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  1. name: "deepsz-modResNet-50"
  2. input: "data"
  3. input_dim: 1
  4. input_dim: 3
  5. input_dim: 32
  6. input_dim: 32
  7.  
  8. layer {
  9. bottom: "data"
  10. top: "conv1_1"
  11. name: "conv1_1"
  12. type: "Convolution"
  13. convolution_param {
  14. num_output: 64
  15. kernel_size: 3
  16. pad: 1
  17. stride: 1
  18. }
  19. }
  20.  
  21. layer {
  22. bottom: "conv1_1"
  23. top: "conv1_1"
  24. name: "bn_conv1_1"
  25. type: "BatchNorm"
  26. batch_norm_param {
  27. use_global_stats: true
  28. }
  29. }
  30.  
  31. layer {
  32. bottom: "conv1_1"
  33. top: "conv1_1"
  34. name: "scale_conv1_1"
  35. type: "Scale"
  36. scale_param {
  37. bias_term: true
  38. }
  39. }
  40.  
  41. layer {
  42. bottom: "conv1_1"
  43. top: "conv1_1"
  44. name: "conv1_1_relu"
  45. type: "ReLU"
  46. }
  47.  
  48.  
  49. layer {
  50. bottom: "conv1_2"
  51. top: "conv1_2"
  52. name: "bn_conv1_2"
  53. type: "BatchNorm"
  54. batch_norm_param {
  55. use_global_stats: true
  56. }
  57. }
  58.  
  59. layer {
  60. bottom: "conv1_1"
  61. top: "conv1_2"
  62. name: "conv1_2"
  63. type: "Convolution"
  64. convolution_param {
  65. num_output: 64
  66. kernel_size: 3
  67. pad: 1
  68. stride: 2
  69. }
  70. }
  71.  
  72. layer {
  73. bottom: "conv1_2"
  74. top: "conv1_2"
  75. name: "scale_conv1_2"
  76. type: "Scale"
  77. scale_param {
  78. bias_term: true
  79. }
  80. }
  81.  
  82. layer {
  83. bottom: "conv1_2"
  84. top: "conv1_2"
  85. name: "conv1_2_relu"
  86. type: "ReLU"
  87. }
  88.  
  89.  
  90. layer {
  91. bottom: "conv1_2"
  92. top: "pool1"
  93. name: "pool1"
  94. type: "Pooling"
  95. pooling_param {
  96. kernel_size: 2
  97. stride: 2
  98. pool: MAX
  99. }
  100. }
  101.  
  102. layer {
  103. bottom: "pool1"
  104. top: "res2a_branch1"
  105. name: "res2a_branch1"
  106. type: "Convolution"
  107. convolution_param {
  108. num_output: 256
  109. kernel_size: 1
  110. pad: 0
  111. stride: 1
  112. bias_term: false
  113. }
  114. }
  115.  
  116. layer {
  117. bottom: "res2a_branch1"
  118. top: "res2a_branch1"
  119. name: "bn2a_branch1"
  120. type: "BatchNorm"
  121. batch_norm_param {
  122. use_global_stats: true
  123. }
  124. }
  125.  
  126. layer {
  127. bottom: "res2a_branch1"
  128. top: "res2a_branch1"
  129. name: "scale2a_branch1"
  130. type: "Scale"
  131. scale_param {
  132. bias_term: true
  133. }
  134. }
  135.  
  136. layer {
  137. bottom: "pool1"
  138. top: "res2a_branch2a"
  139. name: "res2a_branch2a"
  140. type: "Convolution"
  141. convolution_param {
  142. num_output: 64
  143. kernel_size: 1
  144. pad: 0
  145. stride: 1
  146. bias_term: false
  147. }
  148. }
  149.  
  150. layer {
  151. bottom: "res2a_branch2a"
  152. top: "res2a_branch2a"
  153. name: "bn2a_branch2a"
  154. type: "BatchNorm"
  155. batch_norm_param {
  156. use_global_stats: true
  157. }
  158. }
  159.  
