prep for adversarial learning in soundstream

import math

import torch

import torch.nn.functional as F

from torch import nn, einsum

import torch.nn.functional as F

from einops import rearrange

from vector_quantize_pytorch import ResidualVQ

def exists(val):

    return val is not None

# gan losses

def hinge_discr_loss(fake, real):

    return (F.relu(1 + fake) + F.relu(1 - real)).mean()

def hinge_gen_loss(fake):

    return -fake.mean()

# sound stream

class Residual(nn.Module):