| import os | |
| with open( | |
| os.path.expanduser( | |
| "~/torch_datasets/github-python/mega_corpus/data/corpus_processed.txt" | |
| ), | |
| "r", | |
| ) as f: | |
| data = f.read() | |
| to_check = """<newline> logger . info ( f " initial validation samples in first step . . . " ) <newline> model . eval ( ) <newline> <newline> gen _ validation _ samples ( validation _ pipeline , args , wandb , samples _ dir , train _ ts , train _ steps ) <newline> <newline> model . train ( ) <newline>""" | |
| to_check = """' nonpayable ' , ' type ' : ' function ' } , { ' inputs ' : [ { ' internaltype ' : ' uint 2 5 6 ' , ' name ' : ' ' , ' type ' : ' uint 2 5 6 ' } ] , ' name ' : ' ' , ' outputs""" | |
| to_check = """parser . add _ argument ( ' - - save _ folder ' , type = str , default = ' data / save ' , help = ' save folder ' )""" | |
| to_check = """= torch . zeros ( len ( imgs ) ) <newline> <tab> for x _ interp in range ( 1 , args . batch _ size ) :""" | |
| # to_check = """x _ interp = machine . interpolate ( imgs [ 0 ] , imgs [ 1 ] , n _ interp )""" # should be true | |
| # to_check = "<UNK>" | |
| to_check = to_check.replace(" ", "").lower() | |
| data = data.replace(" ", "").lower() | |
| print(to_check in data) | |