def __init__(self, dim=3, c_dim=128, unet=False, unet_kwargs=None, unet3d=False, unet3d_kwargs=None,
plane_resolution=512, grid_resolution=None, plane_type='xz', kernel_size=3, padding=0.1):
super().__init__()
self.actvn = F.relu
if kernel_size == 1:
self.conv_in = nn.Conv3d(1, c_dim, 1)
else:
self.conv_in = nn.Conv3d(1, c_dim, kernel_size, padding=1)
if unet:
self.unet = UNet(c_dim, in_channels=c_dim, **unet_kwargs)
else:
self.unet = None
if unet3d:
self.unet3d = UNet3D(**unet3d_kwargs)
else:
self.unet3d = None
self.c_dim = c_dim
self.reso_plane = plane_resolution
self.reso_grid = grid_resolution
self.plane_type = plane_type
self.padding = padding
def __init__(self,
c_dim=128,
dim=3,
hidden_dim=128,
scatter_type='max',
unet=False,
unet_kwargs=None,
plane_resolution=None,
grid_resolution=None,
plane_type='xz',
padding=0.1,
n_blocks=5,
pos_encoding=False,
n_channels=3,
plane_net='FCPlanenet'):
super().__init__()
self.c_dim = c_dim
self.num_channels = n_channels
if pos_encoding == True:
dim = 60
self.fc_pos = nn.Linear(dim, 2 * hidden_dim)
self.blocks = nn.ModuleList([
ResnetBlockFC(2 * hidden_dim, hidden_dim) for i in range(n_blocks)
])
self.fc_c = nn.Linear(hidden_dim, c_dim)
planenet_hidden_dim = hidden_dim
self.fc_plane_net = FCPlanenet(n_dim=dim, hidden_dim=hidden_dim)
# Create FC layers based on the number of planes
self.plane_params = nn.ModuleList(
[nn.Linear(planenet_hidden_dim, 3) for i in range(n_channels)])
self.plane_params_hdim = nn.ModuleList(
[nn.Linear(3, hidden_dim) for i in range(n_channels)])
self.actvn = nn.ReLU()
self.hidden_dim = hidden_dim
if unet:
self.unet = UNet(c_dim, in_channels=c_dim, **unet_kwargs)
else:
self.unet = None
self.reso_plane = plane_resolution
self.reso_grid = grid_resolution
self.plane_type = plane_type
self.padding = padding
if scatter_type == 'max':
self.scatter = scatter_max
elif scatter_type == 'mean':
self.scatter = scatter_mean
else:
raise ValueError('incorrect scatter type')
self.pos_encoding = pos_encoding
if pos_encoding:
self.pe = positional_encoding()
def __init__(self,
c_dim=128,
dim=3,
hidden_dim=128,
scatter_type='max',
unet=False,
unet_kwargs=None,
unet3d=False,
unet3d_kwargs=None,
plane_resolution=None,
grid_resolution=None,
plane_type='xz',
padding=0.1,
n_blocks=5,
local_coord=False,
pos_encoding='linear',
unit_size=0.1):
super().__init__()
self.c_dim = c_dim
self.blocks = nn.ModuleList([
ResnetBlockFC(2 * hidden_dim, hidden_dim) for i in range(n_blocks)
])
self.fc_c = nn.Linear(hidden_dim, c_dim)
self.actvn = nn.ReLU()
self.hidden_dim = hidden_dim
self.reso_plane = plane_resolution
self.reso_grid = grid_resolution
self.plane_type = plane_type
self.padding = padding
if unet:
self.unet = UNet(c_dim, in_channels=c_dim, **unet_kwargs)
else:
self.unet = None
if unet3d:
self.unet3d = UNet3D(**unet3d_kwargs)
else:
self.unet3d = None
if scatter_type == 'max':
self.scatter = scatter_max
elif scatter_type == 'mean':
self.scatter = scatter_mean
else:
raise ValueError('incorrect scatter type')
if local_coord:
self.map2local = map2local(unit_size, pos_encoding=pos_encoding)
else:
self.map2local = None
if pos_encoding == 'sin_cos':
self.fc_pos = nn.Linear(60, 2 * hidden_dim)
else:
self.fc_pos = nn.Linear(dim, 2 * hidden_dim)
def __init__(self,
c_dim=128,
dim=3,
hidden_dim=128,
scatter_type='max',
unet=False,
unet_kwargs=None,
unet3d=False,
unet3d_kwargs=None,
plane_resolution=None,
grid_resolution=None,
plane_type='xz',
padding=0.1,
n_blocks=5,
pos_encoding=False):
super().__init__()
self.c_dim = c_dim
if pos_encoding == True:
dim = 60
self.fc_pos = nn.Linear(dim, 2 * hidden_dim)
self.blocks = nn.ModuleList([
ResnetBlockFC(2 * hidden_dim, hidden_dim) for i in range(n_blocks)
])
self.fc_c = nn.Linear(hidden_dim, c_dim)
self.actvn = nn.ReLU()
self.hidden_dim = hidden_dim
if unet:
self.unet = UNet(c_dim, in_channels=c_dim, **unet_kwargs)
else:
self.unet = None
if unet3d:
#self.unet3d = UNet3D(**unet3d_kwargs)
self.unet3d = UNet3D_latent(**unet3d_kwargs)
else:
self.unet3d = None
self.reso_plane = plane_resolution
self.reso_grid = grid_resolution
self.plane_type = plane_type
self.padding = padding
if scatter_type == 'max':
self.scatter = scatter_max
elif scatter_type == 'mean':
self.scatter = scatter_mean
else:
raise ValueError('incorrect scatter type')
self.pos_encoding = pos_encoding
if pos_encoding:
self.pe = positional_encoding()