Linear regression with pytorch

''' def func(*args,**kwargs):print(args)#當(dāng)不知道傳入函數(shù)的參數(shù)的個(gè)數(shù)時(shí)可以用args，輸出的args是以元祖的形式print(kwargs)#不知道參數(shù)名稱和值的時(shí)候 傳入的是詞典func(1,2,4,5,x=3,y=5)(1, 2, 4, 5) {'x': 3, 'y': 5}'''class Foobar:def __init__(self):passdef __call__(self, *args, **kwargs):print('hello'+str(args[0]))#所以同理 在call這個(gè)函數(shù)里面會(huì)實(shí)現(xiàn)forward這個(gè)函數(shù)foobar=Foobar() foobar(1,2,3)#hello1 import os import os os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"import matplotlib.pyplot as plt import torch #數(shù)據(jù)集是個(gè)三乘一的矩陣 x_data=torch.Tensor([[1.0],[2.0],[3.0]]) y_data=torch.Tensor([[2.0],[4.0],[6.0]])loss_list=[] epoch_list=[]class LinearModel(torch.nn.Module):#init和forward必須重載 backward不一定要自己實(shí)現(xiàn) module對(duì)象會(huì)自動(dòng)根據(jù)計(jì)算圖去實(shí)現(xiàn)backwarddef __init__(self):super(LinearModel,self).__init__()self.linear=torch.nn.Linear(1,1)#確定w和b 可以直接完成y_hat=xw+b的計(jì)算def forward(self,x):#重載forwardy_pre=self.linear(x)#由init可知實(shí)現(xiàn)forward的計(jì)算return y_pre model =LinearModel()#實(shí)例化criterion=torch.nn.MSELoss(size_average=False)#MSEloss是損失函數(shù) 求loss optimizer=torch.optim.Adam(model.parameters(),lr=0.01)#優(yōu)化方法 分析優(yōu)化器對(duì)哪些tensor進(jìn)行優(yōu)化或用梯度下降更新w的值for epoch in range(100):epoch_list.append(epoch)y_pre=model(x_data)loss=criterion(y_pre,y_data)loss_list.append(loss.item())print(epoch,loss.item())optimizer.zero_grad()#在backward求導(dǎo)數(shù)前必須權(quán)重清零loss.backward()optimizer.step()#更新wprint('w=',model.linear.weight.item()) print('b=',model.linear.bias.item())x_test=torch.Tensor([4.0]) y_test=model(x_test) print('y_pre',y_test.data)plt.plot(epoch_list,loss_list) plt.ylabel('Loss') plt.xlabel('epoch') plt.show()

當(dāng)用Adam這個(gè)方法時(shí)且epoch=100時(shí)可以發(fā)現(xiàn)效果很不好 理想的w=2，b=0，y_pre=8

1 39.28014373779297 2 38.61161804199219 3 37.94915008544922 4 37.29282760620117 5 36.642757415771484 6 35.999019622802734 7 35.36170959472656 8 34.73091125488281 9 34.106685638427734 10 33.489131927490234 11 32.8783073425293 12 32.27427673339844 13 31.677106857299805 14 31.08685302734375 15 30.503564834594727 16 29.927288055419922 17 29.358070373535156 18 28.795944213867188 19 28.240938186645508 20 27.69308853149414 21 27.15241241455078 22 26.618927001953125 23 26.092649459838867 24 25.57358169555664 25 25.06173324584961 26 24.557104110717773 27 24.0596866607666 28 23.56947135925293 29 23.086450576782227 30 22.610599517822266 31 22.14190673828125 32 21.680343627929688 33 21.22588348388672 34 20.77849769592285 35 20.338153839111328 36 19.904815673828125 37 19.478439331054688 38 19.058988571166992 39 18.64641761779785 40 18.240680694580078 41 17.84173011779785 42 17.449512481689453 43 17.063976287841797 44 16.685068130493164 45 16.312732696533203 46 15.946911811828613 47 15.587545394897461 48 15.234573364257812 49 14.887937545776367 50 14.547571182250977 51 14.21341323852539 52 13.885400772094727 53 13.563462257385254 54 13.247535705566406 55 12.937556266784668 56 12.633451461791992 57 12.335158348083496 58 12.042604446411133 59 11.755722045898438 60 11.474445343017578 61 11.198698043823242 62 10.928417205810547 63 10.663528442382812 64 10.40396499633789 65 10.149651527404785 66 9.90052318572998 67 9.656505584716797 68 9.417531967163086 69 9.1835298538208 70 8.954428672790527 71 8.730156898498535 72 8.510649681091309 73 