load model error!

[aligoglos]

I've tried test mainimprovementcolor.py but in line 158 I got this error:

tracking <tf.Variable 'batch_renormalization_2/batch_renormalization_2_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_2/batch_renormalization_2_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_2/batch_renormalization_2_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_3/batch_renormalization_3_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_3/batch_renormalization_3_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_3/batch_renormalization_3_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_4/batch_renormalization_4_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_4/batch_renormalization_4_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_4/batch_renormalization_4_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_5/batch_renormalization_5_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_5/batch_renormalization_5_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_5/batch_renormalization_5_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_17/batch_renormalization_17_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_17/batch_renormalization_17_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_17/batch_renormalization_17_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_6/batch_renormalization_6_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_6/batch_renormalization_6_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_6/batch_renormalization_6_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_7/batch_renormalization_7_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_7/batch_renormalization_7_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_7/batch_renormalization_7_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_8/batch_renormalization_8_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_8/batch_renormalization_8_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_8/batch_renormalization_8_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_9/batch_renormalization_9_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_9/batch_renormalization_9_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_9/batch_renormalization_9_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_10/batch_renormalization_10_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_10/batch_renormalization_10_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_10/batch_renormalization_10_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_11/batch_renormalization_11_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_11/batch_renormalization_11_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_11/batch_renormalization_11_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_18/batch_renormalization_18_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_18/batch_renormalization_18_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_18/batch_renormalization_18_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_12/batch_renormalization_12_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_12/batch_renormalization_12_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_12/batch_renormalization_12_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_13/batch_renormalization_13_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_13/batch_renormalization_13_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_13/batch_renormalization_13_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_14/batch_renormalization_14_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_14/batch_renormalization_14_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_14/batch_renormalization_14_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_15/batch_renormalization_15_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_15/batch_renormalization_15_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_15/batch_renormalization_15_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_16/batch_renormalization_16_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_16/batch_renormalization_16_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_16/batch_renormalization_16_t:0' shape=(1,) dtype=float32> t
tracking <tf.Variable 'batch_renormalization_19/batch_renormalization_19_r_max:0' shape=(1,) dtype=float32> r_max
tracking <tf.Variable 'batch_renormalization_19/batch_renormalization_19_d_max:0' shape=(1,) dtype=float32> d_max
tracking <tf.Variable 'batch_renormalization_19/batch_renormalization_19_t:0' shape=(1,) dtype=float32> t
Traceback (most recent call last):
  File "mainimprovementcolor.py", line 158, in <module>
    model = load_model(args.pretrain, compile=False)
  File "C:\Users\127051\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\engine\saving.py", line 492, in load_wrapper
    return load_function(*args, **kwargs)
  File "C:\Users\127051\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\engine\saving.py", line 584, in load_model
    model = _deserialize_model(h5dict, custom_objects, compile)
  File "C:\Users\127051\AppData\Local\Programs\Python\Python37\lib\site-packages\keras\engine\saving.py", line 334, in _deserialize_model
    ' elements.')
ValueError: Layer #1 (named "batch_renormalization_1" in the current model) was found to correspond to layer b'batch_renormalization_1' in the save file. However the new layer batch_renormalization_1 expects 7 weights, but the saved weights have 4 elements.

[HaowenGuan]

Same issure

[nkoprowicz3]

I had this issue too but was able to get around it by making starting with a fresh python 2.7 environment and installing Keras 2.1.0, and Tensorflow 1.3.0.

[ansariyusuf]

@nkoprowicz3 How did you install Tensorflow 1.3.0? I am unable to locate the package on conda or pip. Please assist.

Thank you,

[hellloxiaotian]

Hi, please try the following command. "conda install --channel https://conda.anaconda.org/jjh_cio_testing tensorflow-gpu" Best wishes, Chunwei Tian, PhD Harbin Institute of Technology, China At 2021-01-12 15:11:55, "Mohammed Yusuf Ansari" <[email protected]> wrote: @nkoprowicz3 How did you install Tensorflow 1.3.0? I am unable to locate the package on conda or pip. Please assist. Thank you, — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub, or unsubscribe.