Open zakaria-hassoun opened 7 months ago
The program cannot create a writeable file. Please check your permission to create files.
Even after granting all permissions, the problem persists. Do you have any further suggestions, please?
The error message said that the path is not found. Could you manually create that directory and see if the error still persists?
Thank you for you precious help! But now, I've been encountering a MemoryError while working with the optimization implementation in the code you provided. The error occurs with the following traceback:
Exception in thread Thread-11: Traceback (most recent call last): File "C:\Users\USER\anaconda3\envs\zakaria\lib\threading.py", line 926, in _bootstrap_inner self.run() File "C:\Users\USER\anaconda3\envs\zakaria\lib\threading.py", line 870, in run self._target(*self._args, **self._kwargs) File "C:\Users\USER\anaconda3\envs\zakaria\lib\site-packages\IPython\utils_process_win32.py", line 100, in stdout_read for line in read_no_interrupt(p.stdout).splitlines(): File "C:\Users\USER\anaconda3\envs\zakaria\lib\site-packages\IPython\utils_process_common.py", line 37, in read_no_interrupt return p.read() MemoryError
I would greatly appreciate any advice or suggestions you may have for resolving this issue.
This might be a hardware issue that simply indicates insufficient memory. Check whether it is running on a CPU or a GPU, and then check if the memory, or GPU memory if running on a GPU, is sufficient.
Hi everybody I trained the Bazier GAN using the training code given in the folder
!python train_gan.py train 2 2 --model_id=0
, but i got the error :94: [D] real 0.049025 fake 0.055628 q -0.489287 [G] fake 2.868984 reg 0.162203 q -0.756375 95: [D] real 0.024284 fake 0.066706 q -0.767501 [G] fake 3.008167 reg 0.151189 q -0.750525 96: [D] real 0.025183 fake 0.063513 q -0.674761 [G] fake 2.918955 reg 0.140957 q -0.816136 97: [D] real 0.018686 fake 0.058341 q -0.535204 [G] fake 2.976438 reg 0.146039 q -0.792278 98: [D] real 0.020485 fake 0.052454 q -0.686408 [G] fake 3.203141 reg 0.146167 q -0.763868 99: [D] real 0.017695 fake 0.049382 q -0.872483 [G] fake 3.673816 reg 0.161016 q -0.910567 100: [D] real 0.019736 fake 0.024547 q -0.772567 [G] fake 3.770491 reg 0.210877 q -0.896318 101: [D] real 0.012227 fake 0.029819 q -0.819332 [G] fake 3.622375 reg 0.190337 q -0.887288 102: [D] real 0.009362 fake 0.037180 q -0.904366 [G] fake 4.002365 reg 0.185869 q -0.870554 103: [D] real 0.008421 fake 0.020478 q -0.865159 [G] fake 3.838341 reg 0.200372 q -1.013012 104: [D] real 0.012289 fake 0.027121 q -0.583854 [G] fake 3.490432 reg 0.173785 q -0.682441 105: [D] real 0.005464 fake 0.048383 q -0.558417 [G] fake 3.059311 reg 0.168226 q -0.707295 106: [D] real 0.005408 fake 0.076037 q -0.722151 [G] fake 3.225547 reg 0.167123 q -0.791089 107: [D] real 0.011245 fake 0.060011 q -0.830260 [G] fake 3.372714 reg 0.174958 q -0.893936 108: [D] real 0.015743 fake 0.057669 q -0.944482 [G] fake 3.649921 reg 0.164587 q -0.892548 109: [D] real 0.014506 fake 0.105701 q -0.893725 [G] fake 3.169295 reg 0.171590 q -0.089188 110: [D] real 0.033460 fake 0.069197 q -0.338123 [G] fake 1.794614 reg 0.180591 q -0.445808 111: [D] real 0.010237 fake 0.407048 q -0.053652 [G] fake 2.409947 reg 0.172413 q -0.533668 112: [D] real 0.056873 fake 0.090222 q -0.605167 [G] fake 2.825137 reg 0.166038 q -0.661242 113: [D] real 0.093108 fake 0.084386 q -0.662412 [G] fake 2.858156 reg 0.171858 q -0.755297 114: [D] real 0.048567 fake 0.104229 q -0.696583 [G] fake 2.956159 reg 0.170676 q -0.740559 115: [D] real 