def equalize3d(input: Tensor) -> Tensor:
    r"""Equalize the values for a 3D volumetric tensor.

    Implements Equalize function for a sequence of images using PyTorch ops based on uint8 format:
    https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/autoaugment.py#L352

    Args:
        input: image tensor with shape :math:`(*, C, D, H, W)` to equalize.

    Returns:
        Equalized volume with shape :math:`(B, C, D, H, W)`.

    """
    res = []
    for volume in input:
        # Assumes RGB for now.  Scales each channel independently
        # and then stacks the result.
        scaled_input = torch.stack([_scale_channel(volume[i, :, :, :]) for i in range(len(volume))])
        res.append(scaled_input)

    return torch.stack(res)
Equalize the values for a 3D volumetric tensor.

    Implements Equalize function for a sequence of images using PyTorch ops based on uint8 format:
    https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/autoaugment.py#L352

    Args:
        input: image tensor with shape :math:`(*, C, D, H, W)` to equalize.

    Returns:
        Equalized volume with shape :math:`(B, C, D, H, W)`.

    
kornia/enhance/adjust.py