Feat/mlx kernel optimization

.github/workflows/release.yml

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+name: Upload Python Package and Docker Image on Release
+on:
+  release:
+    types: [created]
+
+jobs:
+  pypi-publish:
+    name: Publish release to PyPI
+    runs-on: ubuntu-latest
+    environment:
+      name: pypi
+      url: https://pypi.org/p/openevolve
+    permissions:
+      id-token: write
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.x"
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install build
+      - name: Build package
+        run: |
+          python -m build
+      - name: Publish package distributions to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+
+  docker-publish:
+    name: Publish Docker image
+    runs-on: ubuntu-22.04
+    needs: pypi-publish
+    permissions:
+      contents: read
+      packages: write
+    steps:
+      - uses: actions/checkout@v4
+
+      # Add aggressive cleanup before any Docker operations
+      - name: Free disk space
+        run: |
+          # Clean Docker
+          docker system prune -af
+          docker image prune -af
+          docker builder prune -af
+
+          df -h
+
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+        with:
+          driver-opts: |
+            image=moby/buildkit:buildx-stable-1
+            network=host
+          buildkitd-flags: --debug
+
+      - name: Log in to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      # Extract metadata for Docker image
+      - name: Extract metadata for Docker
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: ghcr.io/${{ github.repository }}
+          tags: |
+            type=semver,pattern={{version}}
+            type=semver,pattern={{major}}.{{minor}}
+            type=raw,value=latest
+
+      # Build and push Docker image for AMD64
+      - name: Build and push Docker image AMD64
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: Dockerfile
+          push: true
+          platforms: linux/amd64
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          cache-from: type=gha,scope=openevolve-amd64
+          cache-to: type=gha,scope=openevolve-amd64,mode=max
+          outputs: type=registry,compression=zstd,compression-level=5
+
+      # Cleanup after AMD64 build
+      - name: Cleanup after AMD64 build
+        run: |
+          docker system prune -af
+          docker builder prune -af
+          df -h
+
+      # Build and push Docker image for ARM64
+      - name: Build and push Docker image ARM64
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: Dockerfile
+          push: true
+          platforms: linux/arm64
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          cache-from: type=gha,scope=openevolve-arm64
+          cache-to: type=gha,scope=openevolve-arm64,mode=max
+          outputs: type=registry,compression=zstd,compression-level=5
+
+      # Final cleanup
+      - name: Final cleanup
+        run: |
+          docker system prune -af
+          docker builder prune -af
+          find /tmp -type f -user $(id -u) -exec rm -f {} + 2>/dev/null || true
+          df -h

