import os #line:1
import math #line:2
import time #line:3
import datetime #line:4
from functools import reduce #line:5
import matplotlib #line:7
matplotlib .use ('Agg')#line:8
import matplotlib .pyplot as plt #line:9
import numpy as np #line:11
import scipy .misc as misc #line:12
import pickle #line:13
import torch #line:14
import torch .optim as optim #line:15
import torch .optim .lr_scheduler as lrs #line:16
from skimage .measure import compare_psnr #line:17
from scipy .ndimage import zoom #line:18
class timer ():#line:19
    def __init__ (O0O0OO0O000O0OO00 ):#line:20
        O0O0OO0O000O0OO00 .acc =0 #line:21
        O0O0OO0O000O0OO00 .tic ()#line:22
    def tic (O00OOOOO000OO0O00 ):#line:24
        O00OOOOO000OO0O00 .t0 =time .time ()#line:25
    def toc (O00OO000O0OOO0O0O ):#line:27
        return time .time ()-O00OO000O0OOO0O0O .t0 #line:28
    def hold (O00O0O000O0OOO00O ):#line:30
        O00O0O000O0OOO00O .acc +=O00O0O000O0OOO00O .toc ()#line:31
    def release (O0O00O0O0OO00O0O0 ):#line:33
        O00OO000OOO00O000 =O0O00O0O0OO00O0O0 .acc #line:34
        O0O00O0O0OO00O0O0 .acc =0 #line:35
        return O00OO000OOO00O000 #line:37
    def reset (O00OO00O0O00OO000 ):#line:39
        O00OO00O0O00OO000 .acc =0 #line:40
class checkpoint ():#line:42
    def __init__ (OO0O0OOOO0OOO0000 ,OO0OO0OOO00O0000O ):#line:43
        OO0O0OOOO0OOO0000 .args =OO0OO0OOO00O0000O #line:44
        OO0O0OOOO0OOO0000 .ok =True #line:45
        OO0O0OOOO0OOO0000 .log =torch .Tensor ()#line:46
        O00O0O0O0O00OOOOO =datetime .datetime .now ().strftime ('%Y-%m-%d-%H:%M:%S')#line:47
        if OO0OO0OOO00O0000O .load =='.':#line:49
            if OO0OO0OOO00O0000O .save =='.':OO0OO0OOO00O0000O .save =O00O0O0O0O00OOOOO #line:50
            OO0O0OOOO0OOO0000 .dir =OO0OO0OOO00O0000O .save #line:52
        else :#line:53
            OO0O0OOOO0OOO0000 .dir ='../experiment/'+OO0OO0OOO00O0000O .load #line:54
            if not os .path .exists (OO0O0OOOO0OOO0000 .dir ):#line:55
                OO0OO0OOO00O0000O .load ='.'#line:56
            else :#line:57
                OO0O0OOOO0OOO0000 .log =torch .load (OO0O0OOOO0OOO0000 .dir +'/psnr_log.pt')#line:58
                print ('Continue from epoch {}...'.format (len (OO0O0OOOO0OOO0000 .log )))#line:59
        if OO0OO0OOO00O0000O .reset :#line:61
            os .system ('rm -rf '+OO0O0OOOO0OOO0000 .dir )#line:62
            OO0OO0OOO00O0000O .load ='.'#line:63
        def _O00O0000OOO00O0O0 (O00O0O0O000000OOO ):#line:65
            if not os .path .exists (O00O0O0O000000OOO ):os .makedirs (O00O0O0O000000OOO )#line:66
        _O00O0000OOO00O0O0 (OO0O0OOOO0OOO0000 .dir )#line:68
        _O00O0000OOO00O0O0 (OO0O0OOOO0OOO0000 .dir +'/model')#line:69
        _O00O0000OOO00O0O0 (OO0O0OOOO0OOO0000 .dir +'/results')#line:70