0.059919 fake 0.103678 q -0.686840 [G] fake 3.038925 reg 0.172483 q -0.919335 116: [D] real 0.111117 fake 0.168958 q -0.866141 [G] fake 3.139798 reg 0.160500 q -0.837689 117: [D] real 0.205896 fake 0.437863 q -0.841303 [G] fake 3.713123 reg 0.164670 q -0.679638 118: [D] real 1.123409 fake 2.513395 q -0.587899 [G] fake 3.511013 reg 0.155572 q -0.392821 119: [D] real 1.536775 fake 0.325721 q -0.831571 [G] fake 1.454310 reg 0.161923 q -0.596536 120: [D] real 0.330671 fake 1.434564 q -0.527187 [G] fake 2.096961 reg 0.213576 q -0.880335 121: [D] real 0.845298 fake 0.588884 q -0.683085 [G] fake 1.919043 reg 0.190389 q -0.848813 122: [D] real 0.806444 fake 0.831669 q -0.787398 [G] fake 1.612193 reg 0.181597 q -0.764545 123: [D] real 0.578596 fake 0.556828 q -0.806279 [G] fake 1.795060 reg 0.198984 q -0.849524 124: [D] real 0.574830 fake 0.963833 q -0.842046 [G] fake 1.856215 reg 0.209261 q -0.840430 125: [D] real 0.884844 fake 0.570552 q -0.831394 [G] fake 1.344687 reg 0.186219 q -0.702547 126: [D] real 0.667982 fake 0.939998 q -0.696801 [G] fake 1.727671 reg 0.178839 q -0.645964 127: [D] real 0.811976 fake 0.451530 q -0.751050 [G] fake 1.484829 reg 0.183385 q -0.648140 128: [D] real 0.615507 fake 0.782151 q -0.840182 [G] fake 1.229969 reg 0.185949 q -0.884246 129: [D] real 0.432424 fake 0.582835 q -0.737997 [G] fake 1.672830 reg 0.175358 q -0.778267 130: [D] real 0.756622 fake 0.648572 q -0.832122 [G] fake 1.258403 reg 0.213678 q -0.839033 131: [D] real 0.504551 fake 0.924520 q -0.820396 [G] fake 1.489545 reg 0.220720 q -0.500786 132: [D] real 0.806953 fake 0.559774 q -0.673045 [G] fake 1.377262 reg 0.195133 q -0.956005 133: [D] real 0.604057 fake 0.795723 q -0.824598 [G] fake 1.424316 reg 0.190225 q -0.723750 134: [D] real 0.730149 fake 0.497561 q -0.753350 [G] fake 1.127791 reg 0.195168 q -0.661237 135: [D] real 0.594268 fake 0.745395 q -0.852637 [G] fake 1.306198 reg 0.221789 q -0.753839 136: [D] real 0.527917 fake 0.668734 q -0.914637 [G] fake 1.596844 reg 0.192573 q -0.834908 137: [D] real 0.645270 fake 0.610233 q -0.846997 [G] fake 1.318011 reg 0.180237 q -0.594126 138: [D] real 0.618420 fake 0.617515 q -0.748594 [G] fake 1.482435 reg 0.185728 q -0.880302 139: [D] real 0.640740 fake 0.700095 q -0.765105 [G] fake 1.252635 reg 0.175224 q -0.753500 140: [D] real 0.564426 fake 0.747072 q -0.849074 [G] fake 1.383031 reg 0.172862 q -0.459535 141: [D] real 0.827494 fake 0.443311 q -0.738901 [G] fake 1.064335 reg 0.174561 q -0.758910 142: [D] real 0.487161 fake 1.234263 q -0.789341 [G] fake 1.536461 reg 0.207746 q -0.549804 143: [D] real 0.668465 fake 0.405609 q -0.832105 [G] fake 1.271661 reg 0.202024 q -0.787934 144: [D] real 0.604810 fake 0.817013 q -0.801061 [G] fake 1.247777 reg 0.180549 q -0.869429 145: [D] real 0.622981 fake 0.656119 q -0.806624 [G] fake 1.230857 reg 0.175309 q -0.872301 146: [D] real 0.736194 fake 0.655951 q -0.735813 [G] fake 1.050899 reg 0.175174 q -0.851473 147: [D] real 0.596882 fake 0.815118 q -0.820723 [G] fake 1.350834 reg 0.203711 q -0.702248 148: [D] real 0.692439 fake 0.667475 q -0.819480 [G] fake 1.335103 reg 0.182471 q -0.810421 149: [D] real 0.712486 fake 0.662717 q -0.705899 [G] fake 1.149072 reg 0.159546 q -0.972545 150: [D] real 0.576752 fake 0.664418 q -0.788494 [G] fake 1.237292 reg 0.163760 q -0.867523 151: [D] real 0.581326 fake 0.640885 q -0.765226 [G] fake 1.308925 reg 0.175772 q -0.681130 152: [D] real 0.760331 fake 0.500161 q -1.013284 [G] fake 1.056633 reg 0.181632 q -0.868946 153: [D] real 0.558329 fake 0.727618 q -0.932644 [G] fake 1.292400 reg 0.169674 q -0.982578 