examples/circle_packing/best_program.py

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+# EVOLVE-BLOCK-START
+"""Advanced circle packing for n=26 circles in a unit square"""
+import numpy as np
+from scipy.optimize import minimize
+
+
+def construct_packing():
+    """
+    Construct an optimized arrangement of 26 circles in a unit square
+    using mathematical principles and optimization techniques.
+
+    Returns:
+        Tuple of (centers, radii, sum_of_radii)
+        centers: np.array of shape (26, 2) with (x, y) coordinates
+        radii: np.array of shape (26) with radius of each circle
+        sum_of_radii: Sum of all radii
+    """
+    n = 26
+
+    # Initial guess: Strategic placement with some randomness
+    centers = np.zeros((n, 2))
+    radii = np.zeros(n)
+
+    # Heuristic placement for better initial guess: place larger circles in center
+    radii[:] = np.linspace(0.12, 0.05, n)  # Linear distribution of radii
+
+    # Initial placement: approximate hexagonal grid
+    grid_x = int(np.sqrt(n))
+    grid_y = int(n / grid_x)
+
+    x_coords = np.linspace(0.15, 0.85, grid_x)
+    y_coords = np.linspace(0.15, 0.85, grid_y)
+
+    count = 0
+    for i in range(grid_x):
+        for j in range(grid_y):
+            if count < n:
+                centers[count] = [x_coords[i] + 0.05 * (j % 2), y_coords[j]]
+                count += 1
+
+    # Place remaining circles randomly
+    while count < n:
+        centers[count] = np.random.rand(2) * 0.7 + 0.15
+        count += 1
+
+    # Objective function: Negative sum of radii (to maximize)
+    def objective(x):
+        centers = x[: 2 * n].reshape(n, 2)
+        radii = x[2 * n :]
+        return -np.sum(radii)
+
+    # Constraint: No overlaps and circles stay within the unit square
+    def constraint(x):
+        centers = x[: 2 * n].reshape(n, 2)
+        radii = x[2 * n :]
+
+        # Overlap constraint
+        overlap_constraints = []
+        for i in range(n):
+            for j in range(i + 1, n):
+                dist = np.sqrt(np.sum((centers[i] - centers[j]) ** 2))
+                overlap_constraints.append(dist - (radii[i] + radii[j]))
+
+        # Boundary constraints
+        boundary_constraints = []
+        for i in range(n):
+            boundary_constraints.append(centers[i, 0] - radii[i])  # x >= radius
+            boundary_constraints.append(1 - centers[i, 0] - radii[i])  # x <= 1 - radius
+            boundary_constraints.append(centers[i, 1] - radii[i])  # y >= radius
+            boundary_constraints.append(1 - centers[i, 1] - radii[i])  # y <= 1 - radius
+
+        return np.array(overlap_constraints + boundary_constraints)
+
+    # Initial guess vector
+    x0 = np.concatenate([centers.flatten(), radii])
+
+    # Bounds: Circles stay within the unit square and radii are positive
+    bounds = [(0, 1)] * (2 * n) + [(0.03, 0.2)] * n  # radii are positive, up to 0.2
+
+    # Constraints dictionary
+    constraints = {"type": "ineq", "fun": constraint}
+
+    # Optimization using SLSQP
+    result = minimize(
+        objective,
+        x0,
+        method="SLSQP",
+        bounds=bounds,
+        constraints=constraints,
+        options={"maxiter": 1000, "ftol": 1e-8},
+    )
+
+    # Extract optimized centers and radii
+    optimized_centers = result.x[: 2 * n].reshape(n, 2)
+    optimized_radii = result.x[2 * n :]
+
+    # Ensure radii are not negative (numerical stability)
+    optimized_radii = np.maximum(optimized_radii, 0.001)
+
+    # Calculate the sum of radii
+    sum_radii = np.sum(optimized_radii)
+
+    return optimized_centers, optimized_radii, sum_radii
+
+
+# EVOLVE-BLOCK-END
+
+
+# This part remains fixed (not evolved)
+def run_packing():
+    """Run the circle packing constructor for n=26"""
+    centers, radii, sum_radii = construct_packing()
+    return centers, radii, sum_radii
+
+
+def visualize(centers, radii):
+    """
+    Visualize the circle packing
+
+    Args:
+        centers: np.array of shape (n, 2) with (x, y) coordinates
+        radii: np.array of shape (n) with radius of each circle
+    """
+    import matplotlib.pyplot as plt
+    from matplotlib.patches import Circle
+
+    fig, ax = plt.subplots(figsize=(8, 8))
+
+    # Draw unit square
+    ax.set_xlim(0, 1)
+    ax.set_ylim(0, 1)
+    ax.set_aspect("equal")
+    ax.grid(True)
+
+    # Draw circles
+    for i, (center, radius) in enumerate(zip(centers, radii)):
+        circle = Circle(center, radius, alpha=0.5)
+        ax.add_patch(circle)
+        ax.text(center[0], center[1], str(i), ha="center", va="center")
+
+    plt.title(f"Circle Packing (n={len(centers)}, sum={sum(radii):.6f})")
+    plt.show()
+
+
+if __name__ == "__main__":
+    centers, radii, sum_radii = run_packing()
+    print(f"Sum of radii: {sum_radii}")
+    # AlphaEvolve improved this to 2.635
+
+    # Uncomment to visualize:
+    # visualize(centers, radii)

examples/circle_packing/best_program_info.json

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+{
+  "id": "f6cbff44-9b16-4e6c-af58-b10b6625621a",
+  "generation": 10,
+  "iteration": 0,
+  "timestamp": 1747709506.546607,
+  "parent_id": "b7f51a09-7ba5-4cdb-bc15-9c431ec8885f",
+  "metrics": {
+    "validity": 1.0,
+    "sum_radii": 2.634292402141039,
+    "target_ratio": 0.9997314619131079,
+    "combined_score": 0.9997314619131079,
+    "eval_time": 0.6134955883026123
+  },
+  "language": "python",
+  "saved_at": 1748016967.553278
+}