8.295831680297852 74 8.085638999938965 75 7.879994869232178 76 7.678836822509766 77 7.48209285736084 78 7.289695739746094 79 7.101578712463379 80 6.917667865753174 81 6.73790168762207 82 6.562210559844971 83 6.390528678894043 84 6.2227888107299805 85 6.058926582336426 86 5.898874759674072 87 5.742569923400879 88 5.589945316314697 89 5.4409379959106445 90 5.295485973358154 91 5.153524398803711 92 5.014989852905273 93 4.879822731018066 94 4.747958183288574 95 4.619339466094971 96 4.493905067443848 97 4.371591567993164 98 4.252344608306885 99 4.136101722717285 w= 1.2186882495880127 b= 0.59620201587677 y_pre tensor([5.4710])

epoch=1000時(shí)，

1 73.64485931396484 2 72.73275756835938 3 71.82670593261719 4 70.92681121826172 5 70.03315734863281 6 69.14585876464844 7 68.26498413085938 8 67.390625 9 66.52285766601562 10 65.66177368164062 11 64.80744934082031 12 63.95995330810547 13 63.11935806274414 14 62.28571319580078 15 61.45909881591797 16 60.639556884765625 17 59.827152252197266 18 59.021915435791016 19 58.22390365600586 20 57.43315124511719 21 56.649696350097656 22 55.873565673828125 23 55.10478591918945 24 54.343387603759766 25 53.589385986328125 26 52.842796325683594 27 52.10362243652344 28 51.371883392333984 29 50.64757537841797 30 49.93070983886719 31 49.221275329589844 32 48.51927947998047 33 47.82469177246094 34 47.13752365112305 35 46.45774841308594 36 45.78535842895508 37 45.120323181152344 38 44.46263122558594 39 43.812255859375 40 43.16917037963867 41 42.533348083496094 42 41.904762268066406 43 41.28337860107422 44 40.669158935546875 45 40.06208419799805 46 39.46210861206055 47 38.86919403076172 48 38.283302307128906 49 37.70439910888672 50 37.13243103027344 51 36.56737518310547 52 36.00917053222656 53 35.457786560058594 54 34.913177490234375 55 34.37528610229492 56 33.844078063964844 57 33.31950378417969 58 32.80152130126953 59 32.290069580078125 60 31.785110473632812 61 31.28660011291504 62 30.794479370117188 63 30.30870246887207 64 29.829219818115234 65 29.355979919433594 66 28.888935089111328 67 28.428035736083984 68 27.97323226928711 69 27.52446746826172 70 27.081693649291992 71 26.644861221313477 72 26.21392250061035 73 25.788818359375 74 25.36949920654297 75 24.95591926574707 76 24.548019409179688 77 24.145755767822266 78 23.749069213867188 79 23.35791778564453 80 22.972244262695312 81 22.59199333190918 82 22.217117309570312 83 21.847570419311523 84 21.483293533325195 85 21.12424087524414 86 20.770357131958008 87 20.421592712402344 88 20.07790184020996 89 19.739225387573242 90 19.405517578125 91 19.07672882080078 92 18.7528076171875 93 18.433700561523438 94 18.119361877441406 95 17.809741973876953 96 17.504789352416992 97 17.204452514648438 98 16.90868377685547 99 16.617433547973633 100 16.330656051635742 101 16.048295974731445 102 15.77031135559082 103 15.496650695800781 104 15.227263450622559 105 14.962108612060547 106 14.701131820678711 107 14.444283485412598 108 14.191522598266602 109 13.942800521850586 110 13.698066711425781 111 13.457279205322266 112 13.220386505126953 113 12.987346649169922 114 12.758111953735352 115 12.532634735107422 116 12.310872077941895 117 12.092779159545898 118 11.878307342529297 119 11.667415618896484 120 11.460057258605957 121 11.256189346313477 122 11.055767059326172 123 10.858745574951172 124 10.665084838867188 125 10.474738121032715 126 10.287666320800781 