Add Docker support and fix benchmark/data pipeline bugs

Containerize the application with ROCm GPU support for AMD Radeon R9700:
- Add Dockerfile with PyTorch/PyG ROCm 5.6 wheels
- Add docker-compose.yml with dashboard, live-trading, and train services
- Add .dockerignore and .env.example for configuration

Fix benchmark script to use batch_size instead of num_stocks for variable
dimensions, and replace fragile partial model surgery with a standalone MLP
for memory estimation.

Fix data pipeline to skip dates with no next trading date instead of
fabricating zero returns.

Add slippage to paper broker, optional mark-to-market prices to broker
interface, and health check endpoint for container orchestration.

docker-compose.yml

@@ -0,0 +1,183 @@
+# =============================================================================
+# StockGNN R9700 — Docker Compose Stack
+# =============================================================================
+# Services:
+#   - dashboard   : FastAPI web frontend (http://localhost:8000)
+#   - live-trading: Continuous paper/live trading engine
+#   - train       : One-off model training & backtesting
+#
+# Requirements:
+#   - Docker 20.10+ with Compose v2
+#   - AMD GPU + ROCm 5.6+ drivers on host
+#   - docker-compose run --rm train   # manual training
+# =============================================================================
+
+services:
+  # -------------------------------------------------------------------------
+  # Base image build (shared by all services)
+  # -------------------------------------------------------------------------
+  dashboard:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    image: stockgnn:r9700
+    container_name: stockgnn-dashboard
+    restart: unless-stopped
+
+    # Override default CMD for the web dashboard
+    command: >
+      python -m uvicorn src.web.app:app
+      --host 0.0.0.0
+      --port 8000
+      --reload
+
+    ports:
+      - "8000:8000"
+
+    volumes:
+      # Persist data & model artefacts across restarts
+      - ./data:/app/data
+      - ./models:/app/models
+      - ./logs:/app/logs
+      # Optional: mount source for live-reload during development
+      # - ./src:/app/src
+
+    env_file:
+      - .env
+
+    environment:
+      # ROCm / AMD GPU tuning
+      HSA_OVERRIDE_GFX_VERSION: "${HSA_OVERRIDE_GFX_VERSION:-10.3.0}"
+      PYTORCH_HIP_ALLOC_CONF: "expandable_segments:True"
+      # Ensure the app knows it is inside a container
+      STOCKGNN_ENV: docker
+
+    # AMD GPU device access
+    devices:
+      - /dev/kfd
+      - /dev/dri
+
+    # Required groups for GPU access inside the container
+    group_add:
+      - video
+      - render
+
+    # Security / capability settings for ROCm
+    security_opt:
+      - seccomp:unconfined
+
+    # Shared memory size for PyTorch DataLoader multiprocessing
+    shm_size: "8gb"
+
+    # Health-check for the web dashboard
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8000/api/dashboard/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 40s
+
+    networks:
+      - stockgnn-net
+
+  # -------------------------------------------------------------------------
+  # Live Trading Engine (paper or live — controlled via config.py)
+  # -------------------------------------------------------------------------
+  live-trading:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    image: stockgnn:r9700
+    container_name: stockgnn-live-trading
+    restart: unless-stopped
+
+    command: >
+      python live_trading.py
+
+    volumes:
+      - ./data:/app/data
+      - ./models:/app/models
+      - ./logs:/app/logs
+
+    env_file:
+      - .env
+
+    environment:
+      HSA_OVERRIDE_GFX_VERSION: "${HSA_OVERRIDE_GFX_VERSION:-10.3.0}"
+      PYTORCH_HIP_ALLOC_CONF: "expandable_segments:True"
+      STOCKGNN_ENV: docker
+
+    devices:
+      - /dev/kfd
+      - /dev/dri
+
+    group_add:
+      - video
+      - render
+
+    security_opt:
+      - seccomp:unconfined
+
+    shm_size: "8gb"
+
+    networks:
+      - stockgnn-net
+
+    # Do not auto-start live trading until the user explicitly brings it up
+    profiles:
+      - live
+
+  # -------------------------------------------------------------------------
+  # Model Training & Backtesting (run manually)
+  # -------------------------------------------------------------------------
+  # Usage:
+  #   docker compose run --rm train
+  # -------------------------------------------------------------------------
+  train:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    image: stockgnn:r9700
+    container_name: stockgnn-train
+
+    command: >
+      python main.py
+
+    volumes:
+      - ./data:/app/data
+      - ./models:/app/models
+      - ./logs:/app/logs
+
+    env_file:
+      - .env
+
+    environment:
+      HSA_OVERRIDE_GFX_VERSION: "${HSA_OVERRIDE_GFX_VERSION:-10.3.0}"
+      PYTORCH_HIP_ALLOC_CONF: "expandable_segments:True"
+      STOCKGNN_ENV: docker
+
+    devices:
+      - /dev/kfd
+      - /dev/dri
+
+    group_add:
+      - video
+      - render
+
+    security_opt:
+      - seccomp:unconfined
+
+    shm_size: "16gb"
+
+    networks:
+      - stockgnn-net
+
+    profiles:
+      - train
+
+# -----------------------------------------------------------------------------
+# Shared network
+# -----------------------------------------------------------------------------
+networks:
+  stockgnn-net:
+    driver: bridge