154: [D] real 0.589010 fake 0.777418 q -0.843361 [G] fake 1.272008 reg 0.166010 q -0.863834 155: [D] real 0.643989 fake 0.810005 q -0.837203 [G] fake 1.331134 reg 0.184250 q -0.844173 156: [D] real 0.749743 fake 0.570826 q -0.957411 [G] fake 1.183065 reg 0.179777 q -0.743625 157: [D] real 0.590272 fake 0.586231 q -0.822308 [G] fake 1.134881 reg 0.181980 q -0.929652 158: [D] real 0.466234 fake 0.722427 q -0.692577 [G] fake 1.497250 reg 0.164048 q -0.814350 159: [D] real 0.802311 fake 0.680343 q -0.759023 [G] fake 1.226673 reg 0.158884 q -0.733456 160: [D] real 0.540587 fake 0.648866 q -0.949648 [G] fake 1.151498 reg 0.166885 q -0.761982 161: [D] real 0.570282 fake 0.706784 q -0.941831 [G] fake 1.184997 reg 0.192602 q -0.951665 162: [D] real 0.580857 fake 0.717304 q -0.766593 [G] fake 1.326836 reg 0.174802 q -0.920302 163: [D] real 0.651678 fake 0.594557 q -0.906404 [G] fake 1.103606 reg 0.182712 q -0.796652 164: [D] real 0.618101 fake 0.715031 q -0.922442 [G] fake 1.198589 reg 0.197391 q -0.876396 165: [D] real 0.586636 fake 0.799828 q -0.916981 [G] fake 1.101994 reg 0.190851 q -0.899326 166: [D] real 0.620455 fake 0.654185 q -0.942161 [G] fake 1.242548 reg 0.197050 q -0.885755 167: [D] real 0.548295 fake 0.641066 q -0.894651 [G] fake 1.268167 reg 0.175528 q -0.592985 168: [D] real 0.577349 fake 0.740060 q -0.807416 [G] fake 1.203739 reg 0.172994 q -0.762825 169: [D] real 0.524740 fake 0.578754 q -0.987321 [G] fake 1.280082 reg 0.169113 q -0.927283 170: [D] real 0.588097 fake 0.557567 q -1.051758 [G] fake 1.397066 reg 0.162628 q -0.914452 171: [D] real 0.537267 fake 0.502048 q -1.028583 [G] fake 1.618242 reg 0.154638 q -0.845395 172: [D] real 0.557873 fake 0.485305 q -0.831734 [G] fake 1.420617 reg 0.158682 q -0.079166 173: [D] real 0.297535 fake 0.456154 q -0.342472 [G] fake 1.058169 reg 0.186995 q -0.931712 174: [D] real 0.260578 fake 0.627228 q -0.581013 [G] fake 1.133204 reg 0.196000 q -0.778997 175: [D] real 0.286603 fake 0.596393 q -0.793501 [G] fake 1.768633 reg 0.186810 q -0.772054 176: [D] real 0.448309 fake 0.405023 q -0.794934 [G] fake 1.503221 reg 0.181935 q -0.899701 177: [D] real 0.361072 fake 0.511827 q -1.018397 [G] fake 1.707558 reg 0.177686 q -0.911727 178: [D] real 0.409645 fake 0.471448 q -0.736474 [G] fake 1.796332 reg 0.159705 q -0.347220 179: [D] real 0.732972 fake 0.089192 q -0.501272 [G] fake 2.394927 reg 0.153624 q -0.820980 180: [D] real 0.263928 fake 0.189646 q -0.788025 [G] fake 2.190970 reg 0.154208 q -0.774173 181: [D] real 0.070066 fake 0.232347 q -0.715063 [G] fake 2.152536 reg 0.187857 q -0.862223 182: [D] real 0.081567 fake 0.399424 q -0.858320 [G] fake 2.129161 reg 0.163103 q -0.898540 183: [D] real 0.107097 fake 0.860393 q -0.212941 [G] fake 1.753463 reg 0.194370 q -0.654063 184: [D] real 0.325115 fake 0.688954 q -0.658340 [G] fake 1.533870 reg 0.210164 q -0.583336 185: [D] real 0.950626 fake 0.380645 q -0.672334 [G] fake 1.819451 reg 0.197325 q -0.811858 186: [D] real 0.559435 fake 0.456979 q -0.710562 [G] fake 1.578009 reg 0.201581 q -0.812699 187: [D] real 0.389277 fake 0.601579 q -0.868285 [G] fake 1.766707 reg 0.189469 q -0.919317 188: [D] real 0.457596 fake 0.668966 q -0.712653 [G] fake 1.813855 reg 0.172944 q -0.930159 189: [D] real 1.122157 fake 0.457293 q -0.966136 [G] fake 1.669212 reg 0.167639 q -0.955080 190: [D] real 0.621869 fake 0.663305 q -0.645516 [G] fake 1.493407 reg 0.169039 q -0.672077 191: [D] real 0.263624 fake 1.049936 q -0.423778 [G] fake 1.480487 reg 0.169157 q -0.553272 192: [D] real 0.623585 fake 0.354170 q -0.607599 [G] fake 1.700614 reg 