127 10.103822708129883 128 9.923168182373047 129 9.745658874511719 130 9.571252822875977 131 9.399909973144531 132 9.231588363647461 133 9.066245079040527 134 8.90384292602539 135 8.744339942932129 136 8.587697982788086 137 8.43387508392334 138 8.282833099365234 139 8.134530067443848 140 7.988931655883789 141 7.845998764038086 142 7.705689430236816 143 7.567971229553223 144 7.432806015014648 145 7.300151348114014 146 7.1699748039245605 147 7.042239189147949 148 6.916906833648682 149 6.793943405151367 150 6.673313140869141 151 6.554978370666504 152 6.438908576965332 153 6.325067043304443 154 6.213418483734131 155 6.103930473327637 156 5.996567726135254 157 5.891299247741699 158 5.788090705871582 159 5.6869096755981445 160 5.5877251625061035 161 5.49050235748291 162 5.395212173461914 163 5.301821708679199 164 5.21030330657959 165 5.1206207275390625 166 5.032748222351074 167 4.946656227111816 168 4.862311840057373 169 4.779687881469727 170 4.698754787445068 171 4.619483947753906 172 4.541847229003906 173 4.465815544128418 174 4.391365051269531 175 4.3184638023376465 176 4.247086524963379 177 4.177209377288818 178 4.108800888061523 179 4.041836738586426 180 3.976295232772827 181 3.9121463298797607 182 3.8493666648864746 183 3.787931442260742 184 3.727816104888916 185 3.6689963340759277 186 3.6114494800567627 187 3.555152416229248 188 3.5000805854797363 189 3.446211576461792 190 3.393522262573242 191 3.341992139816284 192 3.291597366333008 193 3.2423181533813477 194 3.194131851196289 195 3.147017478942871 196 3.100956916809082 197 3.0559258460998535 198 3.0119051933288574 199 2.9688799381256104 200 2.926823139190674 201 2.885720729827881 202 2.8455519676208496 203 2.80629825592041 204 2.76794171333313 205 2.730464458465576 206 2.6938467025756836 207 2.658074378967285 208 2.6231274604797363 209 2.5889902114868164 210 2.555644989013672 211 2.5230770111083984 212 2.4912686347961426 213 2.460205554962158 214 2.4298691749572754 215 2.400247573852539 216 2.371324062347412 217 2.3430824279785156 218 2.3155088424682617 219 2.2885916233062744 220 2.2623133659362793 221 2.236661672592163 222 2.211623191833496 223 2.187182664871216 224 2.163328170776367 225 2.140047550201416 226 2.1173276901245117 227 2.0951552391052246 228 2.0735201835632324 229 2.0524063110351562 230 2.031805992126465 231 2.0117058753967285 232 1.99209463596344 233 1.9729598760604858 234 1.9542920589447021 235 1.9360814094543457 236 1.918316125869751 237 1.9009848833084106 238 1.8840787410736084 239 1.8675884008407593 240 1.8515033721923828 241 1.8358139991760254 242 1.8205106258392334 243 1.8055843114852905 244 1.791025996208191 245 1.7768267393112183 246 1.7629787921905518 247 1.7494722604751587 248 1.7363014221191406 249 1.7234545946121216 250 1.7109260559082031 251 1.6987075805664062 252 1.686791181564331 253 1.6751692295074463 254 1.6638338565826416 255 1.652780294418335 256 1.6419994831085205 257 1.6314845085144043 258 1.6212302446365356 259 1.611228585243225 260 1.6014745235443115 261 1.5919599533081055 262 1.5826785564422607 263 1.573627233505249 264 1.564797043800354 265 1.5561835765838623 266 1.5477813482284546 267 1.539583444595337 268 1.531585454940796 269 1.5237834453582764 270 1.516170859336853 271 1.508741855621338 272 1.5014925003051758 273 1.4944188594818115 274 1.4875149726867676 275 1.4807758331298828 276 1.4741991758346558 277 