def __init__(self, input_shape, output_shape, owner_name=""):
super(FCNet, self).__init__(input_shape, output_shape, owner_name)
x = input_shape
self.model = nn.Sequential(BaseN.Flatten(),
nn.Linear(np.prod(x), 1024), nn.Softplus(),
nn.Linear(1024, 512), nn.Tanh(),
nn.Linear(512, 256),
BaseN.EigenLayer(256, self.output_shape[0]))
self.compile()
def __init__(self, input_shape, output_shape, **kwargs):
super(ConvNetMNIST, self).__init__(**kwargs)
self.n = output_shape
self.conv = [BaseN.ResNetBlock(1, 32), BaseN.conv3_2(32, 64)]
x = BaseN.output_shape(self.conv[0], input_shape)
self.model = nn.Sequential(self.conv[0], nn.Softplus(),
BaseN.Flatten(), nn.Linear(np.prod(x), 512),
nn.Linear(512, 256), nn.Tanh(),
BaseN.EigenLayer(256, self.output_shape[0]))
self.compile()
def __init__(self, input_shape, output_shape, owner_name=""):
super(FCSpectralMNet, self).__init__(input_shape, output_shape,
owner_name)
x = input_shape
self.model = nn.Sequential(BaseN.Flatten(),
nn.Linear(np.prod(x), 1024), nn.ReLU(),
nn.Linear(1024, 1024), nn.ReLU(),
nn.Linear(1024, 512), nn.ReLU(),
nn.Linear(512, self.output_shape[0] - 1),
nn.Tanh(), BaseN.EigenLayer())
self.compile()
def __init__(self, input_shape, output_shape, owner_name=""):
super(ConvNet, self).__init__(input_shape, output_shape, owner_name)
self.conv = [
nn.Sequential(BaseN.conv3_2(input_shape[0], 8), nn.ReLU(),
BaseN.conv3_2(8, 16), nn.ReLU(), BaseN.conv3_2(8, 8))
]
x = BaseN.output_shape(self.conv[0], input_shape)
self.model = nn.Sequential(
self.conv[0], BaseN.Flatten(), nn.Linear(np.prod(x), 512),
BaseN.AdaptiveTanh(), nn.Linear(512, 256),
BaseN.EigenLayer(256, self.output_shape[0], bias=False))
self.compile()
def __init__(self, input_shape, output_shape, owner_name=""):
super(ConvNetBigAtari, self).__init__(input_shape, output_shape,
owner_name)
self.conv = [
nn.Sequential(BaseN.conv3_2(input_shape[0], 8), nn.Softplus(),
BaseN.conv3_2(8, 16), BaseN.conv3_2(16, 32))
]
x = BaseN.output_shape(self.conv[0], input_shape)
self.model = nn.Sequential(
self.conv[0], BaseN.Flatten(), nn.Linear(np.prod(x), 512),
nn.Linear(512, 512), nn.Tanh(), nn.Linear(512, 1024),
BaseN.EigenLayer(1024, self.output_shape[0]))
self.compile()