def sample(
        self, axes: Sequence[int], repetitions: int = 1, seed: cirq.RANDOM_STATE_OR_SEED_LIKE = None
    ) -> np.ndarray:
        """Samples the state. Subclasses can override with more performant method.

        Args:
            axes: The axes to sample.
            repetitions: The number of samples to make.
            seed: The random number seed to use.
        Returns:
            The samples in order.
        """
        prng = value.parse_random_state(seed)
        measurements = []
        for _ in range(repetitions):
            state = self.copy()
            measurements.append(state.measure(axes, prng))
        return np.array(measurements, dtype=np.uint8)
Samples the state. Subclasses can override with more performant method.

        Args:
            axes: The axes to sample.
            repetitions: The number of samples to make.
            seed: The random number seed to use.
        Returns:
            The samples in order.
        
cirq-core/cirq/qis/quantum_state_representation.py