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  1. InceptionV4(
  2. (features): Sequential(
  3. (0): BasicConv2d(
  4. (conv): Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), bias=False)
  5. (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  6. (relu): ReLU(inplace=True)
  7. )
  8. (1): BasicConv2d(
  9. (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), bias=False)
  10. (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  11. (relu): ReLU(inplace=True)
  12. )
  13. (2): BasicConv2d(
  14. (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  15. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  16. (relu): ReLU(inplace=True)
  17. )
  18. (3): Mixed_3a(
  19. (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
  20. (conv): BasicConv2d(
  21. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(2, 2), bias=False)
  22. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  23. (relu): ReLU(inplace=True)
  24. )
  25. )
  26. (4): Mixed_4a(
  27. (branch0): Sequential(
  28. (0): BasicConv2d(
  29. (conv): Conv2d(160, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  30. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  31. (relu): ReLU(inplace=True)
  32. )
  33. (1): BasicConv2d(
  34. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), bias=False)
  35. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  36. (relu): ReLU(inplace=True)
  37. )
  38. )
  39. (branch1): Sequential(
  40. (0): BasicConv2d(
  41. (conv): Conv2d(160, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  42. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  43. (relu): ReLU(inplace=True)
  44. )
  45. (1): BasicConv2d(
  46. (conv): Conv2d(64, 64, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  47. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  48. (relu): ReLU(inplace=True)
  49. )
  50. (2): BasicConv2d(
  51. (conv): Conv2d(64, 64, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  52. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  53. (relu): ReLU(inplace=True)
  54. )
  55. (3): BasicConv2d(
  56. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), bias=False)
  57. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  58. (relu): ReLU(inplace=True)
  59. )
  60. )
  61. )
  62. (5): Mixed_5a(
  63. (conv): BasicConv2d(
  64. (conv): Conv2d(192, 192, kernel_size=(3, 3), stride=(2, 2), bias=False)
  65. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  66. (relu): ReLU(inplace=True)
  67. )
  68. (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
  69. )
  70. (6): Inception_A(
  71. (branch0): BasicConv2d(
  72. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  73. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  74. (relu): ReLU(inplace=True)
  75. )
  76. (branch1): Sequential(
  77. (0): BasicConv2d(
  78. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  79. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  80. (relu): ReLU(inplace=True)
  81. )
  82. (1): BasicConv2d(
  83. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  84. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  85. (relu): ReLU(inplace=True)
  86. )
  87. )
  88. (branch2): Sequential(
  89. (0): BasicConv2d(
  90. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  91. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  92. (relu): ReLU(inplace=True)
  93. )
  94. (1): BasicConv2d(
  95. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  96. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  97. (relu): ReLU(inplace=True)
  98. )
  99. (2): BasicConv2d(
  100. (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  101. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  102. (relu): ReLU(inplace=True)
  103. )
  104. )
  105. (branch3): Sequential(
  106. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  107. (1): BasicConv2d(
  108. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  109. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  110. (relu): ReLU(inplace=True)
  111. )
  112. )
  113. )
  114. (7): Inception_A(
  115. (branch0): BasicConv2d(
  116. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  117. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  118. (relu): ReLU(inplace=True)
  119. )
  120. (branch1): Sequential(
  121. (0): BasicConv2d(
  122. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  123. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  124. (relu): ReLU(inplace=True)
  125. )
  126. (1): BasicConv2d(
  127. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  128. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  129. (relu): ReLU(inplace=True)
  130. )
  131. )
  132. (branch2): Sequential(
  133. (0): BasicConv2d(
  134. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  135. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  136. (relu): ReLU(inplace=True)
  137. )
  138. (1): BasicConv2d(
  139. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  140. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  141. (relu): ReLU(inplace=True)
  142. )
  143. (2): BasicConv2d(
  144. (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  145. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  146. (relu): ReLU(inplace=True)
  147. )
  148. )
  149. (branch3): Sequential(
  150. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  151. (1): BasicConv2d(
  152. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  153. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  154. (relu): ReLU(inplace=True)
  155. )
  156. )