  160. layer {
  161. bottom: "res2a_branch2a"
  162. top: "res2a_branch2a"
  163. name: "scale2a_branch2a"
  164. type: "Scale"
  165. scale_param {
  166. bias_term: true
  167. }
  168. }
  169.  
  170. layer {
  171. bottom: "res2a_branch2a"
  172. top: "res2a_branch2a"
  173. name: "res2a_branch2a_relu"
  174. type: "ReLU"
  175. }
  176.  
  177. layer {
  178. bottom: "res2a_branch2a"
  179. top: "res2a_branch2b"
  180. name: "res2a_branch2b"
  181. type: "Convolution"
  182. convolution_param {
  183. num_output: 64
  184. kernel_size: 3
  185. pad: 1
  186. stride: 1
  187. bias_term: false
  188. }
  189. }
  190.  
  191. layer {
  192. bottom: "res2a_branch2b"
  193. top: "res2a_branch2b"
  194. name: "bn2a_branch2b"
  195. type: "BatchNorm"
  196. batch_norm_param {
  197. use_global_stats: true
  198. }
  199. }
  200.  
  201. layer {
  202. bottom: "res2a_branch2b"
  203. top: "res2a_branch2b"
  204. name: "scale2a_branch2b"
  205. type: "Scale"
  206. scale_param {
  207. bias_term: true
  208. }
  209. }
  210.  
  211. layer {
  212. bottom: "res2a_branch2b"
  213. top: "res2a_branch2b"
  214. name: "res2a_branch2b_relu"
  215. type: "ReLU"
  216. }
  217.  
  218. layer {
  219. bottom: "res2a_branch2b"
  220. top: "res2a_branch2c"
  221. name: "res2a_branch2c"
  222. type: "Convolution"
  223. convolution_param {
  224. num_output: 256
  225. kernel_size: 1
  226. pad: 0
  227. stride: 1
  228. bias_term: false
  229. }
  230. }
  231.  
  232. layer {
  233. bottom: "res2a_branch2c"
  234. top: "res2a_branch2c"
  235. name: "bn2a_branch2c"
  236. type: "BatchNorm"
  237. batch_norm_param {
  238. use_global_stats: true
  239. }
  240. }
  241.  
  242. layer {
  243. bottom: "res2a_branch2c"
  244. top: "res2a_branch2c"
  245. name: "scale2a_branch2c"
  246. type: "Scale"
  247. scale_param {
  248. bias_term: true
  249. }
  250. }
  251.  
  252. layer {
  253. bottom: "res2a_branch1"
  254. bottom: "res2a_branch2c"
  255. top: "res2a"
  256. name: "res2a"
  257. type: "Eltwise"
  258. }
  259.  
  260. layer {
  261. bottom: "res2a"
  262. top: "res2a"
  263. name: "res2a_relu"
  264. type: "ReLU"
  265. }
  266.  
  267. layer {
  268. bottom: "res2a"
  269. top: "res2b_branch2a"
  270. name: "res2b_branch2a"
  271. type: "Convolution"
  272. convolution_param {
  273. num_output: 64
  274. kernel_size: 1
  275. pad: 0
  276. stride: 1
  277. bias_term: false
  278. }
  279. }
  280.  
  281. layer {
  282. bottom: "res2b_branch2a"
  283. top: "res2b_branch2a"
  284. name: "bn2b_branch2a"
  285. type: "BatchNorm"
  286. batch_norm_param {
  287. use_global_stats: true
  288. }
  289. }
  290.  
  291. layer {
  292. bottom: "res2b_branch2a"
  293. top: "res2b_branch2a"
  294. name: "scale2b_branch2a"
  295. type: "Scale"
  296. scale_param {
  297. bias_term: true
  298. }
  299. }
  300.  
