def __init__(self, option, model_type, dataset, modules):
BackboneBasedModel.__init__(self, option, model_type, dataset, modules)
# Last MLP
last_mlp_opt = option.mlp_cls
self._dim_output = last_mlp_opt.nn[-1]
self.FC_layer = Seq()
for i in range(1, len(last_mlp_opt.nn)):
self.FC_layer.append(Conv1D(last_mlp_opt.nn[i - 1], last_mlp_opt.nn[i], bn=True, bias=False))
self.loss_names = ["loss_patch_desc"]
def __init__(self, option, model_type, dataset, modules):
BackboneBasedModel.__init__(self, option, model_type, dataset, modules)
# Last MLP
last_mlp_opt = option.mlp_cls
self._dim_output = last_mlp_opt.nn[-1]
self.FC_layer = pt_utils.Seq(last_mlp_opt.nn[0])
for i in range(1, len(last_mlp_opt.nn)):
self.FC_layer.conv1d(last_mlp_opt.nn[i], bn=True)
self.loss_names = ["loss_patch_desc"]
def __init__(self, option, model_type, dataset, modules):
"""
Initialize this model class
Parameters:
opt -- training/test options
A few things can be done here.
- (required) call the initialization function of BaseModel
- define loss function, visualization images, model names, and optimizers
"""
BackboneBasedModel.__init__(self, option, model_type, dataset, modules)
self.set_last_mlp(option.mlp_cls)
self.loss_names = ["loss_reg"]
def __init__(self, option, model_type, dataset, modules):
BackboneBasedModel.__init__(self, option, model_type, dataset, modules)
self.set_last_mlp(option.mlp_cls)
self.loss_names = ["loss_reg", "loss", "internal"]