  157. )
  158. (8): Inception_A(
  159. (branch0): BasicConv2d(
  160. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  161. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  162. (relu): ReLU(inplace=True)
  163. )
  164. (branch1): Sequential(
  165. (0): BasicConv2d(
  166. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  167. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  168. (relu): ReLU(inplace=True)
  169. )
  170. (1): BasicConv2d(
  171. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  172. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  173. (relu): ReLU(inplace=True)
  174. )
  175. )
  176. (branch2): Sequential(
  177. (0): BasicConv2d(
  178. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  179. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  180. (relu): ReLU(inplace=True)
  181. )
  182. (1): BasicConv2d(
  183. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  184. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  185. (relu): ReLU(inplace=True)
  186. )
  187. (2): BasicConv2d(
  188. (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  189. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  190. (relu): ReLU(inplace=True)
  191. )
  192. )
  193. (branch3): Sequential(
  194. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  195. (1): BasicConv2d(
  196. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  197. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  198. (relu): ReLU(inplace=True)
  199. )
  200. )
  201. )
  202. (9): Inception_A(
  203. (branch0): BasicConv2d(
  204. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  205. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  206. (relu): ReLU(inplace=True)
  207. )
  208. (branch1): Sequential(
  209. (0): BasicConv2d(
  210. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  211. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  212. (relu): ReLU(inplace=True)
  213. )
  214. (1): BasicConv2d(
  215. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  216. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  217. (relu): ReLU(inplace=True)
  218. )
  219. )
  220. (branch2): Sequential(
  221. (0): BasicConv2d(
  222. (conv): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  223. (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  224. (relu): ReLU(inplace=True)
  225. )
  226. (1): BasicConv2d(
  227. (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  228. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  229. (relu): ReLU(inplace=True)
  230. )
  231. (2): BasicConv2d(
  232. (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  233. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  234. (relu): ReLU(inplace=True)
  235. )
  236. )
  237. (branch3): Sequential(
  238. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  239. (1): BasicConv2d(
  240. (conv): Conv2d(384, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
  241. (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  242. (relu): ReLU(inplace=True)
  243. )
  244. )
  245. )
  246. (10): Reduction_A(
  247. (branch0): BasicConv2d(
  248. (conv): Conv2d(384, 384, kernel_size=(3, 3), stride=(2, 2), bias=False)
  249. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  250. (relu): ReLU(inplace=True)
  251. )
  252. (branch1): Sequential(
  253. (0): BasicConv2d(
  254. (conv): Conv2d(384, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  255. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  256. (relu): ReLU(inplace=True)
  257. )
  258. (1): BasicConv2d(
  259. (conv): Conv2d(192, 224, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  260. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  261. (relu): ReLU(inplace=True)
  262. )
  263. (2): BasicConv2d(
  264. (conv): Conv2d(224, 256, kernel_size=(3, 3), stride=(2, 2), bias=False)
  265. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  266. (relu): ReLU(inplace=True)
  267. )
  268. )
  269. (branch2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
  270. )
  271. (11): Inception_B(
  272. (branch0): BasicConv2d(
  273. (conv): Conv2d(1024, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  274. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  275. (relu): ReLU(inplace=True)
  276. )
  277. (branch1): Sequential(
  278. (0): BasicConv2d(
  279. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  280. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  281. (relu): ReLU(inplace=True)
  282. )
  283. (1): BasicConv2d(
  284. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  285. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  286. (relu): ReLU(inplace=True)
  287. )
  288. (2): BasicConv2d(
  289. (conv): Conv2d(224, 256, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  290. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  291. (relu): ReLU(inplace=True)
  292. )
  293. )
  294. (branch2): Sequential(
  295. (0): BasicConv2d(
  296. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  297. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  298. (relu): ReLU(inplace=True)
  299. )
  300. (1): BasicConv2d(
  301. (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  302. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  303. (relu): ReLU(inplace=True)
  304. )
  305. (2): BasicConv2d(
  306. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  307. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  308. (relu): ReLU(inplace=True)
  309. )
  310. (3): BasicConv2d(
