def main(args):
# create an input placeholder used by the challenge
w = TinyImageNetPipeline.img_width
h = TinyImageNetPipeline.img_height
c = TinyImageNetPipeline.img_channels
sess = tf.Session()
with sess.as_default():
images = tf.placeholder(tf.float32, (None, w, h, c), name="images")
model = SubmittableResNet(x=images)
foolbox_model = model.get_foolbox_model()
model_server(foolbox_model)
def main():
images, logits = create_test_model()
fmodel = foolbox.models.TensorFlowModel(images, logits, (0, 255))
model_server(fmodel)
from fmodel import create_fmodel
from adversarial_vision_challenge import model_server
if __name__ == '__main__':
fmodel = create_fmodel()
model_server(fmodel)
def main():
model = Model()
model_server(model)
from adversarial_vision_challenge import model_server
import vgg19
if __name__ == '__main__':
model = vgg19.Vgg19([122.46267559570313 114.25840612792969 101.3746757055664],'./models/vgg19-pre.npy')
model_server(model)