        O00OO000OOO0OOO0O ='a'if os .path .exists (OO0O0OOOO0OOO0000 .dir +'/log.txt')else 'w'#line:72
        OO0O0OOOO0OOO0000 .log_file =open (OO0O0OOOO0OOO0000 .dir +'/log.txt',O00OO000OOO0OOO0O )#line:73
        with open (OO0O0OOOO0OOO0000 .dir +'/config.txt',O00OO000OOO0OOO0O )as OO000OOO000000O0O :#line:74
            OO000OOO000000O0O .write (O00O0O0O0O00OOOOO +'\n\n')#line:75
            for O00O0O0O0OO0O00O0 in vars (OO0OO0OOO00O0000O ):#line:76
                OO000OOO000000O0O .write ('{}: {}\n'.format (O00O0O0O0OO0O00O0 ,getattr (OO0OO0OOO00O0000O ,O00O0O0O0OO0O00O0 )))#line:77
            OO000OOO000000O0O .write ('\n')#line:78
    def save (O00O0O00O00OO00OO ,O000OOO00O00O0OO0 ,OO00O00O0OO0OOOOO ,is_best =False ):#line:80
        O000OOO00O00O0OO0 .model .save (O00O0O00O00OO00OO .dir ,OO00O00O0OO0OOOOO ,is_best =is_best )#line:81
        O000OOO00O00O0OO0 .loss .save (O00O0O00O00OO00OO .dir )#line:82
        O000OOO00O00O0OO0 .loss .plot_loss (O00O0O00O00OO00OO .dir ,OO00O00O0OO0OOOOO )#line:83
        O00O0O00O00OO00OO .plot_psnr (OO00O00O0OO0OOOOO )#line:85
        torch .save (O00O0O00O00OO00OO .log ,os .path .join (O00O0O00O00OO00OO .dir ,'psnr_log.pt'))#line:86
        torch .save (O000OOO00O00O0OO0 .optimizer .state_dict (),os .path .join (O00O0O00O00OO00OO .dir ,'optimizer.pt'))#line:90
    def save_train (OOO000O0O0O0O00O0 ,OO0O0O0O0OOO0O0O0 ,O00O0OO0OOO0OOO00 ):#line:92
        OO0O0O0O0OOO0O0O0 .model .save (OOO000O0O0O0O00O0 .dir ,O00O0OO0OOO0OOO00 )#line:93
        torch .save (OOO000O0O0O0O00O0 .log ,os .path .join (OOO000O0O0O0O00O0 .dir ,'psnr_log.pt'))#line:94
        torch .save (OO0O0O0O0OOO0O0O0 .optimizer .state_dict (),os .path .join (OOO000O0O0O0O00O0 .dir ,'optimizer.pt'))#line:98
    def add_log (OOO00000OO0O00OOO ,O0OO000OOOOO0OOO0 ):#line:100
        OOO00000OO0O00OOO .log =torch .cat ([OOO00000OO0O00OOO .log ,O0OO000OOOOO0OOO0 ])#line:101
    def write_log (O00000O00O00O0OO0 ,OO00OOO0O00OOO0OO ,refresh =False ):#line:103
        print (OO00OOO0O00OOO0OO )#line:104
        O00000O00O00O0OO0 .log_file .write (OO00OOO0O00OOO0OO +'\n')#line:105
        if refresh :#line:106
            O00000O00O00O0OO0 .log_file .close ()#line:107
            O00000O00O00O0OO0 .log_file =open (O00000O00O00O0OO0 .dir +'/log.txt','a')#line:108
    def done (OO00O0O00O00000OO ):#line:110
        OO00O0O00O00000OO .log_file .close ()#line:111
    def plot_psnr (OOO0OO0OO0O000000 ,OO00OO0OO00OOOOO0 ):#line:113
        OOOO00O00000O0000 =np .linspace (1 ,OO00OO0OO00OOOOO0 ,OO00OO0OO00OOOOO0 )#line:114
        OO0O00OO00OO00OO0 ='SR on {}'.format (OOO0OO0OO0O000000 .args .data_test )#line:115
        OOO0O00O00OOO0OOO =plt .figure ()#line:116
        plt .title (OO0O00OO00OO00OO0 )#line:117
        for OO00OO00O0OOOO0OO ,OO00O00OOOO00OO00 in enumerate (OOO0OO0OO0O000000 .args .scale ):#line:118
