specifies the command that will always be executed when the container starts. Any command-line arguments provided to docker run <image> [arguments] are appended to the ENTRYPOINT command.

ENTRYPOINT is often used when you want the container's primary purpose to be running a specific application or script.

There are two forms:

1. Exec form (Recommended): ENTRYPOINT ["executable", "param1", "param2"]
   • This is the preferred form. It executes the command directly without invoking a command shell. Arguments passed via docker run are appended directly after the specified parameters.
2. Shell form: ENTRYPOINT command param1 param2
   • This form runs the command within a shell (/bin/sh -c). It can be useful for environment variable substitution but might have unexpected behavior with signal handling or if the command contains shell metacharacters.

Example (Exec Form):

Suppose you want your container to always execute Python scripts.

# Dockerfile snippet
# ... (FROM, WORKDIR, COPY, etc.)

ENTRYPOINT ["python"]

# Default script to run if no arguments are provided to docker run
CMD ["src/train.py"]

When you run this container:

• docker run my-ml-image: Executes python src/train.py (the CMD provides the default argument to the ENTRYPOINT).
• docker run my-ml-image src/predict.py --model /app/models/model.pkl: Executes python src/predict.py --model /app/models/model.pkl (the arguments provided override the CMD and are appended to the ENTRYPOINT).

The ENTRYPOINT ensures python is always the main command, making the container act like a dedicated Python script runner.

Providing Default Commands or Arguments with CMD

The CMD instruction provides defaults for an executing container. These defaults can include an executable, but they are often used to specify default parameters for an ENTRYPOINT. If used without an ENTRYPOINT, CMD specifies the default command to run.

Crucially, the entire CMD instruction is overridden if the user provides arguments to docker run <image> [arguments].

CMD also has two forms:

1. Exec form (Recommended for ENTRYPOINT): CMD ["param1","param2"] (Used as default parameters for ENTRYPOINT)
2. Exec form (Standalone): CMD ["executable","param1","param2"] (Default command if no ENTRYPOINT)
3. Shell form: CMD command param1 param2 (Default command run via /bin/sh -c)

Use Cases:

1. Default arguments for ENTRYPOINT (Most Common Combined Use):

   WORKDIR /app
   COPY src/ ./src/
   ENTRYPOINT ["python", "src/run_experiment.py"]
   # Default parameters if none are provided via 'docker run'
   CMD ["--data", "data/dataset.csv", "--epochs", "10"]
   

   • Running docker run my-ml-image executes: python src/run_experiment.py --data data/dataset.csv --epochs 10
   • Running docker run my-ml-image --data data/other.csv --epochs 20 executes: python src/run_experiment.py --data data/other.csv --epochs 20 (The CMD is completely replaced).

2. Default command (No ENTRYPOINT):

   WORKDIR /app
   COPY src/ ./src/
   # No ENTRYPOINT defined
   CMD ["python", "src/train.py"]
   

   • Running docker run my-ml-image executes: python src/train.py
   • Running docker run my-ml-image python src/predict.py executes: python src/predict.py (The entire default CMD is replaced by the command provided).

Combining ENTRYPOINT and CMD Effectively

The most powerful and common pattern is using ENTRYPOINT to specify the fixed executable (like python or a wrapper script) and CMD to specify the default, overridable arguments (like the script name or default hyperparameters).

Best Practices:

• Use WORKDIR: Always set a WORKDIR to establish a clear execution context within your container. /app is a common convention.
• Prefer the Exec Form: Use the JSON array syntax (["executable", "param1"]) for both ENTRYPOINT and CMD to avoid shell processing quirks and make argument handling explicit.
• ENTRYPOINT for the Executable: If your container is designed to run a specific command or behave like an executable, use ENTRYPOINT. Examples: ENTRYPOINT ["python"], ENTRYPOINT ["./my_inference_server"].
• CMD for Defaults: Use CMD to provide default arguments to the ENTRYPOINT or to specify a default command that is easily overridden. Example: CMD ["my_script.py", "--default-flag"].

By carefully defining WORKDIR, ENTRYPOINT, and CMD, you create Docker images that are not only reproducible environments but also behave predictably and are user-friendly, whether running training jobs or serving models. They define the interface for interacting with your containerized ML application.