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  1. name: "AlexNet"
  2. layer {
  3. name: "data"
  4. type: "Data"
  5. top: "data"
  6. top: "label"
  7. include {
  8. phase: TRAIN
  9. }
  10. transform_param {
  11. mirror: true
  12. crop_size: 227
  13. mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
  14. }
  15. data_param {
  16. source: "examples/imagenet/ilsvrc12_train_lmdb"
  17. batch_size: 256
  18. backend: LMDB
  19. }
  20. }
  21. layer {
  22. name: "data"
  23. type: "Data"
  24. top: "data"
  25. top: "label"
  26. include {
  27. phase: TEST
  28. }
  29. transform_param {
  30. mirror: false
  31. crop_size: 227
  32. mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
  33. }
  34. data_param {
  35. source: "examples/imagenet/ilsvrc12_val_lmdb"
  36. batch_size: 50
  37. backend: LMDB
  38. }
  39. }
  40. layer {
  41. name: "conv1"
  42. type: "Convolution"
  43. bottom: "data"
  44. top: "conv1"
  45. param {
  46. lr_mult: 1
  47. decay_mult: 1
  48. }
  49. param {
  50. lr_mult: 2
  51. decay_mult: 0
  52. }
  53. convolution_param {
  54. num_output: 96
  55. kernel_size: 11
  56. stride: 4
  57. weight_filler {
  58. type: "gaussian"
  59. std: 0.01
  60. }
  61. bias_filler {
  62. type: "constant"
  63. value: 0
  64. }
  65. }
  66. }
  67. layer {
  68. name: "relu1"
  69. type: "ReLU"
  70. bottom: "conv1"
  71. top: "conv1"
  72. }
  73. layer {
  74. name: "norm1"
  75. type: "LRN"
  76. bottom: "conv1"
  77. top: "norm1"
  78. lrn_param {
  79. local_size: 5
  80. alpha: 0.0001
  81. beta: 0.75
  82. }
  83. }
  84. layer {
  85. name: "pool1"
  86. type: "Pooling"
  87. bottom: "norm1"
  88. top: "pool1"
  89. pooling_param {
  90. pool: MAX
  91. kernel_size: 3
  92. stride: 2
  93. }
  94. }
  95. layer {
  96. name: "conv2"
  97. type: "Convolution"
  98. bottom: "pool1"
  99. top: "conv2"
  100. param {
  101. lr_mult: 1
  102. decay_mult: 1
  103. }
  104. param {
  105. lr_mult: 2
  106. decay_mult: 0
  107. }
  108. convolution_param {
  109. num_output: 256
  110. pad: 2
  111. kernel_size: 5
  112. group: 2
  113. weight_filler {
  114. type: "gaussian"
  115. std: 0.01
  116. }
  117. bias_filler {
  118. type: "constant"
  119. value: 0.1
  120. }
  121. }
  122. }
  123. layer {
  124. name: "relu2"
  125. type: "ReLU"
  126. bottom: "conv2"
  127. top: "conv2"
  128. }
  129. layer {
  130. name: "norm2"
  131. type: "LRN"
  132. bottom: "conv2"
  133. top: "norm2"
  134. lrn_param {
  135. local_size: 5
  136. alpha: 0.0001
  137. beta: 0.75
  138. }
  139. }
  140. layer {
  141. name: "pool2"
  142. type: "Pooling"
  143. bottom: "norm2"
  144. top: "pool2"
  145. pooling_param {
  146. pool: MAX
  147. kernel_size: 3
  148. stride: 2
  149. }
  150. }
  151. layer {
  152. name: "conv3"
  153. type: "Convolution"
  154. bottom: "pool2"
  155. top: "conv3"
  156. param {
  157. lr_mult: 1
  158. decay_mult: 1
  159. }
  160. param {
  161. lr_mult: 2
  162. decay_mult: 0
  163. }
  164. convolution_param {
  165. num_output: 384
  166. pad: 1
  167. kernel_size: 3
  168. weight_filler {
  169. type: "gaussian"
  170. std: 0.01
  171. }
  172. bias_filler {
  173. type: "constant"
  174. value: 0
  175. }
  176. }
  177. }
  178. layer {
  179. name: "relu3"
  180. type: "ReLU"
  181. bottom: "conv3"
  182. top: "conv3"
  183. }
  184. layer {
  185. name: "conv4"
  186. type: "Convolution"
  187. bottom: "conv3"
  188. top: "conv4"
  189. param {
  190. lr_mult: 1
  191. decay_mult: 1
  192. }
  193. param {
  194. lr_mult: 2
  195. decay_mult: 0
  196. }
  197. convolution_param {