1.4677786827087402 278 1.461510419845581 279 1.4553906917572021 280 1.4494149684906006 281 1.4435794353485107 282 1.4378809928894043 283 1.432314157485962 284 1.4268763065338135 285 1.4215648174285889 286 1.416374683380127 287 1.4113030433654785 288 1.4063470363616943 289 1.4015024900436401 290 1.3967658281326294 291 1.3921360969543457 292 1.3876075744628906 293 1.3831793069839478 294 1.3788474798202515 295 1.3746098279953003 296 1.3704642057418823 297 1.3664060831069946 298 1.3624346256256104 299 1.3585468530654907 300 1.3547394275665283 301 1.3510115146636963 302 1.3473589420318604 303 1.343780517578125 304 1.3402751684188843 305 1.3368384838104248 306 1.3334698677062988 307 1.3301657438278198 308 1.3269264698028564 309 1.3237487077713013 310 1.3206310272216797 311 1.317570686340332 312 1.3145663738250732 313 1.3116172552108765 314 1.3087208271026611 315 1.3058750629425049 316 1.30307936668396 317 1.3003323078155518 318 1.297631025314331 319 1.29497492313385 320 1.2923626899719238 321 1.289792776107788 322 1.2872636318206787 323 1.2847744226455688 324 1.2823233604431152 325 1.2799098491668701 326 1.2775323390960693 327 1.2751896381378174 328 1.2728803157806396 329 1.2706034183502197 330 1.2683587074279785 331 1.2661442756652832 332 1.2639589309692383 333 1.2618035078048706 334 1.2596746683120728 335 1.257573127746582 336 1.2554970979690552 337 1.253446102142334 338 1.2514185905456543 339 1.2494145631790161 340 1.247434139251709 341 1.2454745769500732 342 1.243537187576294 343 1.2416186332702637 344 1.2397209405899048 345 1.2378422021865845 346 1.2359806299209595 347 1.2341375350952148 348 1.2323123216629028 349 1.2305020093917847 350 1.2287085056304932 351 1.2269303798675537 352 1.2251675128936768 353 1.2234179973602295 354 1.221683144569397 355 1.2199612855911255 356 1.218252182006836 357 1.2165557146072388 358 1.2148706912994385 359 1.2131974697113037 360 1.211535096168518 361 1.2098841667175293 362 1.2082427740097046 363 1.2066116333007812 364 1.204990029335022 365 1.2033777236938477 366 1.2017743587493896 367 1.2001795768737793 368 1.1985926628112793 369 1.1970137357711792 370 1.195443034172058 371 1.1938796043395996 372 1.192323088645935 373 1.1907728910446167 374 1.1892297267913818 375 1.187692642211914 376 1.1861613988876343 377 1.1846365928649902 378 1.183117389678955 379 1.1816024780273438 380 1.180093765258789 381 1.1785897016525269 382 1.177091121673584 383 1.1755962371826172 384 1.1741057634353638 385 1.1726197004318237 386 1.171137809753418 387 1.1696598529815674 388 1.1681857109069824 389 1.1667149066925049 390 1.165247917175293 391 1.1637840270996094 392 1.1623235940933228 393 1.1608657836914062 394 1.1594107151031494 395 1.157958745956421 396 1.1565097570419312 397 1.1550630331039429 398 1.1536190509796143 399 1.152176856994629 400 1.1507372856140137 401 1.1493000984191895 402 1.147864580154419 403 1.1464306116104126 404 1.1449998617172241 405 1.1435694694519043 406 1.1421420574188232 407 1.1407157182693481 408 1.1392905712127686 409 1.1378672122955322 410 1.13644540309906 411 1.1350250244140625 412 1.133606195449829 413 1.132188081741333 414 1.1307710409164429 415 1.1293559074401855 416 1.1279412508010864 417 1.1265281438827515 418 1.1251156330108643 419 1.123704433441162 420 1.1222939491271973 421 1.1208841800689697 422 1.119475245475769 423 1.1180672645568848 424 1.1166596412658691 