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)