  311. (conv): Conv2d(224, 224, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  312. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  313. (relu): ReLU(inplace=True)
  314. )
  315. (4): BasicConv2d(
  316. (conv): Conv2d(224, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  317. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  318. (relu): ReLU(inplace=True)
  319. )
  320. )
  321. (branch3): Sequential(
  322. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  323. (1): BasicConv2d(
  324. (conv): Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  325. (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  326. (relu): ReLU(inplace=True)
  327. )
  328. )
  329. )
  330. (12): Inception_B(
  331. (branch0): BasicConv2d(
  332. (conv): Conv2d(1024, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  333. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  334. (relu): ReLU(inplace=True)
  335. )
  336. (branch1): Sequential(
  337. (0): BasicConv2d(
  338. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  339. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  340. (relu): ReLU(inplace=True)
  341. )
  342. (1): BasicConv2d(
  343. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  344. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  345. (relu): ReLU(inplace=True)
  346. )
  347. (2): BasicConv2d(
  348. (conv): Conv2d(224, 256, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  349. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  350. (relu): ReLU(inplace=True)
  351. )
  352. )
  353. (branch2): Sequential(
  354. (0): BasicConv2d(
  355. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  356. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  357. (relu): ReLU(inplace=True)
  358. )
  359. (1): BasicConv2d(
  360. (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  361. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  362. (relu): ReLU(inplace=True)
  363. )
  364. (2): BasicConv2d(
  365. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  366. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  367. (relu): ReLU(inplace=True)
  368. )
  369. (3): BasicConv2d(
  370. (conv): Conv2d(224, 224, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  371. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  372. (relu): ReLU(inplace=True)
  373. )
  374. (4): BasicConv2d(
  375. (conv): Conv2d(224, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  376. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  377. (relu): ReLU(inplace=True)
  378. )
  379. )
  380. (branch3): Sequential(
  381. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  382. (1): BasicConv2d(
  383. (conv): Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  384. (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  385. (relu): ReLU(inplace=True)
  386. )
  387. )
  388. )
  389. (13): Inception_B(
  390. (branch0): BasicConv2d(
  391. (conv): Conv2d(1024, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  392. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  393. (relu): ReLU(inplace=True)
  394. )
  395. (branch1): Sequential(
  396. (0): BasicConv2d(
  397. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  398. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  399. (relu): ReLU(inplace=True)
  400. )
  401. (1): BasicConv2d(
  402. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  403. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  404. (relu): ReLU(inplace=True)
  405. )
  406. (2): BasicConv2d(
  407. (conv): Conv2d(224, 256, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  408. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  409. (relu): ReLU(inplace=True)
  410. )
  411. )
  412. (branch2): Sequential(
  413. (0): BasicConv2d(
  414. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  415. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  416. (relu): ReLU(inplace=True)
  417. )
  418. (1): BasicConv2d(
  419. (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  420. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  421. (relu): ReLU(inplace=True)
  422. )
  423. (2): BasicConv2d(
  424. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  425. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  426. (relu): ReLU(inplace=True)
  427. )
  428. (3): BasicConv2d(
  429. (conv): Conv2d(224, 224, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  430. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  431. (relu): ReLU(inplace=True)
  432. )
  433. (4): BasicConv2d(
  434. (conv): Conv2d(224, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  435. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  436. (relu): ReLU(inplace=True)
  437. )
  438. )
  439. (branch3): Sequential(
  440. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  441. (1): BasicConv2d(
  442. (conv): Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  443. (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  444. (relu): ReLU(inplace=True)
  445. )
  446. )
  447. )
  448. (14): Inception_B(
  449. (branch0): BasicConv2d(
  450. (conv): Conv2d(1024, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  451. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  452. (relu): ReLU(inplace=True)
  453. )
  454. (branch1): Sequential(
  455. (0): BasicConv2d(
  456. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  457. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  458. (relu): ReLU(inplace=True)
  459. )
  460. (1): BasicConv2d(
  461. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  462. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  463. (relu): ReLU(inplace=True)