425 1.1152534484863281 426 1.113847017288208 427 1.112441897392273 428 1.1110377311706543 429 1.1096336841583252 430 1.1082301139831543 431 1.106826901435852 432 1.1054246425628662 433 1.1040222644805908 434 1.1026207208633423 435 1.101219892501831 436 1.0998187065124512 437 1.0984185934066772 438 1.0970187187194824 439 1.0956188440322876 440 1.09421968460083 441 1.0928208827972412 442 1.0914225578308105 443 1.0900238752365112 444 1.0886261463165283 445 1.0872280597686768 446 1.0858312845230103 447 1.0844335556030273 448 1.0830364227294922 449 1.0816398859024048 450 1.0802432298660278 451 1.07884681224823 452 1.0774507522583008 453 1.0760548114776611 454 1.074658989906311 455 1.0732632875442505 456 1.071867823600769 457 1.070472240447998 458 1.0690771341323853 459 1.0676822662353516 460 1.0662869215011597 461 1.0648924112319946 462 1.0634981393814087 463 1.0621037483215332 464 1.060708999633789 465 1.0593152046203613 466 1.0579206943511963 467 1.0565274953842163 468 1.0551329851150513 469 1.0537396669387817 470 1.0523457527160645 471 1.050952672958374 472 1.0495595932006836 473 1.0481665134429932 474 1.046773076057434 475 1.045379877090454 476 1.0439872741699219 477 1.0425946712493896 478 1.0412020683288574 479 1.0398097038269043 480 1.038417100906372 481 1.0370252132415771 482 1.0356335639953613 483 1.0342413187026978 484 1.032849669456482 485 1.0314579010009766 486 1.0300660133361816 487 1.0286747217178345 488 1.0272836685180664 489 1.025892734527588 490 1.0245015621185303 491 1.0231103897094727 492 1.0217199325561523 493 1.0203297138214111 494 1.0189392566680908 495 1.0175485610961914 496 1.016158938407898 497 1.0147688388824463 498 1.0133793354034424 499 1.0119895935058594 500 1.0106004476547241 501 1.0092110633850098 502 1.007822036743164 503 1.0064334869384766 504 1.005044937133789 505 1.0036563873291016 506 1.0022687911987305 507 1.0008801221847534 508 0.9994925856590271 509 0.9981048107147217 510 0.9967176914215088 511 0.9953306317329407 512 0.9939436912536621 513 0.9925569891929626 514 0.991170346736908 515 0.9897842407226562 516 0.9883979558944702 517 0.9870126247406006 518 0.9856271743774414 519 0.9842422008514404 520 0.9828568696975708 521 0.9814721345901489 522 0.9800871014595032 523 0.9787031412124634 524 0.977319061756134 525 0.9759358167648315 526 0.9745523929595947 527 0.9731693267822266 528 0.9717866778373718 529 0.9704040288925171 530 0.9690216183662415 531 0.9676398634910583 532 0.9662580490112305 533 0.9648770093917847 534 0.9634960889816284 535 0.9621152877807617 536 0.9607350826263428 537 0.9593547582626343 538 0.9579752683639526 539 0.9565959572792053 540 0.9552173614501953 541 0.9538382291793823 542 0.9524598717689514 543 0.9510821104049683 544 0.949704647064209 545 0.9483271837234497 546 0.9469503164291382 547 0.9455736875534058 548 0.9441971778869629 549 0.9428222179412842 550 0.9414463639259338 551 0.9400722980499268 552 0.9386969804763794 553 0.9373229742050171 554 0.9359492063522339 555 0.9345760345458984 556 0.9332026243209839 557 0.9318302869796753 558 0.9304581880569458 559 0.9290866851806641 560 0.9277158975601196 561 0.9263440370559692 562 0.9249739646911621 563 0.9236034154891968 564 0.9222346544265747 565 0.9208654165267944 566 0.9194968938827515 567 0.9181283712387085 568 0.9167606830596924 569 0.915393590927124 570 0.91402667760849 571 0.9126612544059753 572 