diff --git a/backend_react/react_app.py b/backend_react/react_app.py index 76bdac891ab2dd76be174db97f033ddc14b7f106..648c4d25a50bedc0d574458c21933635332dd8a6 100644 --- a/backend_react/react_app.py +++ b/backend_react/react_app.py @@ -24,8 +24,10 @@ import sys sys.path.insert(0, os.path.abspath('..')) # import agents and its functions -from MetaAugment import UCB1_JC_py as UCB1_JC -from MetaAugment import Evo_learner as Evo +from ..MetaAugment import UCB1_JC_py as UCB1_JC +from ..MetaAugment.autoaugment_learners import evo_learner +import MetaAugment.controller_networks as cn +import MetaAugment.autoaugment_learners as aal print('@@@ import successful') # import agents and its functions @@ -158,9 +160,9 @@ def training(): best_q_values = np.array(best_q_values) elif auto_aug_learner == 'Evolutionary Learner': - network = Evo.Learner(fun_num=num_funcs, p_bins=1, m_bins=1, sub_num_pol=1) - child_network = Evo.LeNet() - learner = Evo.Evolutionary_learner(network=network, fun_num=num_funcs, p_bins=1, mag_bins=1, sub_num_pol=1, ds = ds, ds_name=ds_name, exclude_method=exclude_method, child_network=child_network) + network = cn.evo_controller.evo_controller(fun_num=num_funcs, p_bins=1, m_bins=1, sub_num_pol=1) + child_network = aal.evo.LeNet() + learner = aal.evo.evo_learner(network=network, fun_num=num_funcs, p_bins=1, mag_bins=1, sub_num_pol=1, ds = ds, ds_name=ds_name, exclude_method=exclude_method, child_network=child_network) learner.run_instance() elif auto_aug_learner == 'Random Searcher': pass diff --git a/setupProxy.js b/setupProxy.js new file mode 100644 index 0000000000000000000000000000000000000000..0b021257aca377b78503c40a9ccfb0a95197b16b --- /dev/null +++ b/setupProxy.js @@ -0,0 +1,11 @@ +const { createProxyMiddleware } = require('http-proxy-middleware'); + +module.exports = function(app) { + app.use( + '/api', + createProxyMiddleware({ + target: 'http://localhost:3000', + changeOrigin: true, + }) + ); +}; \ No newline at end of file