  464. )
  465. (2): BasicConv2d(
  466. (conv): Conv2d(224, 256, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  467. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  468. (relu): ReLU(inplace=True)
  469. )
  470. )
  471. (branch2): Sequential(
  472. (0): BasicConv2d(
  473. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  474. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  475. (relu): ReLU(inplace=True)
  476. )
  477. (1): BasicConv2d(
  478. (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  479. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  480. (relu): ReLU(inplace=True)
  481. )
  482. (2): BasicConv2d(
  483. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  484. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  485. (relu): ReLU(inplace=True)
  486. )
  487. (3): BasicConv2d(
  488. (conv): Conv2d(224, 224, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  489. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  490. (relu): ReLU(inplace=True)
  491. )
  492. (4): BasicConv2d(
  493. (conv): Conv2d(224, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  494. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  495. (relu): ReLU(inplace=True)
  496. )
  497. )
  498. (branch3): Sequential(
  499. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  500. (1): BasicConv2d(
  501. (conv): Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  502. (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  503. (relu): ReLU(inplace=True)
  504. )
  505. )
  506. )
  507. (15): Inception_B(
  508. (branch0): BasicConv2d(
  509. (conv): Conv2d(1024, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  510. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  511. (relu): ReLU(inplace=True)
  512. )
  513. (branch1): Sequential(
  514. (0): BasicConv2d(
  515. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  516. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  517. (relu): ReLU(inplace=True)
  518. )
  519. (1): BasicConv2d(
  520. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  521. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  522. (relu): ReLU(inplace=True)
  523. )
  524. (2): BasicConv2d(
  525. (conv): Conv2d(224, 256, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  526. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  527. (relu): ReLU(inplace=True)
  528. )
  529. )
  530. (branch2): Sequential(
  531. (0): BasicConv2d(
  532. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  533. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  534. (relu): ReLU(inplace=True)
  535. )
  536. (1): BasicConv2d(
  537. (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  538. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  539. (relu): ReLU(inplace=True)
  540. )
  541. (2): BasicConv2d(
  542. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  543. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  544. (relu): ReLU(inplace=True)
  545. )
  546. (3): BasicConv2d(
  547. (conv): Conv2d(224, 224, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  548. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  549. (relu): ReLU(inplace=True)
  550. )
  551. (4): BasicConv2d(
  552. (conv): Conv2d(224, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  553. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  554. (relu): ReLU(inplace=True)
  555. )
  556. )
  557. (branch3): Sequential(
  558. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  559. (1): BasicConv2d(
  560. (conv): Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  561. (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  562. (relu): ReLU(inplace=True)
  563. )
  564. )
  565. )
  566. (16): Inception_B(
  567. (branch0): BasicConv2d(
  568. (conv): Conv2d(1024, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  569. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  570. (relu): ReLU(inplace=True)
  571. )
  572. (branch1): Sequential(
  573. (0): BasicConv2d(
  574. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  575. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  576. (relu): ReLU(inplace=True)
  577. )
  578. (1): BasicConv2d(
  579. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  580. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  581. (relu): ReLU(inplace=True)
  582. )
  583. (2): BasicConv2d(
  584. (conv): Conv2d(224, 256, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  585. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  586. (relu): ReLU(inplace=True)
  587. )
  588. )
  589. (branch2): Sequential(
  590. (0): BasicConv2d(
  591. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  592. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  593. (relu): ReLU(inplace=True)
  594. )
  595. (1): BasicConv2d(
  596. (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  597. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  598. (relu): ReLU(inplace=True)
  599. )
  600. (2): BasicConv2d(
  601. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  602. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  603. (relu): ReLU(inplace=True)
  604. )
  605. (3): BasicConv2d(
  606. (conv): Conv2d(224, 224, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  607. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  608. (relu): ReLU(inplace=True)
  609. )
  610. (4): BasicConv2d(
  611. (conv): Conv2d(224, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  612. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  613. (relu): ReLU(inplace=True)
