def ResNetTiny_FewCombo( c, **kargs ): # resnetWide also used by mixtrain and scaling provable adversarial defenses def wb(c, bias=True, **kargs): return n.WideBlock(c, False, bias=bias, ibp_init=True, batch_norm=False, **kargs) dl = n.DeepLoss cmk = n.CorrMaxK cm2d = n.CorrMaxPool2D cm3d = n.CorrMaxPool3D dec = lambda x: n.DecorrMin(x, num_to_keep=True) return n.Seq( cmk(32), n.Conv(16, 3, padding=1, bias=True, ibp_init=True), dec(8), wb(16), dec(4), wb(32), n.Concretize(), wb(32), wb(32), wb(32), cmk(10), n.FFNN([500, c], bias=True, last_lin=True, ibp_init=True, last_zono=True, **kargs))
def ResNetTiny(c, **kargs): # resnetWide also used by mixtrain and scaling provable adversarial defenses def wb(c, bias = True, **kargs): return n.WideBlock(c, False, bias=bias, ibp_init=True, batch_norm = False, **kargs) return n.Seq(n.Conv(16, 3, padding=1, bias=True, ibp_init = True), wb(16), wb(32), wb(32), wb(32), wb(32), n.FFNN([500, c], bias=True, last_lin=True, ibp_init = True, last_zono = True, **kargs))
def ResNetWong(c, **kargs): return n.Seq( n.Conv(16, 3, padding=1, bias=False), n.WideBlock(16), n.WideBlock(16), n.WideBlock(32, True), n.WideBlock(64, True), n.FFNN([1000, c], ibp_init=True, bias=True, last_lin=True, last_zono=True, **kargs))
def ResNetLarge_LargeCombo(c, **kargs): # resnetWide also used by mixtrain and scaling provable adversarial defenses def wb(c, bias = True, **kargs): return n.WideBlock(c, False, bias=bias, ibp_init=True, batch_norm = False, **kargs) dl = n.DeepLoss cmk = n.CorrMaxK cm2d = n.CorrMaxPool2D cm3d = n.CorrMaxPool3D dec = lambda x: n.DecorrMin(x, num_to_keep = True) return n.Seq(n.Conv(16, 3, padding=1, bias=True, ibp_init = True), cmk(4), wb(16), cmk(4), dec(4), wb(32), cmk(4), dec(4), wb(32), dl(S.Until(1, 0, S.Lin(0.5, 0, 50, 3))), wb(32), cmk(4), dec(4), wb(64), cmk(4), dec(2), wb(64), dl(S.Until(24, S.Lin(0, 0.1, 20, 4), S.Lin(0.1, 0, 50))), wb(64), n.FFNN([1000, c], bias=True, last_lin=True, ibp_init = True, **kargs))
def CharLevelAGSub(c, **kargs): return n.Seq(n.EmbeddingWithSub(64, 64, 3), n.Conv(64, 10, bias=True), n.AvgPool2D(10), n.ReduceToZono(), n.FFNN([64, 64, c], last_lin=True, last_zono=True, **kargs)) #
def WordLevelSST2(c, **kargs): return n.Seq(n.Embedding(1, 300), n.Conv(100, 5, bias=True), n.AvgPool2D(5), n.ReduceToZono(), n.FFNN([c], last_lin=True, last_zono=True, **kargs))