  301. layer {
  302. bottom: "res2b_branch2a"
  303. top: "res2b_branch2a"
  304. name: "res2b_branch2a_relu"
  305. type: "ReLU"
  306. }
  307.  
  308. layer {
  309. bottom: "res2b_branch2a"
  310. top: "res2b_branch2b"
  311. name: "res2b_branch2b"
  312. type: "Convolution"
  313. convolution_param {
  314. num_output: 64
  315. kernel_size: 3
  316. pad: 1
  317. stride: 1
  318. bias_term: false
  319. }
  320. }
  321.  
  322. layer {
  323. bottom: "res2b_branch2b"
  324. top: "res2b_branch2b"
  325. name: "bn2b_branch2b"
  326. type: "BatchNorm"
  327. batch_norm_param {
  328. use_global_stats: true
  329. }
  330. }
  331.  
  332. layer {
  333. bottom: "res2b_branch2b"
  334. top: "res2b_branch2b"
  335. name: "scale2b_branch2b"
  336. type: "Scale"
  337. scale_param {
  338. bias_term: true
  339. }
  340. }
  341.  
  342. layer {
  343. bottom: "res2b_branch2b"
  344. top: "res2b_branch2b"
  345. name: "res2b_branch2b_relu"
  346. type: "ReLU"
  347. }
  348.  
  349. layer {
  350. bottom: "res2b_branch2b"
  351. top: "res2b_branch2c"
  352. name: "res2b_branch2c"
  353. type: "Convolution"
  354. convolution_param {
  355. num_output: 256
  356. kernel_size: 1
  357. pad: 0
  358. stride: 1
  359. bias_term: false
  360. }
  361. }
  362.  
  363. layer {
  364. bottom: "res2b_branch2c"
  365. top: "res2b_branch2c"
  366. name: "bn2b_branch2c"
  367. type: "BatchNorm"
  368. batch_norm_param {
  369. use_global_stats: true
  370. }
  371. }
  372.  
  373. layer {
  374. bottom: "res2b_branch2c"
  375. top: "res2b_branch2c"
  376. name: "scale2b_branch2c"
  377. type: "Scale"
  378. scale_param {
  379. bias_term: true
  380. }
  381. }
  382.  
  383. layer {
  384. bottom: "res2a"
  385. bottom: "res2b_branch2c"
  386. top: "res2b"
  387. name: "res2b"
  388. type: "Eltwise"
  389. }
  390.  
  391. layer {
  392. bottom: "res2b"
  393. top: "res2b"
  394. name: "res2b_relu"
  395. type: "ReLU"
  396. }
  397.  
  398. layer {
  399. bottom: "res2b"
  400. top: "res2c_branch2a"
  401. name: "res2c_branch2a"
  402. type: "Convolution"
  403. convolution_param {
  404. num_output: 64
  405. kernel_size: 1
  406. pad: 0
  407. stride: 1
  408. bias_term: false
  409. }
  410. }
  411.  
  412. layer {
  413. bottom: "res2c_branch2a"
  414. top: "res2c_branch2a"
  415. name: "bn2c_branch2a"
  416. type: "BatchNorm"
  417. batch_norm_param {
  418. use_global_stats: true
  419. }
  420. }
  421.  
  422. layer {
  423. bottom: "res2c_branch2a"
  424. top: "res2c_branch2a"
  425. name: "scale2c_branch2a"
  426. type: "Scale"
  427. scale_param {
  428. bias_term: true
  429. }
  430. }
  431.  
  432. layer {
  433. bottom: "res2c_branch2a"
  434. top: "res2c_branch2a"
  435. name: "res2c_branch2a_relu"
  436. type: "ReLU"
  437. }
  438.  
