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# Copyright (c) 2025 Quandela
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"""
Automatic differentiation handling for sampling.
"""

import warnings

from ..measurement.process import SamplingProcess


class AutoDiffProcess:
    """Handles automatic differentiation backend and sampling noise integration."""

    def __init__(self, sampling_method: str = "multinomial"):
        self.sampling_noise = SamplingProcess(method=sampling_method)

    def autodiff_backend(
        self, needs_gradient: bool, apply_sampling: bool, shots: int
    ) -> tuple[bool, int]:
        """Determine sampling configuration based on gradient requirements."""
        if needs_gradient and (apply_sampling or shots > 0):
            warnings.warn(
                "Sampling was requested but is disabled because gradients are being computed. "
                "Sampling during gradient computation would lead to incorrect gradients.",
                category=UserWarning,
                stacklevel=1,
            )
            return False, 0
        return apply_sampling, shots
