运行 yad2k 以生成模型 h5 文件时，“tensorflow”在 tensorflow 2.3 中没有属性“space_to_depth”错误

Question

I am trying to generate YOLOv2 model yolo.h5 so that I can load this pre-trained model. I am trying to port Andrew Ng coursera Yolo assignment ( which runs in tensorflow 1.x) to tensorflow 2.3.

I was able to cleanly port it thanks to tensorflow uprade ( https://www.tensorflow.org/guide/upgrade ), But little did I realize that I cannot download the yolo.h5 file ( either its get corrupted or the download times out) and therefore I thought I should build one and I followed instructions from https://github.com/JudasDie/deeplearning.ai/issues/2 . It looked pretty straight forward as I cloned YAD2k repo and downloaded both the yolo.weights and yolo.cfg. I ran the following the command as per the instructions:

python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5

But I got the following error:-

Traceback (most recent call last):

  _main(parser.parse_args())
File "yad2k.py", line 233, in _main
  Lambda(
File "/home/sunny/miniconda3/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 
925, in __call__
  return self._functional_construction_call(inputs, args, kwargs,
File "/home/sunny/miniconda3/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 
1117, in _functional_construction_call
  outputs = call_fn(cast_inputs, *args, **kwargs)
File "/home/sunny/miniconda3/lib/python3.8/site-packages/tensorflow/python/keras/layers/core.py", line 903, i
n call
  result = self.function(inputs, **kwargs)
File "/home/sunny/YAD2K/yad2k/models/keras_yolo.py", line 32, in space_to_depth_x2
  return tf.space_to_depth(x, block_size=2)
AttributeError: module 'tensorflow' has no attribute 'space_to_depth'

From the all chats I figured out that the above needs to run in tensorflow 1.x . However it puts me back where I started which is to run it in tensorflow 1.x. I would love to stick with tensorflow 2.3.

Wondering if someone can guide me here. Frankly, to get me going all I need is an model hd5 file. But I thought generating one would be a better learning than to get one.

Answer 1

The above problem goes away when you upgrade all of your code under yad2k repo ( particularly yad2k.py and python files under models folder to tensorflow 2.x. The beautiful upgrade utility provided by tensorflow does the magic for you by replacing the original call to the compatible tf.compat.v1.space_to_depth(input=x, block_size=...)

Therefore for those who are planning to do the hard job of downgrading their tensorflow and keras, I would recommend them to try the tensorflow upgrade. This saves a lot of time.

This takes care of my model h5 file creation. My bad - I didn't think about it when I asking the question.