  439. layer {
  440. bottom: "res2c_branch2a"
  441. top: "res2c_branch2b"
  442. name: "res2c_branch2b"
  443. type: "Convolution"
  444. convolution_param {
  445. num_output: 64
  446. kernel_size: 3
  447. pad: 1
  448. stride: 1
  449. bias_term: false
  450. }
  451. }
  452.  
  453. layer {
  454. bottom: "res2c_branch2b"
  455. top: "res2c_branch2b"
  456. name: "bn2c_branch2b"
  457. type: "BatchNorm"
  458. batch_norm_param {
  459. use_global_stats: true
  460. }
  461. }
  462.  
  463. layer {
  464. bottom: "res2c_branch2b"
  465. top: "res2c_branch2b"
  466. name: "scale2c_branch2b"
  467. type: "Scale"
  468. scale_param {
  469. bias_term: true
  470. }
  471. }
  472.  
  473. layer {
  474. bottom: "res2c_branch2b"
  475. top: "res2c_branch2b"
  476. name: "res2c_branch2b_relu"
  477. type: "ReLU"
  478. }
  479.  
  480. layer {
  481. bottom: "res2c_branch2b"
  482. top: "res2c_branch2c"
  483. name: "res2c_branch2c"
  484. type: "Convolution"
  485. convolution_param {
  486. num_output: 256
  487. kernel_size: 1
  488. pad: 0
  489. stride: 1
  490. bias_term: false
  491. }
  492. }
  493.  
  494. layer {
  495. bottom: "res2c_branch2c"
  496. top: "res2c_branch2c"
  497. name: "bn2c_branch2c"
  498. type: "BatchNorm"
  499. batch_norm_param {
  500. use_global_stats: true
  501. }
  502. }
  503.  
  504. layer {
  505. bottom: "res2c_branch2c"
  506. top: "res2c_branch2c"
  507. name: "scale2c_branch2c"
  508. type: "Scale"
  509. scale_param {
  510. bias_term: true
  511. }
  512. }
  513.  
  514. layer {
  515. bottom: "res2b"
  516. bottom: "res2c_branch2c"
  517. top: "res2c"
  518. name: "res2c"
  519. type: "Eltwise"
  520. }
  521.  
  522. layer {
  523. bottom: "res2c"
  524. top: "res2c"
  525. name: "res2c_relu"
  526. type: "ReLU"
  527. }
  528.  
  529. layer {
  530. bottom: "res2c"
  531. top: "res3a_branch1"
  532. name: "res3a_branch1"
  533. type: "Convolution"
  534. convolution_param {
  535. num_output: 512
  536. kernel_size: 1
  537. pad: 0
  538. stride: 2
  539. bias_term: false
  540. }
  541. }
  542.  
  543. layer {
  544. bottom: "res3a_branch1"
  545. top: "res3a_branch1"
  546. name: "bn3a_branch1"
  547. type: "BatchNorm"
  548. batch_norm_param {
  549. use_global_stats: true
  550. }
  551. }
  552.  
  553. layer {
  554. bottom: "res3a_branch1"
  555. top: "res3a_branch1"
  556. name: "scale3a_branch1"
  557. type: "Scale"
  558. scale_param {
  559. bias_term: true
  560. }
  561. }
  562.  
  563. layer {
  564. bottom: "res2c"
  565. top: "res3a_branch2a"
  566. name: "res3a_branch2a"
  567. type: "Convolution"
  568. convolution_param {
  569. num_output: 128
  570. kernel_size: 1
  571. pad: 0
  572. stride: 2
  573. bias_term: false
  574. }
  575. }
  576.  
  577. layer {
  578. bottom: "res3a_branch2a"
  579. top: "res3a_branch2a"
  580. name: "bn3a_branch2a"
  581. type: "BatchNorm"
  582. batch_norm_param {
  583. use_global_stats: true
  584. }
  585. }
  586.  
  587. layer {
  588. bottom: "res3a_branch2a"
  589. top: "res3a_branch2a"
  590. name: "scale3a_branch2a"
  591. type: "Scale"
  592. scale_param {
  593. bias_term: true
  594. }
  595. }
  596.  
