def build_model(self):
print('Building Test Network')
with tf.variable_scope('network') as scope:
self.train_model = None
self.model = self.model(self.args)
self.model.build()
calculate_flops()
def build_model(self):
if self.mode == 'train' or self.mode == 'overfit': # validation phase
with tf.variable_scope('network') as scope:
self.model = self.model(self.args)
self.model.build()
# print('Building Train Network')
# with tf.variable_scope('network') as scope:
# self.train_model = self.model(self.args, phase=0)
# self.train_model.build()
#
# print('Building Test Network')
# with tf.variable_scope('network') as scope:
# scope.reuse_variables()
# self.test_model = self.model(self.args, phase=1)
# self.test_model.build()
else: # inference phase
print('Building Test Network')
with tf.variable_scope('network') as scope:
self.train_model = None
self.model = self.model(self.args)
self.model.build()
calculate_flops()
def build_model(self):
if self.operator.name == 'Train':
with tf.variable_scope('network') as scope:
self.model = self.model(self.args)
self.model.build()
# print('Building Train Network')
# with tf.variable_scope('network') as scope:
# self.train_model = self.model(self.args, phase=0)
# self.train_model.build()
#
# print('Building Test Network')
# with tf.variable_scope('network') as scope:
# scope.reuse_variables()
# self.test_model = self.model(self.args, phase=1)
# self.test_model.build()
else: # inference phase
print('Building Test Network')
with tf.variable_scope('network') as scope:
# self.train_model = None
self.model = self.model(self.args)
self.model.build()
calculate_flops()