"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)