  597. layer {
  598. bottom: "res3a_branch2a"
  599. top: "res3a_branch2a"
  600. name: "res3a_branch2a_relu"
  601. type: "ReLU"
  602. }
  603.  
  604. layer {
  605. bottom: "res3a_branch2a"
  606. top: "res3a_branch2b"
  607. name: "res3a_branch2b"
  608. type: "Convolution"
  609. convolution_param {
  610. num_output: 128
  611. kernel_size: 3
  612. pad: 1
  613. stride: 1
  614. bias_term: false
  615. }
  616. }
  617.  
  618. layer {
  619. bottom: "res3a_branch2b"
  620. top: "res3a_branch2b"
  621. name: "bn3a_branch2b"
  622. type: "BatchNorm"
  623. batch_norm_param {
  624. use_global_stats: true
  625. }
  626. }
  627.  
  628. layer {
  629. bottom: "res3a_branch2b"
  630. top: "res3a_branch2b"
  631. name: "scale3a_branch2b"
  632. type: "Scale"
  633. scale_param {
  634. bias_term: true
  635. }
  636. }
  637.  
  638. layer {
  639. bottom: "res3a_branch2b"
  640. top: "res3a_branch2b"
  641. name: "res3a_branch2b_relu"
  642. type: "ReLU"
  643. }
  644.  
  645. layer {
  646. bottom: "res3a_branch2b"
  647. top: "res3a_branch2c"
  648. name: "res3a_branch2c"
  649. type: "Convolution"
  650. convolution_param {
  651. num_output: 512
  652. kernel_size: 1
  653. pad: 0
  654. stride: 1
  655. bias_term: false
  656. }
  657. }
  658.  
  659. layer {
  660. bottom: "res3a_branch2c"
  661. top: "res3a_branch2c"
  662. name: "bn3a_branch2c"
  663. type: "BatchNorm"
  664. batch_norm_param {
  665. use_global_stats: true
  666. }
  667. }
  668.  
  669. layer {
  670. bottom: "res3a_branch2c"
  671. top: "res3a_branch2c"
  672. name: "scale3a_branch2c"
  673. type: "Scale"
  674. scale_param {
  675. bias_term: true
  676. }
  677. }
  678.  
  679. layer {
  680. bottom: "res3a_branch1"
  681. bottom: "res3a_branch2c"
  682. top: "res3a"
  683. name: "res3a"
  684. type: "Eltwise"
  685. }
  686.  
  687. layer {
  688. bottom: "res3a"
  689. top: "res3a"
  690. name: "res3a_relu"
  691. type: "ReLU"
  692. }
  693.  
  694. layer {
  695. bottom: "res3a"
  696. top: "res3b_branch2a"
  697. name: "res3b_branch2a"
  698. type: "Convolution"
  699. convolution_param {
  700. num_output: 128
  701. kernel_size: 1
  702. pad: 0
  703. stride: 1
  704. bias_term: false
  705. }
  706. }
  707.  
  708. layer {
  709. bottom: "res3b_branch2a"
  710. top: "res3b_branch2a"
  711. name: "bn3b_branch2a"
  712. type: "BatchNorm"
  713. batch_norm_param {
  714. use_global_stats: true
  715. }
  716. }
  717.  
  718. layer {
  719. bottom: "res3b_branch2a"
  720. top: "res3b_branch2a"
  721. name: "scale3b_branch2a"
  722. type: "Scale"
  723. scale_param {
  724. bias_term: true
  725. }
  726. }
  727.  
  728. layer {
  729. bottom: "res3b_branch2a"
  730. top: "res3b_branch2a"
  731. name: "res3b_branch2a_relu"
  732. type: "ReLU"
  733. }
  734.  