  614. )
  615. )
  616. (branch3): Sequential(
  617. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  618. (1): BasicConv2d(
  619. (conv): Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  620. (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  621. (relu): ReLU(inplace=True)
  622. )
  623. )
  624. )
  625. (17): Inception_B(
  626. (branch0): BasicConv2d(
  627. (conv): Conv2d(1024, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  628. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  629. (relu): ReLU(inplace=True)
  630. )
  631. (branch1): Sequential(
  632. (0): BasicConv2d(
  633. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  634. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  635. (relu): ReLU(inplace=True)
  636. )
  637. (1): BasicConv2d(
  638. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  639. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  640. (relu): ReLU(inplace=True)
  641. )
  642. (2): BasicConv2d(
  643. (conv): Conv2d(224, 256, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  644. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  645. (relu): ReLU(inplace=True)
  646. )
  647. )
  648. (branch2): Sequential(
  649. (0): BasicConv2d(
  650. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  651. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  652. (relu): ReLU(inplace=True)
  653. )
  654. (1): BasicConv2d(
  655. (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  656. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  657. (relu): ReLU(inplace=True)
  658. )
  659. (2): BasicConv2d(
  660. (conv): Conv2d(192, 224, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  661. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  662. (relu): ReLU(inplace=True)
  663. )
  664. (3): BasicConv2d(
  665. (conv): Conv2d(224, 224, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  666. (bn): BatchNorm2d(224, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  667. (relu): ReLU(inplace=True)
  668. )
  669. (4): BasicConv2d(
  670. (conv): Conv2d(224, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  671. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  672. (relu): ReLU(inplace=True)
  673. )
  674. )
  675. (branch3): Sequential(
  676. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  677. (1): BasicConv2d(
  678. (conv): Conv2d(1024, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  679. (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  680. (relu): ReLU(inplace=True)
  681. )
  682. )
  683. )
  684. (18): Reduction_B(
  685. (branch0): Sequential(
  686. (0): BasicConv2d(
  687. (conv): Conv2d(1024, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
  688. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  689. (relu): ReLU(inplace=True)
  690. )
  691. (1): BasicConv2d(
  692. (conv): Conv2d(192, 192, kernel_size=(3, 3), stride=(2, 2), bias=False)
  693. (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  694. (relu): ReLU(inplace=True)
  695. )
  696. )
  697. (branch1): Sequential(
  698. (0): BasicConv2d(
  699. (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  700. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  701. (relu): ReLU(inplace=True)
  702. )
  703. (1): BasicConv2d(
  704. (conv): Conv2d(256, 256, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)
  705. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  706. (relu): ReLU(inplace=True)
  707. )
  708. (2): BasicConv2d(
  709. (conv): Conv2d(256, 320, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)
  710. (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  711. (relu): ReLU(inplace=True)
  712. )
  713. (3): BasicConv2d(
  714. (conv): Conv2d(320, 320, kernel_size=(3, 3), stride=(2, 2), bias=False)
  715. (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  716. (relu): ReLU(inplace=True)
  717. )
  718. )
  719. (branch2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
  720. )
  721. (19): Inception_C(
  722. (branch0): BasicConv2d(
  723. (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  724. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  725. (relu): ReLU(inplace=True)
  726. )
  727. (branch1_0): BasicConv2d(
  728. (conv): Conv2d(1536, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  729. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  730. (relu): ReLU(inplace=True)
  731. )
  732. (branch1_1a): BasicConv2d(
  733. (conv): Conv2d(384, 256, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  734. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  735. (relu): ReLU(inplace=True)
  736. )
  737. (branch1_1b): BasicConv2d(
  738. (conv): Conv2d(384, 256, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  739. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  740. (relu): ReLU(inplace=True)
  741. )
  742. (branch2_0): BasicConv2d(
  743. (conv): Conv2d(1536, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  744. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  745. (relu): ReLU(inplace=True)
  746. )
  747. (branch2_1): BasicConv2d(
  748. (conv): Conv2d(384, 448, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  749. (bn): BatchNorm2d(448, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  750. (relu): ReLU(inplace=True)
  751. )
  752. (branch2_2): BasicConv2d(
  753. (conv): Conv2d(448, 512, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  754. (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  755. (relu): ReLU(inplace=True)