0.9112955331802368 573 0.9099300503730774 574 0.9085650444030762 575 0.9072009325027466 576 0.9058372378349304 577 0.904474139213562 578 0.9031108021736145 579 0.901748776435852 580 0.9003862142562866 581 0.8990248441696167 582 0.8976646661758423 583 0.8963040113449097 584 0.8949441909790039 585 0.8935853838920593 586 0.8922266364097595 587 0.8908682465553284 588 0.8895108699798584 589 0.888153612613678 590 0.8867970705032349 591 0.8854413032531738 592 0.8840858936309814 593 0.8827314376831055 594 0.8813769817352295 595 0.8800232410430908 596 0.8786699771881104 597 0.877317488193512 598 0.8759661912918091 599 0.8746145367622375 600 0.873263955116272 601 0.8719136714935303 602 0.8705644607543945 603 0.8692153096199036 604 0.8678669929504395 605 0.8665192127227783 606 0.8651715517044067 607 0.8638256788253784 608 0.8624793887138367 609 0.8611346483230591 610 0.8597896099090576 611 0.8584458827972412 612 0.8571021556854248 613 0.8557597398757935 614 0.8544173836708069 615 0.8530756235122681 616 0.8517352342605591 617 0.8503947257995605 618 0.8490554094314575 619 0.8477169275283813 620 0.84637850522995 621 0.8450407981872559 622 0.8437040448188782 623 0.8423681855201721 624 0.8410332202911377 625 0.839698314666748 626 0.8383642435073853 627 0.8370309472084045 628 0.8356978297233582 629 0.8343659043312073 630 0.8330344557762146 631 0.8317039608955383 632 0.8303738236427307 633 0.8290453553199768 634 0.8277170062065125 635 0.8263890743255615 636 0.8250622153282166 637 0.8237359523773193 638 0.822409987449646 639 0.8210856318473816 640 0.8197613954544067 641 0.8184381723403931 642 0.817115843296051 643 0.8157939314842224 644 0.814472496509552 645 0.8131524324417114 646 0.8118323087692261 647 0.8105140328407288 648 0.8091951012611389 649 0.807878315448761 650 0.8065618276596069 651 0.8052458763122559 652 0.8039308786392212 653 0.8026171922683716 654 0.8013036251068115 655 0.7999911308288574 656 0.7986792325973511 657 0.7973682284355164 658 0.7960574626922607 659 0.7947486042976379 660 0.7934401035308838 661 0.7921321988105774 662 0.7908249497413635 663 0.7895179986953735 664 0.7882125973701477 665 0.7869082093238831 666 0.7856042385101318 667 0.7843017578125 668 0.7829991579055786 669 0.78169846534729 670 0.7803975343704224 671 0.7790980339050293 672 0.7777993679046631 673 0.7765015363693237 674 0.7752041220664978 675 0.7739077210426331 676 0.7726120948791504 677 0.7713176608085632 678 0.7700244784355164 679 0.768731415271759 680 0.7674394845962524 681 0.7661483883857727 682 0.7648578882217407 683 0.7635684609413147 684 0.7622798085212708 685 0.7609926462173462 686 0.7597064971923828 687 0.7584200501441956 688 0.757135272026062 689 0.7558512687683105 690 0.7545679807662964 691 0.7532857656478882 692 0.7520039081573486 693 0.7507238984107971 694 0.7494442462921143 695 0.7481656670570374 696 0.746887743473053 697 0.7456105351448059 698 0.7443349361419678 699 0.7430600523948669 700 0.7417857646942139 701 0.7405126094818115 702 0.7392405867576599 703 0.7379692792892456 704 0.7366986274719238 705 0.7354295253753662 706 0.734160840511322 707 0.7328929901123047 708 0.7316263318061829 709 0.7303608655929565 710 0.7290961742401123 711 0.7278319597244263 712 0.7265700101852417 713 0.7253075838088989 714 0.7240464687347412 715 0.7227869033813477 716 0.7215279340744019 717 0.7202697396278381 718 0.7190126180648804 719 