print(
'====================================Revovering Model===================================='
)
ckpt = None
if FLAGS.last_ckpt is not None:
ckpt = tf.train.latest_checkpoint(FLAGS.last_ckpt)
if ckpt is not None:
# set up save configuration
eval_loader.restore(eval_session, ckpt)
print('Recovering From {}'.format(ckpt))
elif FLAGS.pretrained_ckpts is not None:
print('No previous Model Found in {}'.format(ckpt))
# pre-train priority higher
with eval_graph.as_default():
eval_session.run(tf.global_variables_initializer())
partial_restore_op = partial_restore(tf.global_variables(),
FLAGS.pretrained_ckpts)
eval_session.run(partial_restore_op)
print('Recovering From Pretrained Model {}'.format(FLAGS.pretrained_ckpts))
else:
print('Training From Scartch TvT')
with eval_graph.as_default():
eval_session.run(tf.global_variables_initializer())
print(
'====================================RUNNING!===================================='
)
try:
print(
"====================================Start of Eval=============================================="
)
with eval_graph.as_default():
# for i in (tf.global_variables()):
# print(i.name)
if __name__ == '__main__':
sess = tf.Session()
# inputs = tf.placeholder(name='inputs', shape=[16, 224, 224, 3], dtype=tf.float32)
# inputs = tf.random_uniform((1, 224, 224, 3),dtype=tf.float32)
inputs = tf.placeholder(shape=[1, 224, 224, 3],
dtype=tf.float32,
name='inputs')
# in_array = sess.run(tf.Print(inputs,[inputs]))
# np.save("input.npy",in_array)
# np.savetxt("input.txt",in_array.reshape(224*224,3))
with arg_scope(mobilenet_v1_arg_scope()):
nets, end_points = mobilenet_v1(inputs)
partial_restore_op = partial_restore(
sess, tf.global_variables(),
'/mnt/disk/jiabao/mobilenet_v1_1/mobilenet_v1_1.0_224.ckpt')
sess.run(partial_restore_op)
out_array = sess.run(nets, feed_dict={inputs: np.load('input.npy')})
print(np.mean(out_array), np.var(out_array))
np.savetxt("output_1.txt", out_array)
print('=' * 8)
# sess.run(partial_restore_op)
# print('Recovering From Pretrained Model ')
sess.run(tf.global_variables_initializer())
saver = tf.train.Saver()
saver.restore(
sess=sess,
save_path='/mnt/disk/jiabao/mobilenet_v1_1/mobilenet_v1_1.0_224.ckpt')