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configs.py
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import math
FFHQ_default = {
'global': {
'img_size': 256,
'batch_size': 4, # batchsize per GPU. We use 8 GPUs by default so that the effective batchsize for an iteration is 4*8=32
'z_dist': 'gaussian',
},
'optimizer': {
'gen_lr': 2e-5,
'disc_lr': 2e-4,
'betas': (0, 0.9),
'grad_clip': 1.,
},
'process': {
'class': 'Gan3DProcess',
'kwargs': {
'batch_split': 4,
'real_pos_lambda': 15.,
'r1_lambda': 1.,
'pos_lambda': 15.,
}
},
'generator': {
'class': 'GramGenerator',
'kwargs': {
'z_dim': 256,
'img_size': 256,
'h_stddev': 0.3,
'v_stddev': 0.155,
'h_mean': math.pi*0.5,
'v_mean': math.pi*0.5,
'sample_dist': 'gaussian',
},
'representation': {
'class': 'gram',
'kwargs': {
'hidden_dim': 256,
'sigma_clamp_mode': 'softplus',
'rgb_clamp_mode': 'widen_sigmoid',
'hidden_dim_sample': 128,
'layer_num_sample': 3,
'center': (0, 0, -1.5),
'init_radius': 0,
},
},
'renderer': {
'class': 'manifold_renderer',
'kwargs': {
'num_samples': 64,
'num_manifolds': 24,
'levels_start': 23,
'levels_end': 8,
'last_back': False,
'white_back': False,
'background': True,
}
}
},
'discriminator': {
'class': 'GramDiscriminator',
'kwargs': {
'img_size': 256,
}
},
'dataset': {
'class': 'FFHQ',
'kwargs': {
'img_size': 256,
'real_pose': True,
}
},
'camera': {
'fov': 12,
'ray_start': 0.88,
'ray_end': 1.12,
}
}
CATS_default = {
'global': {
'img_size': 256,
'batch_size': 2,
'z_dist': 'gaussian',
},
'optimizer': {
'gen_lr': 2e-5,
'disc_lr': 2e-4,
'betas': (0, 0.9),
'grad_clip': 1.,
},
'process': {
'class': 'Gan3DProcess',
'kwargs': {
'batch_split': 2,
'real_pos_lambda': 30.,
'r1_lambda': 1.,
'pos_lambda': 15.,
}
},
'generator': {
'class': 'GramGenerator',
'kwargs': {
'z_dim': 256,
'img_size': 256,
'h_stddev': 0.3,
'v_stddev': 0.155,
'h_mean': math.pi*0.5,
'v_mean': math.pi*0.5,
'sample_dist': 'gaussian',
},
'representation': {
'class': 'gram',
'kwargs': {
'hidden_dim': 256,
'sigma_clamp_mode': 'softplus',
'rgb_clamp_mode': 'widen_sigmoid',
'hidden_dim_sample': 64,
'layer_num_sample': 3,
'center': (0, 0, -1.5),
'init_radius': 0,
},
},
'renderer': {
'class': 'manifold_renderer',
'kwargs': {
'num_samples': 64,
'num_manifolds': 24,
'levels_start': 23,
'levels_end': 8,
'last_back': False,
'white_back': False,
'background': True,
}
}
},
'discriminator': {
'class': 'GramDiscriminator',
'kwargs': {
'img_size': 256,
}
},
'dataset': {
'class': 'CATS',
'kwargs': {
'img_size': 256,
'real_pose': True,
}
},
'camera': {
'fov': 12,
'ray_start': 0.88,
'ray_end': 1.12,
}
}
CARLA_default = {
'global': {
'img_size': 128,
'batch_size': 4,
'z_dist': 'gaussian',
},
'optimizer': {
'gen_lr': 2e-5,
'disc_lr': 2e-4,
'sampling_network_lr': 2e-6,
'betas': (0, 0.9),
'grad_clip': 0.3,
},
'process': {
'class': 'Gan3DProcess',
'kwargs': {
'batch_split': 4,
'real_pos_lambda': 15.,
'r1_lambda': 1.,
'pos_lambda': 15.,
}
},
'generator': {
'class': 'GramGenerator',
'kwargs': {
'z_dim': 256,
'img_size': 128,
'h_stddev': math.pi,
'v_stddev': math.pi*(42.5/180),
'h_mean': math.pi*0.5,
'v_mean': math.pi*(42.5/180),
'sample_dist': 'spherical_uniform',
},
'representation': {
'class': 'gram',
'kwargs': {
'hidden_dim': 256,
'normalize': 2,
'sigma_clamp_mode': 'softplus',
'rgb_clamp_mode': 'widen_sigmoid',
'hidden_dim_sample': 256,
'layer_num_sample': 3,
'center': (0, 0, 0),
'init_radius': 0,
},
},
'renderer': {
'class': 'manifold_renderer',
'kwargs': {
'num_samples': 64,
'num_manifolds': 48,
'levels_start': 35,
'levels_end': 5,
'delta_alpha': 0.02,
'last_back': False,
'white_back': True,
'background': False,
}
}
},
'discriminator': {
'class': 'GramDiscriminator',
'kwargs': {
'img_size': 128,
}
},
'dataset': {
'class': 'CARLA',
'kwargs': {
'img_size': 128,
'real_pose': True,
}
},
'camera': {
'fov': 30,
'ray_start': 0.7,
'ray_end': 1.3,
}
}
Ear = {
'global': {
'img_size': 64,
'batch_size': 2,
'z_dist': 'gaussian',
},
'optimizer': {
'gen_lr': 2e-5,
'disc_lr': 2e-4,
'betas': (0, 0.9),
'grad_clip': 1.,
},
'process': {
'class': 'Gan3DProcess',
'kwargs': {
'batch_split': 2,
'real_pos_lambda': 30.,
'r1_lambda': 1.,
'pos_lambda': 15.,
}
},
'generator': {
'class': 'GramGenerator',
'kwargs': {
'z_dim': 256,
'img_size': 64,
'h_stddev': 0.3,
'v_stddev': 0.155,
'h_mean': math.pi*0.5,
'v_mean': math.pi*0.5,
'sample_dist': 'gaussian',
},
'representation': {
'class': 'gram',
'kwargs': {
'hidden_dim': 256,
'sigma_clamp_mode': 'softplus',
'rgb_clamp_mode': 'widen_sigmoid',
'hidden_dim_sample': 64,
'layer_num_sample': 3,
'center': (0, 0, -1.5),
'init_radius': 0,
},
},
'renderer': {
'class': 'manifold_renderer',
'kwargs': {
'num_samples': 64,
'num_manifolds': 24,
'levels_start': 23,
'levels_end': 8,
'last_back': False,
'white_back': False,
'background': True,
}
}
},
'discriminator': {
'class': 'GramDiscriminator',
'kwargs': {
'img_size': 64,
}
},
'dataset': {
'class': 'Ear',
'kwargs': {
'img_size': 64,
'real_pose': False,
}
},
'camera': {
'fov': 12,
'ray_start': 0.88,
'ray_end': 1.12,
}
}