0.7177562713623047 720 0.7165012359619141 721 0.7152470350265503 722 0.713994026184082 723 0.7127417325973511 724 0.7114908695220947 725 0.7102402448654175 726 0.708991289138794 727 0.7077429294586182 728 0.7064957618713379 729 0.7052496075630188 730 0.7040042281150818 731 0.7027602791786194 732 0.7015162706375122 733 0.7002747058868408 734 0.6990330219268799 735 0.6977927088737488 736 0.6965535283088684 737 0.6953158378601074 738 0.6940786242485046 739 0.6928420066833496 740 0.6916073560714722 741 0.6903733611106873 742 0.6891401410102844 743 0.687907874584198 744 0.6866771578788757 745 0.6854472160339355 746 0.6842181086540222 747 0.6829899549484253 748 0.6817634105682373 749 0.6805371046066284 750 0.6793124079704285 751 0.6780890822410583 752 0.6768659949302673 753 0.6756446361541748 754 0.6744242310523987 755 0.673204243183136 756 0.67198646068573 757 0.6707682013511658 758 0.6695523262023926 759 0.6683372259140015 760 0.6671223044395447 761 0.6659096479415894 762 0.6646977066993713 763 0.6634865999221802 764 0.6622768640518188 765 0.6610680222511292 766 0.6598601937294006 767 0.6586534976959229 768 0.657447874546051 769 0.6562433242797852 770 0.65503990650177 771 0.6538375616073608 772 0.6526364088058472 773 0.6514362692832947 774 0.6502371430397034 775 0.6490389108657837 776 0.6478418111801147 777 0.6466465592384338 778 0.6454519629478455 779 0.6442580819129944 780 0.6430658102035522 781 0.6418745517730713 782 0.6406842470169067 783 0.6394948363304138 784 0.6383069157600403 785 0.6371200680732727 786 0.6359342932701111 787 0.6347496509552002 788 0.63356614112854 789 0.6323837041854858 790 0.6312023401260376 791 0.6300224661827087 792 0.6288437247276306 793 0.6276652812957764 794 0.6264888048171997 795 0.625313401222229 796 0.6241387128829956 797 0.6229650974273682 798 0.6217929124832153 799 0.6206222176551819 800 0.6194519400596619 801 0.6182833909988403 802 0.6171156167984009 803 0.6159493327140808 804 0.614783763885498 805 0.6136201620101929 806 0.6124567985534668 807 0.6112948060035706 808 0.6101344227790833 809 0.6089747548103333 810 0.6078166365623474 811 0.6066591143608093 812 0.6055030822753906 813 0.6043481230735779 814 0.6031947135925293 815 0.6020423173904419 816 0.6008907556533813 817 0.5997405052185059 818 0.5985913872718811 819 0.5974433422088623 820 0.5962969064712524 821 0.5951517820358276 822 0.5940070748329163 823 0.592863917350769 824 0.5917217135429382 825 0.5905809998512268 826 0.5894414186477661 827 0.5883033275604248 828 0.5871662497520447 829 0.5860303640365601 830 0.5848957300186157 831 0.5837616324424744 832 0.5826293230056763 833 0.5814980864524841 834 0.580367922782898 835 0.5792388916015625 836 0.5781115889549255 837 0.5769854784011841 838 0.5758597254753113 839 0.5747359991073608 840 0.573613166809082 841 0.5724914073944092 842 0.5713709592819214 843 0.5702520608901978 844 0.5691338777542114 845 0.5680175423622131 846 0.5669018030166626 847 0.5657879710197449 848 0.5646744966506958 849 0.5635623931884766 850 0.5624518394470215 851 0.561342716217041 852 0.5602341890335083 853 0.5591272711753845 854 0.558022141456604 855 0.5569171905517578 856 0.5558139085769653 857 0.5547115802764893 858 0.5536109209060669 859 0.5525111556053162 860 0.5514127612113953 861 0.5503158569335938 862 0.5492197275161743 863 0.5481252670288086 864 0.5470314621925354 865 0.5459392666816711 866 