def quantile(x, q, axis=None, method="linear", keepdims=False):
    """Compute the q-th quantile(s) of the data along the specified axis.

    Args:
        x: Input tensor.
        q: Probability or sequence of probabilities for the quantiles to
            compute. Values must be between 0 and 1 inclusive.
        axis: Axis or axes along which the quantiles are computed. Defaults to
            `axis=None` which is to compute the quantile(s) along a flattened
            version of the array.
        method: A string specifies the method to use for estimating the
            quantile. Available methods are `"linear"`, `"lower"`, `"higher"`,
            `"midpoint"`, and `"nearest"`. Defaults to `"linear"`.
            If the desired quantile lies between two data points `i < j`:
            - `"linear"`: `i + (j - i) * fraction`, where fraction is the
                fractional part of the index surrounded by `i` and `j`.
            - `"lower"`: `i`.
            - `"higher"`: `j`.
            - `"midpoint"`: `(i + j) / 2`
            - `"nearest"`: `i` or `j`, whichever is nearest.
        keepdims: If this is set to `True`, the axes which are reduce
            are left in the result as dimensions with size one.

    Returns:
        The quantile(s). If `q` is a single probability and `axis=None`, then
        the result is a scalar. If multiple probabilities levels are given,
        first axis of the result corresponds to the quantiles. The other axes
        are the axes that remain after the reduction of `x`.
    """
    if any_symbolic_tensors((x, q)):
        return Quantile(
            axis=axis, method=method, keepdims=keepdims
        ).symbolic_call(x, q)
    return backend.numpy.quantile(
        x, q, axis=axis, method=method, keepdims=keepdims
    )
Compute the q-th quantile(s) of the data along the specified axis.

    Args:
        x: Input tensor.
        q: Probability or sequence of probabilities for the quantiles to
            compute. Values must be between 0 and 1 inclusive.
        axis: Axis or axes along which the quantiles are computed. Defaults to
            `axis=None` which is to compute the quantile(s) along a flattened
            version of the array.
        method: A string specifies the method to use for estimating the
            quantile. Available methods are `"linear"`, `"lower"`, `"higher"`,
            `"midpoint"`, and `"nearest"`. Defaults to `"linear"`.
            If the desired quantile lies between two data points `i < j`:
            - `"linear"`: `i + (j - i) * fraction`, where fraction is the
                fractional part of the index surrounded by `i` and `j`.
            - `"lower"`: `i`.
            - `"higher"`: `j`.
            - `"midpoint"`: `(i + j) / 2`
            - `"nearest"`: `i` or `j`, whichever is nearest.
        keepdims: If this is set to `True`, the axes which are reduce
            are left in the result as dimensions with size one.

    Returns:
        The quantile(s). If `q` is a single probability and `axis=None`, then
        the result is a scalar. If multiple probabilities levels are given,
        first axis of the result corresponds to the quantiles. The other axes
        are the axes that remain after the reduction of `x`.
    
keras/src/ops/numpy.py