def __init__(self, out_channels, mid_channels=16): super().__init__() self.mul_net = nn.Sequential( conv2d(0, mid_channels, coords=True), nn.ReLU(), conv2d(mid_channels, out_channels, coords=True)) self.bias_net = nn.Sequential( conv2d(0, mid_channels, coords=True), nn.ReLU(), conv2d(mid_channels, out_channels, coords=True))
def __init__(self,*args,inverse_tol=1e-7,circ=True,**kwargs): super().__init__() self.conv = conv2d(*args,**kwargs) self.inverse_tol = inverse_tol self._reverse_iters = 0 self._inverses_evaluated = 0 self._circ= circ
def __init__(self,out_channels): super().__init__() self.mul_net = conv2d(0,out_channels,coords=True) self.bias_net = self.mul_net = conv2d(0,out_channels,coords=True)