  735. layer {
  736. bottom: "res3b_branch2a"
  737. top: "res3b_branch2b"
  738. name: "res3b_branch2b"
  739. type: "Convolution"
  740. convolution_param {
  741. num_output: 128
  742. kernel_size: 3
  743. pad: 1
  744. stride: 1
  745. bias_term: false
  746. }
  747. }
  748.  
  749. layer {
  750. bottom: "res3b_branch2b"
  751. top: "res3b_branch2b"
  752. name: "bn3b_branch2b"
  753. type: "BatchNorm"
  754. batch_norm_param {
  755. use_global_stats: true
  756. }
  757. }
  758.  
  759. layer {
  760. bottom: "res3b_branch2b"
  761. top: "res3b_branch2b"
  762. name: "scale3b_branch2b"
  763. type: "Scale"
  764. scale_param {
  765. bias_term: true
  766. }
  767. }
  768.  
  769. layer {
  770. bottom: "res3b_branch2b"
  771. top: "res3b_branch2b"
  772. name: "res3b_branch2b_relu"
  773. type: "ReLU"
  774. }
  775.  
  776. layer {
  777. bottom: "res3b_branch2b"
  778. top: "res3b_branch2c"
  779. name: "res3b_branch2c"
  780. type: "Convolution"
  781. convolution_param {
  782. num_output: 512
  783. kernel_size: 1
  784. pad: 0
  785. stride: 1
  786. bias_term: false
  787. }
  788. }
  789.  
  790. layer {
  791. bottom: "res3b_branch2c"
  792. top: "res3b_branch2c"
  793. name: "bn3b_branch2c"
  794. type: "BatchNorm"
  795. batch_norm_param {
  796. use_global_stats: true
  797. }
  798. }
  799.  
  800. layer {
  801. bottom: "res3b_branch2c"
  802. top: "res3b_branch2c"
  803. name: "scale3b_branch2c"
  804. type: "Scale"
  805. scale_param {
  806. bias_term: true
  807. }
  808. }
  809.  
  810. layer {
  811. bottom: "res3a"
  812. bottom: "res3b_branch2c"
  813. top: "res3b"
  814. name: "res3b"
  815. type: "Eltwise"
  816. }
  817.  
  818. layer {
  819. bottom: "res3b"
  820. top: "res3b"
  821. name: "res3b_relu"
  822. type: "ReLU"
  823. }
  824.  
  825. layer {
  826. bottom: "res3b"
  827. top: "res3c_branch2a"
  828. name: "res3c_branch2a"
  829. type: "Convolution"
  830. convolution_param {
  831. num_output: 128
  832. kernel_size: 1
  833. pad: 0
  834. stride: 1
  835. bias_term: false
  836. }
  837. }
  838.  
  839. layer {
  840. bottom: "res3c_branch2a"
  841. top: "res3c_branch2a"
  842. name: "bn3c_branch2a"
  843. type: "BatchNorm"
  844. batch_norm_param {
  845. use_global_stats: true
  846. }
  847. }
  848.  
  849. layer {
  850. bottom: "res3c_branch2a"
  851. top: "res3c_branch2a"
  852. name: "scale3c_branch2a"
  853. type: "Scale"
  854. scale_param {
  855. bias_term: true
  856. }
  857. }
  858.  
  859. layer {
  860. bottom: "res3c_branch2a"
  861. top: "res3c_branch2a"
  862. name: "res3c_branch2a_relu"
  863. type: "ReLU"
  864. }
  865.  
  866. layer {
  867. bottom: "res3c_branch2a"
  868. top: "res3c_branch2b"
  869. name: "res3c_branch2b"
  870. type: "Convolution"
  871. convolution_param {
  872. num_output: 128
  873. kernel_size: 3
  874. pad: 1
  875. stride: 1
  876. bias_term: false
  877. }
  878. }
  879.  