  198. num_output: 384
  199. pad: 1
  200. kernel_size: 3
  201. group: 2
  202. weight_filler {
  203. type: "gaussian"
  204. std: 0.01
  205. }
  206. bias_filler {
  207. type: "constant"
  208. value: 0.1
  209. }
  210. }
  211. }
  212. layer {
  213. name: "relu4"
  214. type: "ReLU"
  215. bottom: "conv4"
  216. top: "conv4"
  217. }
  218. layer {
  219. name: "conv5"
  220. type: "Convolution"
  221. bottom: "conv4"
  222. top: "conv5"
  223. param {
  224. lr_mult: 1
  225. decay_mult: 1
  226. }
  227. param {
  228. lr_mult: 2
  229. decay_mult: 0
  230. }
  231. convolution_param {
  232. num_output: 256
  233. pad: 1
  234. kernel_size: 3
  235. group: 2
  236. weight_filler {
  237. type: "gaussian"
  238. std: 0.01
  239. }
  240. bias_filler {
  241. type: "constant"
  242. value: 0.1
  243. }
  244. }
  245. }
  246. layer {
  247. name: "relu5"
  248. type: "ReLU"
  249. bottom: "conv5"
  250. top: "conv5"
  251. }
  252. layer {
  253. name: "pool5"
  254. type: "Pooling"
  255. bottom: "conv5"
  256. top: "pool5"
  257. pooling_param {
  258. pool: MAX
  259. kernel_size: 3
  260. stride: 2
  261. }
  262. }
  263. layer {
  264. name: "fc6"
  265. type: "InnerProduct"
  266. bottom: "pool5"
  267. top: "fc6"
  268. param {
  269. lr_mult: 1
  270. decay_mult: 1
  271. }
  272. param {
  273. lr_mult: 2
  274. decay_mult: 0
  275. }
  276. inner_product_param {
  277. num_output: 4096
  278. weight_filler {
  279. type: "gaussian"
  280. std: 0.005
  281. }
  282. bias_filler {
  283. type: "constant"
  284. value: 0.1
  285. }
  286. }
  287. }
  288. layer {
  289. name: "relu6"
  290. type: "ReLU"
  291. bottom: "fc6"
  292. top: "fc6"
  293. }
  294. layer {
  295. name: "drop6"
  296. type: "Dropout"
  297. bottom: "fc6"
  298. top: "fc6"
  299. dropout_param {
  300. dropout_ratio: 0.5
  301. }
  302. }
  303. layer {
  304. name: "fc7"
  305. type: "InnerProduct"
  306. bottom: "fc6"
  307. top: "fc7"
  308. param {
  309. lr_mult: 1
  310. decay_mult: 1
  311. }
  312. param {
  313. lr_mult: 2
  314. decay_mult: 0
  315. }
  316. inner_product_param {
  317. num_output: 4096
  318. weight_filler {
  319. type: "gaussian"
  320. std: 0.005
  321. }
  322. bias_filler {
  323. type: "constant"
  324. value: 0.1
  325. }
  326. }
  327. }
  328. layer {
  329. name: "relu7"
  330. type: "ReLU"
  331. bottom: "fc7"
  332. top: "fc7"
  333. }
  334. layer {
  335. name: "drop7"
  336. type: "Dropout"
  337. bottom: "fc7"
  338. top: "fc7"
  339. dropout_param {
  340. dropout_ratio: 0.5
  341. }
  342. }
  343. layer {
  344. name: "fc8"
  345. type: "InnerProduct"
  346. bottom: "fc7"
  347. top: "fc8"
  348. param {
  349. lr_mult: 1
  350. decay_mult: 1
  351. }
  352. param {
  353. lr_mult: 2
  354. decay_mult: 0
  355. }
  356. inner_product_param {
  357. num_output: 1000
  358. weight_filler {
  359. type: "gaussian"
  360. std: 0.01
  361. }
  362. bias_filler {
  363. type: "constant"
  364. value: 0
  365. }
  366. }
  367. }
  368. layer {
  369. name: "accuracy"
  370. type: "Accuracy"
  371. bottom: "fc8"
  372. bottom: "label"
  373. top: "accuracy"
  374. include {
  375. phase: TEST
  376. }
  377. }
  378. layer {
  379. name: "loss"
  380. type: "SoftmaxWithLoss"
  381. bottom: "fc8"
  382. bottom: "label"
  383. top: "loss"
  384. }
  385.  
  386. layer {
  387. name: "loss"
  388. type: "SoftmaxWithLoss"
  389. bottom: "fc8"
  390. bottom: "label"
  391. top: "loss"
  392. }
  393.  
  394. layer {
  395. name: "loss"
  396. type: "SoftmaxWithLoss"
  397. bottom: "fc8"
  398. bottom: "label"
  399. top: "loss"
  400. }
  401.  
