import torch #line:1
from .import utility #line:2
from .import data #line:3
from .data import test #line:4
from .model import meta_multi #line:5
from .import model #line:6
from .import loss #line:7
import os #line:8
import sys #line:9
from .import option #line:11
from .trainer import Trainer #line:12

local_model_path =os .path .abspath (__file__ ).replace (os .path .abspath (__file__ ).split ('/')[-1 ],'')#line:15
def get_Stage1_result (scale ='4',save ='/home1/mksun/SAINT/result/brain_ct',loss ='1*L1',base_model ='META_MULTI',epochs =100 ,batch_size =1 ,dir_data ='/home1/mksun/SAINT/Data/Stage1_Input',data_train ='TRAIN',data_test ='TEST',data_range ='1-1/1-100',n_colors =3 ,n_GPUs =1 ,save_results =True ,rgb_range =4000 ,RDNconfig ='C',patch_size =32 ,pre_train =os .path .join (local_model_path ,'model_best.pt'),test_only =True ,view ='sag',gpu='0'):#line:21
    ""#line:45
    os .environ ['CUDA_VISIBLE_DEVICES']=gpu#line:13
    OO0OOO000OOOO00OO =option .paprams2arg (dict (scale =scale ,save =save ,loss =loss ,base_model =base_model ,epochs =epochs ,batch_size =batch_size ,dir_data =dir_data ,data_train =data_train ,data_test =data_test ,data_range =data_range ,n_colors =n_colors ,n_GPUs =n_GPUs ,save_results =save_results ,rgb_range =rgb_range ,RDNconfig =RDNconfig ,patch_size =patch_size ,pre_train =pre_train ,test_only =test_only ,view =view )).args #line:54
    torch .manual_seed (OO0OOO000OOOO00OO .seed )#line:56
    O00OOO0O00OOOOO00 =utility .checkpoint (OO0OOO000OOOO00OO )#line:57
    if O00OOO0O00OOOOO00 .ok :#line:59
        OO0000O000OO0O000 =data .Data (OO0OOO000OOOO00OO )#line:60
        print ("loader_loadertest---",len (OO0000O000OO0O000 .loader_test ))#line:61
        print ("model:----",model )#line:63
        print ("model.type:---",type (model ))#line:64
        OO0OO000OOO00OOOO =model .Model (OO0OOO000OOOO00OO ,O00OOO0O00OOOOO00 )#line:65
        print ('number of parameters:',count_parameters (OO0OO000OOO00OOOO ))#line:67
        loss =loss .Loss (OO0OOO000OOOO00OO ,O00OOO0O00OOOOO00 )if not OO0OOO000OOOO00OO .test_only else None #line:68
        O0O000O0000O00O00 =Trainer (OO0OOO000OOOO00OO ,OO0000O000OO0O000 ,OO0OO000OOO00OOOO ,loss ,O00OOO0O00OOOOO00 )#line:69
        while not O0O000O0000O00O00 .terminate ():#line:70
            print (1 )#line:71
            O0O000O0000O00O00 .train ()#line:72
            print (2 )#line:73
            O0O000O0000O00O00 .test ()#line:74
            print (3 )#line:75
        O00OOO0O00OOOOO00 .done ()#line:76
def count_parameters (OOO0O0OO00O00O0OO ):#line:78
        return sum (O000O000OO0OOOOOO .numel ()for O000O000OO0OOOOOO in OOO0O0OO00O00O0OO .parameters ()if O000O000OO0OOOOOO .requires_grad )#line:79