0.189422 q -0.543530 193: [D] real 0.850270 fake 0.499374 q -0.708906 [G] fake 1.342539 reg 0.185945 q -0.711809 194: [D] real 0.366806 fake 0.483162 q -0.787004 [G] fake 1.439575 reg 0.190259 q -0.900386 195: [D] real 0.332763 fake 0.629679 q -0.840518 [G] fake 1.823097 reg 0.189459 q -0.777243 196: [D] real 0.586912 fake 0.468720 q -1.000087 [G] fake 1.632961 reg 0.183253 q -0.981954 197: [D] real 0.617223 fake 0.412802 q -0.875779 [G] fake 1.565403 reg 0.176076 q -1.046356 198: [D] real 0.408841 fake 0.676116 q -1.017243 [G] fake 1.802686 reg 0.174198 q -1.058955 199: [D] real 0.494034 fake 0.585102 q -0.767353 [G] fake 1.877573 reg 0.174197 q -0.802177 200: [D] real 0.486504 fake 0.422234 q -0.774088 [G] fake 1.586223 reg 0.178410 q -0.867320 201: [D] real 0.569218 fake 0.495879 q -0.910300 [G] fake 1.453305 reg 0.174519 q -0.931885 202: [D] real 0.425385 fake 0.693199 q -0.993027 [G] fake 1.629206 reg 0.163880 q -1.147344 203: [D] real 0.584926 fake 0.698773 q -1.052680 [G] fake 2.092289 reg 0.170324 q -1.014533 204: [D] real 0.847685 fake 0.425146 q -1.158492 [G] fake 1.667479 reg 0.165669 q -1.155453 205: [D] real 0.541921 fake 0.606119 q -1.278375 [G] fake 1.464315 reg 0.175812 q -1.076050 206: [D] real 0.378487 fake 0.754230 q -1.191002 [G] fake 1.897093 reg 0.180908 q -1.018805 207: [D] real 0.786705 fake 0.401779 q -1.138337 [G] fake 1.390654 reg 0.183071 q -1.215994 208: [D] real 0.488997 fake 0.856426 q -1.164147 [G] fake 1.560180 reg 0.180549 q -0.352701 209: [D] real 0.414485 fake 0.143282 q 0.116483 [G] fake 2.308135 reg 0.153489 q 0.894769 210: [D] real 0.791623 fake 0.082891 q 0.121810 [G] fake 2.045639 reg 0.131675 q -0.611036 211: [D] real 0.159225 fake 0.196745 q -0.517456 [G] fake 1.918807 reg 0.143353 q -0.536624 212: [D] real 0.070445 fake 0.199352 q -0.582943 [G] fake 2.240221 reg 0.153021 q -0.622566 213: [D] real 0.043131 fake 0.174563 q -0.661611 [G] fake 2.246523 reg 0.141507 q -0.711075 214: [D] real 0.043824 fake 0.188989 q -0.827823 [G] fake 2.160186 reg 0.140674 q -0.726190 215: [D] real 0.044929 fake 0.375078 q -0.844923 [G] fake 2.041591 reg 0.153948 q -0.778921 216: [D] real 0.092407 fake 0.996320 q -0.568906 [G] fake 1.723639 reg 0.159930 q -0.786749 217: [D] real 0.303783 fake 0.423281 q -0.687701 [G] fake 1.577882 reg 0.176508 q -0.789670 218: [D] real 0.605584 fake 0.399700 q -0.682859 [G] fake 1.418545 reg 0.174511 q -0.812666 219: [D] real 0.425186 fake 0.664644 q -0.878901 [G] fake 1.286871 reg 0.173372 q -0.821737 220: [D] real 0.318283 fake 0.473053 q -0.946168 [G] fake 1.435802 reg 0.163573 q -0.928213 221: [D] real 0.357351 fake 0.456713 q -0.860409 [G] fake 1.409808 reg 0.162237 q -0.960886 222: [D] real 0.321783 fake 0.462360 q -0.932166 [G] fake 1.578986 reg 0.176128 q -1.077763 223: [D] real 0.425614 fake 0.504160 q -1.074022 [G] fake 1.232175 reg 0.178551 q -1.169410 224: [D] real 0.315275 fake 0.657427 q -1.146146 [G] fake 1.688043 reg 0.178284 q -0.996123 225: [D] real 0.348319 fake 0.407061 q -0.769110 [G] fake 1.682521 reg 0.177204 q -0.705174 226: [D] real 0.486660 fake 0.427022 q -0.462274 [G] fake 1.620193 reg 0.179665 q -0.494154 227: [D] real 0.483713 fake 0.487291 q -0.687896 [G] fake 1.570116 reg 0.179423 q -0.840340 228: [D] real 0.311039 fake 0.606739 q -0.911812 [G] fake 1.818091 reg 0.174518 q -1.002786 229: [D] real 0.453980 fake 0.313651 q -1.000875 [G] fake 1.639843 reg 0.165214 q -1.102536 230: [D] real 0.394061 fake 0.463557 q -0.950259 [G] fake 1.549970 reg 0.157326 q -1.018562 231: [D] real 0.469057 fake 0.312427 q -1.027573 [G] fake 1.801611 reg 0.168607 q -1.062141 232: [D] real 0.271077 fake 0.613803 q -0.627922 [G] fake 1.640943 reg 0.198766 q -0.560992 233: [D] real 0.206435 fake 0.359742 q -0.569240 [G] fake 1.886556 reg 0.191011 q -0.589881 234: [D] real 0.515490 fake 0.266945 q -0.739391 [G] fake 1.952120 reg 0.202333 q -0.817620 235: [D] real 0.397208 fake 0.679691 q -0.862016 [G] fake 1.979137 reg 0.192351 q -0.800645 236: [D] real 0.400889 fake 0.286162 q -0.927120 [G] fake 2.111108 reg 0.180551 q -0.941602 237: [D] real 0.373123 fake 0.224365 q -1.036293 [G] fake 2.352549 reg 0.175140 q -0.998028 238: [D] real 0.193978 fake 0.478606 q -0.974143 [G] fake 2.006686 reg 0.168198 q -1.079218 239: [D] real 0.224958 fake 0.080906 q -1.141151 [G] fake 3.147329 reg 0.171498 q -0.824057 240: [D] real 0.318862 fake 0.206866 q -1.034546 [G] fake 2.097729 reg 0.162782 q -0.964602 241: [D] real 0.101638 fake 0.753400 q -0.942146 [G] fake 2.206700 reg 0.161936 q -1.033158 242: [D] real 0.369955 fake 0.010845 q 0.159056 [G] fake 1.517223 reg 0.178974 q -0.345402 243: [D] real 0.223678 fake 0.586859 q -0.324083 [G] fake 1.110781 reg 0.188524 q -0.318636 244: [D] real 0.214494 fake 0.787482 q -0.374255 [G] fake 1.504704 reg 0.184277 q -0.341333 245: [D] real 0.340791 fake 0.468451 q -0.375497 [G] fake 1.555001 reg 0.177670 q -0.271757 246: [D] real 0.425240 fake 0.599963 q -0.477677 [G] fake 1.331756 reg 0.175542 q -0.471476 247: [D] real 0.392904 fake 0.659003 q -0.521527 [G] fake 1.304916 reg 0.167718 q -0.470568 248: [D] real 0.347176 fake 0.564037 q -0.705766 [G] fake 1.426940 reg 0.169626 q -0.676109 249: [D] real 0.278482 fake 0.464156 q -0.634570 [G] fake 1.517711 reg 0.167615 q -0.748319 250: [D] real 0.398629 fake 0.797213 q -0.839209 [G] fake 1.834175 reg 0.170347 q -0.635464 251: [D] real 0.289832 fake 0.307061 q -0.741741 [G] fake 1.572076 reg 0.171206 q -0.892280 252: [D] real 0.310638 fake 0.565109 q -0.892271 [G] fake 1.904063 reg 0.195529 q -0.812942 253: [D] real 0.239937 fake 0.317925 q -0.866001 [G] fake 2.092096 reg 0.202708 q -0.971743 254: [D] real 0.345387 fake 0.207933 q -0.873197 [G] fake 1.742245 reg 0.202094 q -0.806660 255: [D] real 0.134807 fake 0.322319 q -0.839402 [G] fake 1.854336 reg 0.208734 q -0.801090 256: [D] real 0.126718 fake 0.381376 q -0.782909 [G] fake 2.367402 reg 0.195367 q -0.634487 257: [D] real 0.146076 fake 0.125274 q -0.421200 [G] fake 2.204415 reg 0.195664 q -0.736207 258: [D] real 0.294505 fake 0.212146 q -0.856953 [G] fake 2.146280 reg 0.193623 q -0.847464 259: [D] real 0.203709 fake 0.259220 q -1.013733 [G] fake 1.981403 reg 0.187881 q -0.988741 260: [D] real 0.133654 fake 0.292103 q -1.028832 [G] fake 2.306002 reg 0.178669 q -1.004125 261: [D] real 0.192651 fake 0.171296 q -1.021533 [G] fake 2.185297 reg 0.175234 q -1.153042 262: [D] real 0.246044 fake 0.281807 q -1.043701 [G] fake 2.364691 reg 0.176147 q -1.060042 263: [D] real 0.212628 fake 0.199133 q -1.020985 [G] fake 2.525411 reg 0.164617 q -0.782530 264: [D] real 0.181502 fake 0.143028 q -1.076159 [G] fake 2.026202 reg 0.173901 q -1.040835 265: [D] real 0.087186 fake 0.278096 q -1.001667 [G] fake 2.347130 reg 0.183379 q -0.878565 266: [D] real 0.062752 fake 0.144715 q -0.699100 [G] fake 2.536963 reg 0.179629 q -1.082230 267: [D] real 0.063224 fake 0.118571 q 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fake 1.768010 reg 0.195666 q -1.183692 409: [D] real 0.521303 fake 0.540671 q -1.109700 [G] fake 1.550412 reg 0.173292 q -1.304809 410: [D] real 0.400568 fake 0.492276 q -1.262418 [G] fake 1.421175 reg 0.157941 q -1.436225 