def any(x, axis=None, keepdims=False):
    """Test whether any array element along a given axis evaluates to `True`.

    Args:
        x: Input tensor.
        axis: An integer or tuple of integers that represent the axis along
            which a logical OR reduction is performed. The default
            (`axis=None`) is to perform a logical OR over all the dimensions
            of the input array. `axis` may be negative, in which case it counts
            for the last to the first axis.
        keepdims: If `True`, axes which are reduced are left in the result as
            dimensions with size one. With this option, the result will
            broadcast correctly against the input array. Defaults to `False`.

    Returns:
        The tensor containing the logical OR reduction over the `axis`.

    Examples:
    >>> x = keras.ops.convert_to_tensor([True, False])
    >>> keras.ops.any(x)
    array(True, shape=(), dtype=bool)

    >>> x = keras.ops.convert_to_tensor([[True, False], [True, True]])
    >>> keras.ops.any(x, axis=0)
    array([ True  True], shape=(2,), dtype=bool)

    `keepdims=True` outputs a tensor with dimensions reduced to one.
    >>> x = keras.ops.convert_to_tensor([[True, False], [True, True]])
    >>> keras.ops.all(x, keepdims=True)
    array([[False]], shape=(1, 1), dtype=bool)
    """
    if any_symbolic_tensors((x,)):
        return Any(axis=axis, keepdims=keepdims).symbolic_call(x)
    return backend.numpy.any(x, axis=axis, keepdims=keepdims)
Test whether any array element along a given axis evaluates to `True`.

    Args:
        x: Input tensor.
        axis: An integer or tuple of integers that represent the axis along
            which a logical OR reduction is performed. The default
            (`axis=None`) is to perform a logical OR over all the dimensions
            of the input array. `axis` may be negative, in which case it counts
            for the last to the first axis.
        keepdims: If `True`, axes which are reduced are left in the result as
            dimensions with size one. With this option, the result will
            broadcast correctly against the input array. Defaults to `False`.

    Returns:
        The tensor containing the logical OR reduction over the `axis`.

    Examples:
    >>> x = keras.ops.convert_to_tensor([True, False])
    >>> keras.ops.any(x)
    array(True, shape=(), dtype=bool)

    >>> x = keras.ops.convert_to_tensor([[True, False], [True, True]])
    >>> keras.ops.any(x, axis=0)
    array([ True  True], shape=(2,), dtype=bool)

    `keepdims=True` outputs a tensor with dimensions reduced to one.
    >>> x = keras.ops.convert_to_tensor([[True, False], [True, True]])
    >>> keras.ops.all(x, keepdims=True)
    array([[False]], shape=(1, 1), dtype=bool)
    
keras/src/ops/numpy.py