def create_mlp_model(hyper_params): n_in=hyper_params['n_in'] n_hidden=hyper_params['n_hidden'] n_out=hyper_params['n_out'] rand=ml_tools.RandomNum() hidden=ml_tools.create_layer((n_in,n_hidden),rand) logistic=ml_tools.create_layer((n_hidden,n_out),rand) return MlpModel(hidden,logistic)
def built_logit_cls(shape=(3200,20)): free_vars=ml_tools.FlatImages() model=ml_tools.create_layer(shape) train,test=create_cls_fun(free_vars,model) return ml_tools.Classifier(free_vars,model,train,test)