Helo there, I have the following code.
a global variable that num_gpu that indicates the number of gpus availavle.
If I can data() or create_mode() separate everything is fine.
But when I call optim.minimize and pass the function, it does not see the global variable and num_gpu becomes undfined.
Am I doing something wrong?
Thanks in advance.
...
from keras import backend as K
from livelossplot import PlotLossesKeras
from hyperas import optim
from hyperas.distributions import choice, uniform
from hyperopt import Trials, STATUS_OK, tpe
# Setup (multi) GPU usage with scalable VRAM
num_gpu = setup_multi_gpus()
def data():
print(num_gpu)
df, train = data_import(possible_columns)
df = prepare_data(df)
...
return X_train, y_train, X_test, y_test
def create_model(X_train, y_train, X_test, y_test):
print(num_gpu)
if __name__ == '__main__':
best_run, best_model = optim.minimize(model=create_model,
data=data,
algo=tpe.suggest,
max_evals=500,
trials=Trials(),
eval_space=True)
X_train, y_train, X_test, y_test = data()
create_model(X_train, y_train, X_test, y_test )
print(num_gpu)
Helo there, I have the following code.
a global variable that num_gpu that indicates the number of gpus availavle.
If I can data() or create_mode() separate everything is fine.
But when I call optim.minimize and pass the function, it does not see the global variable and num_gpu becomes undfined.
Am I doing something wrong?
Thanks in advance.
...