411: [D] real 0.386527 fake 0.481183 q -1.323238 [G] fake 1.509165 reg 0.137360 q -1.477507 412: [D] real 0.545413 fake 0.674720 q -1.346152 [G] fake 1.734227 reg 0.117121 q -1.404580 413: [D] real 0.752010 fake 0.750794 q -1.322700 [G] fake 1.648709 reg 0.099929 q -1.119342 414: [D] real 0.749021 fake 0.631194 q -1.453865 [G] fake 1.791239 reg 0.210895 q -1.508321 415: [D] real 0.672374 fake 0.349962 q -1.229887 [G] fake 1.801314 reg 0.204337 q -0.991480 416: [D] real 0.459560 fake 0.642567 q -1.002367 [G] fake 1.806863 reg 0.226479 q -1.342126 417: [D] real 0.517731 fake 0.445993 q -1.335984 [G] fake 1.604069 reg 0.245346 q -1.378793 418: [D] real 0.449239 fake 0.539421 q -1.362687 [G] fake 1.250012 reg 0.225423 q -1.380262 419: [D] real 0.467366 fake 0.610346 q -1.418554 [G] fake 1.425873 reg 0.216040 q -1.609614 420: [D] real 0.584381 fake 0.739430 q -1.243760 [G] fake 1.778856 reg 0.194991 q -0.759429 421: [D] real 0.686479 fake 0.486648 q -1.308187 [G] fake 1.909177 reg 0.169440 q -1.487011 422: [D] real 0.694140 fake 0.553595 q -1.486097 [G] fake 1.483725 reg 0.149889 q -1.466514 423: [D] real 0.555272 fake 0.529127 q -1.456444 [G] fake 1.374125 reg 0.130824 q -1.575219 424: [D] real 0.309444 fake 0.464759 q -1.508069 [G] fake 1.733922 reg 0.111103 q -1.429905 425: [D] real 0.372169 fake 0.665501 q -1.388209 [G] fake 2.136502 reg 0.143159 q -0.305924 426: [D] real 0.841549 fake 0.030695 q -0.485900 [G] fake 3.154605 reg 0.228497 q -1.074697 427: [D] real 0.577676 fake 0.060933 q -1.053382 [G] fake 2.865932 reg 0.231541 q -1.107838 428: [D] real 0.101495 fake 0.127293 q -1.010209 [G] fake 2.523548 reg 0.221672 q -1.077350 429: [D] real 0.053267 fake 0.468731 q -1.171559 [G] fake 2.167472 reg 0.224412 q -1.344616 430: [D] real 0.061854 fake 0.940322 q -0.859592 [G] fake 2.019461 reg 0.216242 q -1.041106 431: [D] real 0.261079 fake 0.117306 q -0.902248 [G] fake 2.713635 reg 0.211516 q -1.119087 432: [D] real 0.559906 fake 0.199107 q -1.088247 [G] fake 1.931207 reg 0.194939 q -1.123041 433: [D] real 0.198679 fake 0.780264 q -1.241093 [G] fake 1.614694 reg 0.170649 q -1.282053 434: [D] real 0.155219 fake 0.503043 q -1.248094 [G] fake 2.105291 reg 0.145290 q -1.330676 435: [D] real 0.513490 fake 0.474479 q -1.405019 [G] fake 1.757776 reg 0.122879 q -1.361636 436: [D] real 0.376866 fake 0.491382 q -1.418623 [G] fake 1.546366 reg 0.102088 q -1.560200 437: [D] real 0.546402 fake 0.452626 q -1.397195 [G] fake 1.801389 reg 0.195543 q -1.336879 438: [D] real 0.454353 fake 0.230549 q -1.386031 [G] fake 1.758412 reg 0.207535 q -1.479000 439: [D] real 0.150279 fake 0.795486 q -1.286400 [G] fake 2.320328 reg 0.218961 q -0.671317 440: [D] real 0.549875 fake 0.152246 q -1.553409 [G] fake 2.514274 reg 0.220151 q -1.498377 WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:36: The name tf.AUTO_REUSE is deprecated. Please use tf.compat.v1.AUTO_REUSE instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:188: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:131: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:133: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version. Instructions for updating: Use tf.keras.layers.Conv2D instead. WARNING:tensorflow:From C:\Users\USER\anaconda3\envs\zakaria\lib\site-packages\tensorflow_core\python\layers\convolutional.py:424: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version. Instructions for updating: Please use layer.call method instead. WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:134: batch_normalization (from tensorflow.python.layers.normalization) is