            plt .plot (OOOO00O00000O0000 ,OOO0OO0OO0O000000 .log [:,OO00OO00O0OOOO0OO ].numpy (),label ='Scale {}'.format (OO00O00OOOO00OO00 ))#line:123
        plt .legend ()#line:124
        plt .xlabel ('Epochs')#line:125
        plt .ylabel ('PSNR')#line:126
        plt .grid (True )#line:127
        plt .savefig ('{}/test_{}.pdf'.format (OOO0OO0OO0O000000 .dir ,OOO0OO0OO0O000000 .args .data_test ))#line:128
        plt .close (OOO0O00O00OOO0OOO )#line:129
    def save_results (OO000000O00O0OO0O ,OO00OO0OO000O0OO0 ,OO00OOOOOOO00O00O ,OOO000000OOO0000O ):#line:131
        OOO0000OO00OOOO0O =('SR','LR','HR','NUM')#line:134
        if not os .path .isdir ('{}/results/raw/'.format (OO000000O00O0OO0O .dir )):#line:135
            os .mkdir ('{}/results/raw/'.format (OO000000O00O0OO0O .dir ))#line:136
        if not os .path .isdir ('{}/results/img/'.format (OO000000O00O0OO0O .dir )):#line:137
            os .mkdir ('{}/results/img/'.format (OO000000O00O0OO0O .dir ))#line:138
        for OO00O0OO0OOO0OOO0 ,OOO0O0OOOOO000O00 in zip (OO00OOOOOOO00O00O ,OOO0000OO00OOOO0O ):#line:139
            O00O000OOO0000000 =np .clip (OO00O0OO0OOO0OOO0 ,-1024 ,4000 ).round ().astype ('int16')#line:141
            if OO000000O00O0OO0O .args .model =='META_MULTI':#line:142
                O0OO0O00O0OO0OOO0 =np .zeros ((O00O000OOO0000000 .shape [1 ],O00O000OOO0000000 .shape [2 ],O00O000OOO0000000 .shape [3 ]*OOO000000OOO0000O ))#line:143
                for OOO0OO000O00O0OO0 in range (OOO000000OOO0000O ):#line:144
                    O0OO0O00O0OO0OOO0 [...,OOO0OO000O00O0OO0 :][...,::OOO000000OOO0000O ]=O00O000OOO0000000 [OOO0OO000O00O0OO0 ]#line:146
            else :#line:147
                O0OO0O00O0OO0OOO0 =O00O000OOO0000000 [...,::2 ]#line:148
            if OO000000O00O0OO0O .args .view !='cor':#line:151
                O0OO0O00O0OO0OOO0 =np .transpose (O0OO0O00O0OO0OOO0 ,(1 ,0 ,2 ))#line:152
            print ('HOLDER:',O0OO0O00O0OO0OOO0 .shape )#line:153
            O0OO0000OO000O0O0 ='{}/results/raw/{}_{}_x{}_'.format (OO000000O00O0OO0O .dir ,OO00OO0OO000O0OO0 ,OO000000O00O0OO0O .args .view ,OOO000000OOO0000O )#line:155
            pickle .dump (O0OO0O00O0OO0OOO0 ,open ('{}{}.pt'.format (O0OO0000OO000O0O0 ,OOO0O0OOOOO000O00 ),'wb'))#line:157
def quantize (OO000OO000OOOO0OO ,O000000OO0OO00OOO ):#line:162
    O0O00O0OOOO0OO0OO =255 /O000000OO0OO00OOO #line:163
    return OO000OO000OOOO0OO .mul (O0O00O0OOOO0OO0OO ).clamp (0 ,255 ).round ().div (O0O00O0OOOO0OO0OO )#line:164
def calc_psnr (O0OOO00O0O0OOO000 ,OOO000O0O0OO00O0O ,O0O0O0O0OOO0O00O0 ,O0O000O00OOOOOO0O ):#line:166
    print (OOO000O0O0OO00O0O .shape ,O0O0O0O0OOO0O00O0 .shape )#line:168
    O0OO0O0OOOO0OO0OO =OOO000O0O0OO00O0O #line:169
    OO00O0OO000O0O0O0 =O0O0O0O0OOO0O00O0 .data .cpu ().numpy ().astype (float )#line:170
