min_loss = state['min_loss']
checkpoint_path = state['checkpoint_path']
sess.run(tf.assign(global_step, state['iteration']))
except:
print('[!] no models to checkpoint from..')
# raise
saver = tf.train.Saver(tf.global_variables(), max_to_keep=None)
sess.graph.finalize()
with open('configs/win_client.frrn.yaml') as f:
config = yaml.safe_load(f)
amp = Pipeline(config['pipeline'])
amp.run()
amp.keepalive(block=False)
tip = amp._get_tip_queue()
augmenters = [
# blur images with a sigma between 0 and 3.0
iaa.Noop(),
iaa.GaussianBlur(sigma=(0.5, 2.0)),
iaa.Add((-50.0, 50.0), per_channel=False),
iaa.AdditiveGaussianNoise(loc=0,
scale=(0.07 * 255, 0.07 * 255),
per_channel=False),
iaa.Dropout(p=0.07, per_channel=False),
iaa.CoarseDropout(p=(0.05, 0.15),
size_percent=(0.1, 0.9),
per_channel=False),
iaa.SaltAndPepper(p=(0.05, 0.15), per_channel=False),
iaa.Salt(p=(0.05, 0.15), per_channel=False),