deprecated and will be removed in a future version. Instructions for updating: Use keras.layers.BatchNormalization instead. In particular, tf.control_dependencies(tf.GraphKeys.UPDATE_OPS) should not be used (consult the tf.keras.layers.batch_normalization documentation). WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:136: dropout (from tensorflow.python.layers.core) is deprecated and will be removed in a future version. Instructions for updating: Use keras.layers.dropout instead. WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:163: flatten (from tensorflow.python.layers.core) is deprecated and will be removed in a future version. Instructions for updating: Use keras.layers.flatten instead. WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:164: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version. Instructions for updating: Use keras.layers.Dense instead. WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:59: conv2d_transpose (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version. Instructions for updating: Use tf.keras.layers.Conv2DTranspose instead. WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:111: The name tf.log is deprecated. Please use tf.math.log instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:112: The name tf.lgamma is deprecated. Please use tf.math.lgamma instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:120: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Deprecated in favor of operator or tf.math.divide. WARNING:tensorflow:From C:\Users\USER\anaconda3\envs\zakaria\lib\site-packages\tensorflow_core\python\ops\nn_impl.py:183: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.where in 2.0, which has the same broadcast rule as np.where WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:227: The name tf.train.AdamOptimizer is deprecated. Please use tf.compat.v1.train.AdamOptimizer instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:231: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:231: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:252: The name tf.global_variables_initializer is deprecated. Please use tf.compat.v1.global_variables_initializer instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:255: The name tf.summary.scalar is deprecated. Please use tf.compat.v1.summary.scalar instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:261: The name tf.summary.merge_all is deprecated. Please use tf.compat.v1.summary.merge_all instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:264: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.
WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:267: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
2024-01-03 22:11:32.802831: I tensorflow/core/platform/cpu_feature_guard.cc:145] This TensorFlow binary is optimized with Intel(R) MKL-DNN to use the following CPU instructions in performance critical operations: AVX AVX2 To enable them in non-MKL-DNN operations, rebuild TensorFlow with the appropriate compiler flags. 2024-01-03 22:11:32.809138: I tensorflow/core/common_runtime/process_util.cc:115] Creating new thread pool with default inter op setting: 12. Tune using inter_op_parallelism_threads for best performance. WARNING:tensorflow:From C:\Users\USER\OneDrive - Ministere de l'education nationale, de l'enseignement supérieur, de la formation professionnelle et de la recherche scientifique\Bureau\Nouveau dossier\beziergan\gan.py:272: The name tf.summary.FileWriter is deprecated. Please use tf.compat.v1.summary.FileWriter instead.
