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)