UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd5 in position 86: invalid continuation byte

[jiandandan001]

Thank you for sharing the code. I have the following problem, do you know how to solve it? thanks

==================== PRETRAINED MODEL Loading Succeeded ====================
==================== Reading Checkpoints ====================
=================== Fail to find a Checkpoint ====================
==================== No model to load ======================================
[*] Training Starts
Traceback (most recent call last):
File "D:/2020/ReferenceCode/MZSR-master/main.py", line 71, in
main()
File "D:/2020/ReferenceCode/MZSR-master/main.py", line 30, in main
Trainer()
File "D:\2020\ReferenceCode\MZSR-master\train.py", line 171, in call
inputa, labela, inputb, labelb = self.data_generator.make_data_tensor(sess, self.scale_list, noise_std=0.0)
File "D:\2020\ReferenceCode\MZSR-master\dataGenerator.py", line 19, in make_data_tensor
label_train_=sess.run(self.label_train)
File "G:\Anaconda\envs\tensorflow2.3-gpu\lib\site-packages\tensorflow\python\client\session.py", line 958, in run
run_metadata_ptr)
File "G:\Anaconda\envs\tensorflow2.3-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1181, in _run
feed_dict_tensor, options, run_metadata)
File "G:\Anaconda\envs\tensorflow2.3-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1359, in _do_run
run_metadata)
File "G:\Anaconda\envs\tensorflow2.3-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1365, in _do_call
return fn(*args)
File "G:\Anaconda\envs\tensorflow2.3-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _run_fn
target_list, run_metadata)
File "G:\Anaconda\envs\tensorflow2.3-gpu\lib\site-packages\tensorflow\python\client\session.py", line 1443, in _call_tf_sessionrun
run_metadata)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd5 in position 86: invalid continuation byte

Process finished with exit code 1

[BassantTolba1234]

Dear Sir,
Amazing work ! Congratulation!!
please , I have a question.can you kindly provide me with the full path I should insert of checkpoint the trained large scale training model to be able to use it as a pre-trained to meta transfer training?
I'm waiting for your reply.
Thanks in advance

[BassantTolba1234]

Please @jiandandan001 I'm facing a problem when i load the pretrained model , specially when it reads the checkpoint
this is the error .. how did you kindly solve it please ??

NotFoundError (see above for traceback): Key MODEL/conv7/kernel/Adam_3 not found in checkpoint
[[Node: save/RestoreV2_69 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_save/Const_0_0, save/RestoreV2_69/tensor_names, save/RestoreV2_69/shape_and_slices)]]

[BassantTolba1234]

Please can you kindly explain me how to calculate this weight loss ?

def get_loss_weights(self):
loss_weights = tf.ones(shape=[self.TASK_ITER]) * (1.0/self.TASK_ITER)
decay_rate = 1.0 / self.TASK_ITER / (10000 / 3)
min_value= 0.03 / self.TASK_ITER

    loss_weights_pre = tf.maximum(loss_weights[:-1] - (tf.multiply(tf.to_float(self.global_step), decay_rate)), min_value)

    loss_weight_cur= tf.minimum(loss_weights[-1] + (tf.multiply(tf.to_float(self.global_step),(self.TASK_ITER- 1) * decay_rate)), 1.0 - ((self.TASK_ITER - 1) * min_value))
    loss_weights = tf.concat([[loss_weights_pre], [[loss_weight_cur]]], axis=1)
    return loss_weights