OMP: Info #212: KMP_AFFINITY: decoding x2APIC ids. OMP: Info #210: KMP_AFFINITY: Affinity capable, using global cpuid leaf 11 info OMP: Info #154: KMP_AFFINITY: Initial OS proc set respected: 0-11 OMP: Info #156: KMP_AFFINITY: 12 available OS procs OMP: Info #157: KMP_AFFINITY: Uniform topology OMP: Info #179: KMP_AFFINITY: 1 packages x 6 cores/pkg x 2 threads/core (6 total cores) OMP: Info #214: KMP_AFFINITY: OS proc to physical thread map: OMP: Info #171: KMP_AFFINITY: OS proc 0 maps to package 0 core 0 thread 0 OMP: Info #171: KMP_AFFINITY: OS proc 1 maps to package 0 core 0 thread 1 OMP: Info #171: KMP_AFFINITY: OS proc 2 maps to package 0 core 1 thread 0 OMP: Info #171: KMP_AFFINITY: OS proc 3 maps to package 0 core 1 thread 1 OMP: Info #171: KMP_AFFINITY: OS proc 4 maps to package 0 core 2 thread 0 OMP: Info #171: KMP_AFFINITY: OS proc 5 maps to package 0 core 2 thread 1 OMP: Info #171: KMP_AFFINITY: OS proc 6 maps to package 0 core 4 thread 0 OMP: Info #171: KMP_AFFINITY: OS proc 7 maps to package 0 core 4 thread 1 OMP: Info #171: KMP_AFFINITY: OS proc 8 maps to package 0 core 5 thread 0 OMP: Info #171: KMP_AFFINITY: OS proc 9 maps to package 0 core 5 thread 1 OMP: Info #171: KMP_AFFINITY: OS proc 10 maps to package 0 core 6 thread 0 OMP: Info #171: KMP_AFFINITY: OS proc 11 maps to package 0 core 6 thread 1 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 5876 thread 0 bound to OS proc set 0 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16304 thread 4 bound to OS proc set 8 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 18112 thread 2 bound to OS proc set 4 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 6692 thread 3 bound to OS proc set 6 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 11092 thread 1 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 19440 thread 5 bound to OS proc set 10 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 5948 thread 6 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 2300 thread 7 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 12228 thread 8 bound to OS proc set 5 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 7984 thread 9 bound to OS proc set 7 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 11756 thread 10 bound to OS proc set 9 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15012 thread 11 bound to OS proc set 11 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 5128 thread 12 bound to OS proc set 0 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 13004 thread 13 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 11796 thread 14 bound to OS proc set 4 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 10112 thread 15 bound to OS proc set 6 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 14728 thread 16 bound to OS proc set 8 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15988 thread 17 bound to OS proc set 10 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 9048 thread 18 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15224 thread 23 bound to OS proc set 11 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16528 thread 19 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16940 thread 21 bound to OS proc set 7 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 7404 thread 20 bound to OS proc set 5 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 11932 thread 22 bound to OS proc set 9 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 13140 thread 24 bound to OS proc set 0 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 3052 thread 25 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15584 thread 26 bound to OS proc set 4 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 14748 thread 27 bound to OS proc set 6 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 9380 thread 29 bound to OS proc set 10 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 12220 thread 28 bound to OS proc set 8 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 9612 thread 30 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 13428 thread 31 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 4288 thread 32 bound to OS proc set 5 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15996 thread 33 bound to OS proc set 7 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 2044 thread 34 bound to OS proc set 9 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 12812 thread 35 bound to OS proc set 11 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 12356 thread 36 bound to OS proc set 0 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16092 thread 37 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 17064 thread 38 bound to OS proc set 4 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 11360 thread 39 bound to OS proc set 6 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16220 thread 40 bound to OS proc set 8 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 14804 thread 41 bound to OS proc set 10 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 7572 thread 42 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 13488 thread 43 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 2564 thread 44 bound to OS proc set 5 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 10856 thread 45 bound to OS proc set 7 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 19276 thread 46 bound to OS proc set 9 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 2924 thread 47 bound to OS proc set 11 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16964 thread 48 bound to OS proc set 0 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15912 thread 49 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 10128 thread 50 bound to OS proc set 4 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 7712 thread 51 bound to OS proc set 6 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 9924 thread 52 bound to OS proc set 8 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 2012 thread 53 bound to OS proc set 10 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 812 thread 54 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 19288 thread 55 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 3280 thread 56 bound to OS proc set 5 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 4224 thread 57 bound to OS proc set 7 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 9016 thread 58 bound to OS proc set 9 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 4236 thread 59 bound to OS proc set 11 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16276 thread 60 bound to OS proc set 0 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 5332 thread 61 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 16108 thread 62 bound to OS proc set 4 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 8608 thread 63 bound to OS proc set 6 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15624 thread 64 bound to OS proc set 8 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 8988 thread 65 bound to OS proc set 10 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 15456 thread 66 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 2720 thread 67 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 6228 thread 68 bound to OS proc set 5 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 17236 thread 69 bound to OS proc set 7 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 4452 thread 70 bound to OS proc set 9 OMP: Info #250: KMP_AFFINITY: pid 18472 tid 3904 thread 71 bound to OS proc set 11 2024-01-04 00:03:17.673033: W tensorflow/core/framework/op_kernel.cc:1651] OP_REQUIRES failed at save_restore_v2_ops.cc:109 : Not found: Failed to create a NewWriteableFile: ./trained_gan/2_2/0/model.data-00000-of-00001.tempstate7771815659253205507 : Le chemin d’accès spécifié est introuvable. ; No such process.
how can i solve it please and what is the next step to do to find the results?