def training_from_flag(flags):
"""
Training interface. 1. Read data 2. initialize network 3. train network 4. record flags
:param flag: The training flags read from command line or parameter.py
:return: None
"""
if flags.use_cpu_only:
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
# Get the data
train_loader, test_loader = data_reader.read_data(flags)
# Reset the boundary is normalized
if flags.normalize_input:
flags.geoboundary_norm = [-1, 1, -1, 1]
print("Boundary is set at:", flags.geoboundary)
print("Making network now")
# Make Network
ntwk = Network(Forward, flags, train_loader, test_loader)
# Training process
print("Start training now...")
ntwk.train()
# Do the house keeping, write the parameters and put into folder, also use pickle to save the flags obejct
write_flags_and_BVE(flags, ntwk.best_validation_loss, ntwk.ckpt_dir)
def training_from_flag(flags):
"""
Training interface. 1. Read data 2. initialize network 3. train network 4. record flags
:param flag: The training flags read from command line or parameter.py
:return: None
"""
# Get the data
train_loader, test_loader = data_reader.read_data(flags)
print("Making network now")
# Make Network
ntwk = Network(VAE, flags, train_loader, test_loader)
# Training process
print("Start training now...")
ntwk.train()
# Do the house keeping, write the parameters and put into folder, also use pickle to save the flags obejct
write_flags_and_BVE(flags, ntwk.best_validation_loss, ntwk.ckpt_dir)