    O0OO0O0OOOO0OO0OO ,OO00O0OO000O0O0O0 =np .clip (O0OO0O0OOOO0OO0OO ,-1024 ,4000 ).round ().astype (float )/4000 ,np .clip (OO00O0OO000O0O0O0 ,-1024 ,4000 ).round ()/4000 #line:172
    if O0OOO00O0O0OOO000 .model =='MSR_RDN':#line:174
        O0OO0O0OOOO0OO0OO ,OO00O0OO000O0O0O0 =np .delete (O0OO0O0OOOO0OO0OO ,np .s_ [::int (O0OOO00O0O0OOO000 .scale [0 ])],axis =2 ),np .delete (OO00O0OO000O0O0O0 ,np .s_ [::int (O0OOO00O0O0OOO000 .scale [0 ])],axis =2 )#line:175
    else :#line:176
        print ('comparison, ',O0OO0O0OOOO0OO0OO .shape ,OO00O0OO000O0O0O0 .shape )#line:177
        O0OO0O0OOOO0OO0OO ,OO00O0OO000O0O0O0 =O0OO0O0OOOO0OO0OO [1 :int (O0OOO00O0O0OOO000 .scale [0 ])],OO00O0OO000O0O0O0 [1 :int (O0OOO00O0O0OOO000 .scale [0 ])]#line:178
        print ('comparison, ',O0OO0O0OOOO0OO0OO .shape ,OO00O0OO000O0O0O0 .shape )#line:179
    OO000O000OO00O0O0 =compare_psnr (OO00O0OO000O0O0O0 [:,128 :384 ,128 :384 ,:],O0OO0O0OOOO0OO0OO [:,128 :384 ,128 :384 ,:])#line:190
    return OO000O000OO00O0O0 #line:191
def make_optimizer (OOO00O000O0O0O00O ,OOOOO0O0000OO000O ):#line:193
    OO0OOOO000O0O0000 =filter (lambda O00OOOOOO0OO0O0OO :O00OOOOOO0OO0O0OO .requires_grad ,OOOOO0O0000OO000O .parameters ())#line:194
    if OOO00O000O0O0O00O .optimizer =='SGD':#line:196
        O0O0OOOO0OO0O0OO0 =optim .SGD #line:197
        O00O000O0000000O0 ={'momentum':OOO00O000O0O0O00O .momentum }#line:198
    elif OOO00O000O0O0O00O .optimizer =='ADAM':#line:199
        O0O0OOOO0OO0O0OO0 =optim .Adam #line:200
        O00O000O0000000O0 ={'betas':(OOO00O000O0O0O00O .beta1 ,OOO00O000O0O0O00O .beta2 ),'eps':OOO00O000O0O0O00O .epsilon }#line:204
    elif OOO00O000O0O0O00O .optimizer =='RMSprop':#line:205
        O0O0OOOO0OO0O0OO0 =optim .RMSprop #line:206
        O00O000O0000000O0 ={'eps':OOO00O000O0O0O00O .epsilon }#line:207
    O00O000O0000000O0 ['lr']=OOO00O000O0O0O00O .lr #line:209
    O00O000O0000000O0 ['weight_decay']=OOO00O000O0O0O00O .weight_decay #line:210
    return O0O0OOOO0OO0O0OO0 (OO0OOOO000O0O0000 ,**O00O000O0000000O0 )#line:212
def make_scheduler (OO00O0000OOO0OOOO ,O0O0O00OO0OO0OO0O ):#line:214
    if OO00O0000OOO0OOOO .decay_type =='step':#line:215
        OOOOOO00O0O000000 =lrs .StepLR (O0O0O00OO0OO0OO0O ,step_size =OO00O0000OOO0OOOO .lr_decay ,gamma =OO00O0000OOO0OOOO .gamma )#line:220
    elif OO00O0000OOO0OOOO .decay_type .find ('step')>=0 :#line:221
        OO00000O0OO0OO000 =OO00O0000OOO0OOOO .decay_type .split ('_')#line:222
        OO00000O0OO0OO000 .pop (0 )#line:223
        OO00000O0OO0OO000 =list (map (lambda OOOO0OO00000O00OO :int (OOOO0OO00000O00OO ),OO00000O0OO0OO000 ))#line:224
        OOOOOO00O0O000000 =lrs .MultiStepLR (O0O0O00OO0OO0OO0O ,milestones =OO00000O0OO0OO000 ,gamma =OO00O0000OOO0OOOO .gamma )#line:229
    return OOOOOO00O0O000000 #line:231