  402. layer {
  403. name: "loss"
  404. type: "SoftmaxWithLoss"
  405. bottom: "fc8"
  406. bottom: "label"
  407. top: "loss"
  408. }
  409.  
  410. layer {
  411. name: "loss"
  412. type: "SoftmaxWithLoss"
  413. bottom: "fc8"
  414. bottom: "label"
  415. top: "loss"
  416. }
  417.  
  418. layer {
  419. name: "loss"
  420. type: "SoftmaxWithLoss"
  421. bottom: "fc8"
  422. bottom: "label"
  423. top: "loss"
  424. }
  425.  
  426. layer {
  427. name: "loss"
  428. type: "SoftmaxWithLoss"
  429. bottom: "fc8"
  430. bottom: "label"
  431. top: "loss"
  432. }
  433.  
  434. layer {
  435. name: "loss"
  436. type: "SoftmaxWithLoss"
  437. bottom: "fc8"
  438. bottom: "label"
  439. top: "loss"
  440. }
  441.  
  442. layer {
  443. name: "loss"
  444. type: "SoftmaxWithLoss"
  445. bottom: "fc8"
  446. bottom: "label"
  447. top: "loss"
  448. }
  449.  
  450. layer {
  451. name: "loss"
  452. type: "SoftmaxWithLoss"
  453. bottom: "fc8"
  454. bottom: "label"
  455. top: "loss"
  456. }
  457.  
  458. layer {
  459. name: "loss"
  460. type: "SoftmaxWithLoss"
  461. bottom: "fc8"
  462. bottom: "label"
  463. top: "loss"
  464. }
  465.  
  466. layer {
  467. name: "loss"
  468. type: "SoftmaxWithLoss"
  469. bottom: "fc8"
  470. bottom: "label"
  471. top: "loss"
  472. }
  473.  
  474. layer {
  475. name: "loss"
  476. type: "SoftmaxWithLoss"
  477. bottom: "fc8"
  478. bottom: "label"
  479. top: "loss"
  480. }
  481.  
  482. layer {
  483. name: "loss"
  484. type: "SoftmaxWithLoss"
  485. bottom: "fc8"
  486. bottom: "label"
  487. top: "loss"
  488. }
  489.  
  490. layer {
  491. name: "loss"
  492. type: "SoftmaxWithLoss"
  493. bottom: "fc8"
  494. bottom: "label"
  495. top: "loss"
  496. }
  497.  
  498. layer {
  499. name: "loss"
  500. type: "SoftmaxWithLoss"
  501. bottom: "fc8"
  502. bottom: "label"
  503. top: "loss"
  504. }
  505.  
  506. layer {
  507. name: "loss"
  508. type: "SoftmaxWithLoss"
  509. bottom: "fc8"
  510. bottom: "label"
  511. top: "loss"
  512. }
  513.  
  514. layer {
  515. name: "loss"
  516. type: "SoftmaxWithLoss"
  517. bottom: "fc8"
  518. bottom: "label"
  519. top: "loss"
  520. }
  521.  
  522. layer {
  523. name: "loss"
  524. type: "SoftmaxWithLoss"
  525. bottom: "fc8"
  526. bottom: "label"
  527. top: "loss"
  528. }
  529.  
  530. layer {
  531. name: "loss"
  532. type: "SoftmaxWithLoss"
  533. bottom: "fc8"
  534. bottom: "label"
  535. top: "loss"
  536. }
  537.  
  538. layer {
  539. name: "loss"
  540. type: "SoftmaxWithLoss"
  541. bottom: "fc8"
  542. bottom: "label"
  543. top: "loss"
  544. }
  545.  
  546. layer {
  547. name: "loss"
  548. type: "SoftmaxWithLoss"
  549. bottom: "fc8"
  550. bottom: "label"
  551. top: "loss"
  552. }
  553.  
  554. layer {
  555. name: "loss"
  556. type: "SoftmaxWithLoss"
  557. bottom: "fc8"
  558. bottom: "label"
  559. top: "loss"
  560. }
  561.  
  562. layer {
  563. name: "loss"
  564. type: "SoftmaxWithLoss"
  565. bottom: "fc8"
  566. bottom: "label"
  567. top: "loss"
  568. }
  569.  
  570. layer {
  571. name: "loss"
  572. type: "SoftmaxWithLoss"
  573. bottom: "fc8"
  574. bottom: "label"
  575. top: "loss"
  576. }
  577.  
  578. layer {
  579. name: "loss"
  580. type: "SoftmaxWithLoss"
  581. bottom: "fc8"
  582. bottom: "label"
  583. top: "loss"
  584. }
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