  756. )
  757. (branch2_3a): BasicConv2d(
  758. (conv): Conv2d(512, 256, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  759. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  760. (relu): ReLU(inplace=True)
  761. )
  762. (branch2_3b): BasicConv2d(
  763. (conv): Conv2d(512, 256, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  764. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  765. (relu): ReLU(inplace=True)
  766. )
  767. (branch3): Sequential(
  768. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  769. (1): BasicConv2d(
  770. (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  771. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  772. (relu): ReLU(inplace=True)
  773. )
  774. )
  775. )
  776. (20): Inception_C(
  777. (branch0): BasicConv2d(
  778. (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  779. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  780. (relu): ReLU(inplace=True)
  781. )
  782. (branch1_0): BasicConv2d(
  783. (conv): Conv2d(1536, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  784. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  785. (relu): ReLU(inplace=True)
  786. )
  787. (branch1_1a): BasicConv2d(
  788. (conv): Conv2d(384, 256, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  789. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  790. (relu): ReLU(inplace=True)
  791. )
  792. (branch1_1b): BasicConv2d(
  793. (conv): Conv2d(384, 256, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  794. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  795. (relu): ReLU(inplace=True)
  796. )
  797. (branch2_0): BasicConv2d(
  798. (conv): Conv2d(1536, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  799. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  800. (relu): ReLU(inplace=True)
  801. )
  802. (branch2_1): BasicConv2d(
  803. (conv): Conv2d(384, 448, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  804. (bn): BatchNorm2d(448, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  805. (relu): ReLU(inplace=True)
  806. )
  807. (branch2_2): BasicConv2d(
  808. (conv): Conv2d(448, 512, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  809. (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  810. (relu): ReLU(inplace=True)
  811. )
  812. (branch2_3a): BasicConv2d(
  813. (conv): Conv2d(512, 256, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  814. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  815. (relu): ReLU(inplace=True)
  816. )
  817. (branch2_3b): BasicConv2d(
  818. (conv): Conv2d(512, 256, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  819. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  820. (relu): ReLU(inplace=True)
  821. )
  822. (branch3): Sequential(
  823. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  824. (1): BasicConv2d(
  825. (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  826. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  827. (relu): ReLU(inplace=True)
  828. )
  829. )
  830. )
  831. (21): Inception_C(
  832. (branch0): BasicConv2d(
  833. (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  834. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  835. (relu): ReLU(inplace=True)
  836. )
  837. (branch1_0): BasicConv2d(
  838. (conv): Conv2d(1536, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  839. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  840. (relu): ReLU(inplace=True)
  841. )
  842. (branch1_1a): BasicConv2d(
  843. (conv): Conv2d(384, 256, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  844. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  845. (relu): ReLU(inplace=True)
  846. )
  847. (branch1_1b): BasicConv2d(
  848. (conv): Conv2d(384, 256, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  849. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  850. (relu): ReLU(inplace=True)
  851. )
  852. (branch2_0): BasicConv2d(
  853. (conv): Conv2d(1536, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
  854. (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  855. (relu): ReLU(inplace=True)
  856. )
  857. (branch2_1): BasicConv2d(
  858. (conv): Conv2d(384, 448, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  859. (bn): BatchNorm2d(448, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  860. (relu): ReLU(inplace=True)
  861. )
  862. (branch2_2): BasicConv2d(
  863. (conv): Conv2d(448, 512, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  864. (bn): BatchNorm2d(512, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  865. (relu): ReLU(inplace=True)
  866. )
  867. (branch2_3a): BasicConv2d(
  868. (conv): Conv2d(512, 256, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)
  869. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  870. (relu): ReLU(inplace=True)
  871. )
  872. (branch2_3b): BasicConv2d(
  873. (conv): Conv2d(512, 256, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)
  874. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  875. (relu): ReLU(inplace=True)
  876. )
  877. (branch3): Sequential(
  878. (0): AvgPool2d(kernel_size=3, stride=1, padding=1)
  879. (1): BasicConv2d(
  880. (conv): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  881. (bn): BatchNorm2d(256, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
  882. (relu): ReLU(inplace=True)
  883. )
  884. )
  885. )
  886. )
  887. (last_linear): Linear(in_features=1536, out_features=4, bias=True)
  888. (softmax): Softmax(dim=None)
  889. )
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