Traceback (most recent call last):


 "scipy_minimize_constraints.py", line 19, in <module>

a=minimize(obj,x,args=(b),constraints={'type': 'ineq', 'fun':constr,'args':[b]})


 "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/optimize/_minimize.py", line 495, in minimize

constraints, callback=callback, **options)


 "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/optimize/slsqp.py", line 378, in _minimize_slsqp

fx = func(x)


 "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/optimize/optimize.py", line 292, in function_wrapper

return function(*(wrapper_args + args))


 "scipy_minimize_constraints.py", line 9, in obj

return math.log(x-b)
ValueError: math domain error

Traceback (most recent call last):


 "train.py", line 75, in <module>

monitored_metrics={'val_generator_PSNR_Y' : 'max'}


 "D:\ProgramData\Anaconda3\envs\isr\lib\site-packages\ISR\train\trainer.py", line 308, in train

validation_feats = self.feature_extractor.model.predict(validation_set['hr'])


 "D:\ProgramData\Anaconda3\envs\isr\lib\site-packages\keras\engine\training.py", line 1149, in predict

x, _, _ = self._standardize_user_data(x)


 "D:\ProgramData\Anaconda3\envs\isr\lib\site-packages\keras\engine\training.py", line 751, in _standardize_user_data

exception_prefix='input')


 "D:\ProgramData\Anaconda3\envs\isr\lib\site-packages\keras\engine\training_utils.py", line 128, in standardize_input_data

'with shape ' + str(data_shape))
ValueError: Error when checking input: expected input_2 to have 4 dimensions, but got array with shape (1024, 1)
