"tr_cond": 'all_gains', "test_cond": 'all_gains', "n_hid": 500, "n_in": 50, "batch_size": 50, "stim_dur": 25, "delay_dur": 100, "resp_dur": 25, "kappa": 2.0, "spon_rate": 0.1, "tr_max_iter": 25001, "test_max_iter": 2501 } # Build task generators generator, test_generator = build_generators(ExptDict) # Define the input and expected output variable input_var, target_var = T.tensor3s('input', 'target') # Build the model l_out, l_rec = build_model(input_var, ExptDict) # The generated output variable and the loss function if ExptDict["task"]["task_id"] in ['DE1', 'DE2', 'GDE2', 'VDE1', 'SINE']: pred_var = lasagne.layers.get_output(l_out) elif ExptDict["task"]["task_id"] in [ 'CD1', 'CD2', 'Harvey2012', 'Harvey2012Dynamic', 'Harvey2016', 'COMP' ]: pred_var = T.clip(lasagne.layers.get_output(l_out), 1e-6, 1.0 - 1e-6)
"tr_cond": 'all_gains', "test_cond": 'all_gains', "n_hid": 500, "n_in": 50, "batch_size": 50, "stim_dur": 25, "delay_dur": 100, "resp_dur": 25, "kappa": 2.0, "spon_rate": 0.1, "tr_max_iter": 25001, "test_max_iter": 2501 } # Build task generators generator_first, test_generator_first = build_generators(ExptDict) # Define the input and expected output variable input_var, target_var = T.tensor3s('input', 'target') # Build the model l_out, l_rec = build_model(input_var, ExptDict) # The generated output variable and the loss function if ExptDict["task"]["task_id"] in ['DE1', 'DE2', 'GDE2', 'VDE1', 'SINE']: pred_var = lasagne.layers.get_output(l_out) elif ExptDict["task"]["task_id"] in [ 'CD1', 'CD2', 'Harvey2012', 'Harvey2012Dynamic', 'Harvey2016', 'COMP' ]: pred_var = T.clip(lasagne.layers.get_output(l_out), 1e-6, 1.0 - 1e-6)