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JWSoh / MZSR

Meta-Transfer Learning for Zero-Shot Super-Resolution (CVPR, 2020)
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UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd5 in position 86: invalid continuation byte #26

Open jiandandan001 opened 4 years ago

jiandandan001 commented 4 years ago

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 labeltrain=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 commented 3 years ago

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 commented 3 years ago

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 commented 3 years ago

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