[INPUT_SEPARATOR]
First, create a Cython helper module for distance calculations.
```python
edit
file: solver.pylines: 0-0
---
import numpy as np
from scipy.interpolate import RBFInterpolator

class Solver:
    def solve(self, problem):
        # Unpack training and test data
        x_train = np.asarray(problem["x_train"], dtype=float)
        y_train = np.asarray(problem["y_train"], dtype=float).ravel()
        x_test = np.asarray(problem["x_test"], dtype=float)

        # Get RBF configuration
        cfg = problem.get("rbf_config", {})
        kernel = cfg.get("kernel", "thin_plate_spline")
        epsilon = cfg.get("epsilon", 1.0)
        smoothing = cfg.get("smoothing", 0.0)

        # Build and evaluate the interpolator
        rbf = RBFInterpolator(
            x_train, y_train,
            kernel=kernel,
            epsilon=epsilon,
            smoothing=smoothing
        )
        y_pred = rbf(x_test)

        return {
            "y_pred": y_pred.tolist()
        }
---
```
[INPUT_SEPARATOR]
First, create a Cython helper module for distance calculations.
```python
edit
file: solver.py
lines: 0-0
---
import numpy as np
from scipy.interpolate import RBFInterpolator

class Solver:
    def solve(self, problem):
        # Unpack training and test data
        x_train = np.asarray(problem["x_train"], dtype=float)
        y_train = np.asarray(problem["y_train"], dtype=float).ravel()
        x_test = np.asarray(problem["x_test"], dtype=float)

        # Get RBF configuration
        cfg = problem.get("rbf_config", {})
        kernel = cfg.get("kernel", "thin_plate_spline")
        epsilon = cfg.get("epsilon", 1.0)
        smoothing = cfg.get("smoothing", 0.0)

        # Build and evaluate the interpolator
        rbf = RBFInterpolator(
            x_train, y_train,
            kernel=kernel,
            epsilon=epsilon,
            smoothing=smoothing
        )
        y_pred = rbf(x_test)

        return {
            "y_pred": y_pred.tolist()
        }
---
```