0.5448483824729919 867 0.5437586307525635 868 0.5426698923110962 869 0.5415827035903931 870 0.540496826171875 871 0.5394120812416077 872 0.5383283495903015 873 0.5372465252876282 874 0.5361652970314026 875 0.5350855588912964 876 0.53400719165802 877 0.5329298973083496 878 0.5318533778190613 879 0.5307788848876953 880 0.5297055244445801 881 0.5286327600479126 882 0.5275626182556152 883 0.5264925360679626 884 0.5254241228103638 885 0.5243571996688843 886 0.5232908129692078 887 0.5222263336181641 888 0.5211629271507263 889 0.520100474357605 890 0.5190395712852478 891 0.5179795622825623 892 0.5169217586517334 893 0.5158646106719971 894 0.5148086547851562 895 0.5137540698051453 896 0.5127005577087402 897 0.5116487145423889 898 0.5105979442596436 899 0.509548544883728 900 0.5084999799728394 901 0.5074533820152283 902 0.5064074993133545 903 0.5053631067276001 904 0.5043204426765442 905 0.5032788515090942 906 0.5022381544113159 907 0.5011982917785645 908 0.5001605153083801 909 0.49912387132644653 910 0.4980884790420532 911 0.4970548152923584 912 0.4960212707519531 913 0.4949900507926941 914 0.49395957589149475 915 0.49293094873428345 916 0.491903156042099 917 0.4908769130706787 918 0.48985159397125244 919 0.48882779479026794 920 0.4878048896789551 921 0.4867837429046631 922 0.48576343059539795 923 0.4847453832626343 924 0.48372775316238403 925 0.4827115535736084 926 0.4816969633102417 927 0.48068317770957947 928 0.4796709716320038 929 0.47865986824035645 930 0.47765088081359863 931 0.47664231061935425 932 0.4756356477737427 933 0.47463005781173706 934 0.47362545132637024 935 0.472622275352478 936 0.47162050008773804 937 0.4706196188926697 938 0.4696205258369446 939 0.4686221480369568 940 0.46762579679489136 941 0.46663016080856323 942 0.4656361937522888 943 0.46464356780052185 944 0.46365243196487427 945 0.4626621603965759 946 0.4616733193397522 947 0.46068620681762695 948 0.4596996605396271 949 0.45871496200561523 950 0.4577317535877228 951 0.4567490220069885 952 0.4557684063911438 953 0.4547886550426483 954 0.45381033420562744 955 0.452833354473114 956 0.4518572688102722 957 0.45088309049606323 958 0.44991010427474976 959 0.448938250541687 960 0.4479675889015198 961 0.446998655796051 962 0.44603046774864197 963 0.4450642168521881 964 0.4440993070602417 965 0.4431350827217102 966 0.44217222929000854 967 0.4412113428115845 968 0.4402511715888977 969 0.43929266929626465 970 0.4383354187011719 971 0.43737953901290894 972 0.4364246726036072 973 0.4354711174964905 974 0.4345192313194275 975 0.43356844782829285 976 0.43261921405792236 977 0.43167102336883545 978 0.43072405457496643 979 0.4297788441181183 980 0.4288349151611328 981 0.42789143323898315 982 0.426950067281723 983 0.4260098338127136 984 0.42507117986679077 985 0.42413392663002014 986 0.4231972098350525 987 0.4222624897956848 988 0.4213288426399231 989 0.4203967750072479 990 0.41946542263031006 991 0.4185360074043274 992 0.4176079034805298 993 0.4166807234287262 994 0.4157549738883972 995 0.41483068466186523 996 0.4139077961444855 997 0.41298624873161316 998 0.41206538677215576 999 0.4111466407775879 w= 1.5620301961898804 b= 0.970091700553894 y_pre tensor([7.2182])

當(dāng)用SGD且epcho=100

當(dāng)用SGD且epcho=1000

總結(jié)

以上是生活随笔為你收集整理的PyTorch深度学习实践05的全部?jī)?nèi)容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網(wǎng)站內(nèi)容還不錯(cuò)，歡迎將生活随笔推薦給好友。