  880. layer {
  881. bottom: "res3c_branch2b"
  882. top: "res3c_branch2b"
  883. name: "bn3c_branch2b"
  884. type: "BatchNorm"
  885. batch_norm_param {
  886. use_global_stats: true
  887. }
  888. }
  889.  
  890. layer {
  891. bottom: "res3c_branch2b"
  892. top: "res3c_branch2b"
  893. name: "scale3c_branch2b"
  894. type: "Scale"
  895. scale_param {
  896. bias_term: true
  897. }
  898. }
  899.  
  900. layer {
  901. bottom: "res3c_branch2b"
  902. top: "res3c_branch2b"
  903. name: "res3c_branch2b_relu"
  904. type: "ReLU"
  905. }
  906.  
  907. layer {
  908. bottom: "res3c_branch2b"
  909. top: "res3c_branch2c"
  910. name: "res3c_branch2c"
  911. type: "Convolution"
  912. convolution_param {
  913. num_output: 512
  914. kernel_size: 1
  915. pad: 0
  916. stride: 1
  917. bias_term: false
  918. }
  919. }
  920.  
  921. layer {
  922. bottom: "res3c_branch2c"
  923. top: "res3c_branch2c"
  924. name: "bn3c_branch2c"
  925. type: "BatchNorm"
  926. batch_norm_param {
  927. use_global_stats: true
  928. }
  929. }
  930.  
  931. layer {
  932. bottom: "res3c_branch2c"
  933. top: "res3c_branch2c"
  934. name: "scale3c_branch2c"
  935. type: "Scale"
  936. scale_param {
  937. bias_term: true
  938. }
  939. }
  940.  
  941. layer {
  942. bottom: "res3b"
  943. bottom: "res3c_branch2c"
  944. top: "res3c"
  945. name: "res3c"
  946. type: "Eltwise"
  947. }
  948.  
  949. layer {
  950. bottom: "res3c"
  951. top: "res3c"
  952. name: "res3c_relu"
  953. type: "ReLU"
  954. }
  955.  
  956. layer {
  957. bottom: "res3c"
  958. top: "res3d_branch2a"
  959. name: "res3d_branch2a"
  960. type: "Convolution"
  961. convolution_param {
  962. num_output: 128
  963. kernel_size: 1
  964. pad: 0
  965. stride: 1
  966. bias_term: false
  967. }
  968. }
  969.  
  970. layer {
  971. bottom: "res3d_branch2a"
  972. top: "res3d_branch2a"
  973. name: "bn3d_branch2a"
  974. type: "BatchNorm"
  975. batch_norm_param {
  976. use_global_stats: true
  977. }
  978. }
  979.  
  980. layer {
  981. bottom: "res3d_branch2a"
  982. top: "res3d_branch2a"
  983. name: "scale3d_branch2a"
  984. type: "Scale"
  985. scale_param {
  986. bias_term: true
  987. }
  988. }
  989.  
  990. layer {
  991. bottom: "res3d_branch2a"
  992. top: "res3d_branch2a"
  993. name: "res3d_branch2a_relu"
  994. type: "ReLU"
  995. }
  996.  
  997. layer {
  998. bottom: "res3d_branch2a"
  999. top: "res3d_branch2b"
  1000. name: "res3d_branch2b"
  1001. type: "Convolution"
  1002. convolution_param {
  1003. num_output: 128
  1004. kernel_size: 3
  1005. pad: 1
  1006. stride: 1
  1007. bias_term: false
  1008. }
  1009. }
  1010.  
  1011. layer {
  1012. bottom: "res3d_branch2b"
  1013. top: "res3d_branch2b"
  1014. name: "bn3d_branch2b"
  1015. type: "BatchNorm"
  1016. batch_norm_param {
  1017. use_global_stats: true
  1018. }
  1019. }
  1020.  
  1021. layer {
  1022. bottom: "res3d_branch2b"
  1023. top: "res3d_branch2b"
  1024. name: "scale3d_branch2b"
  1025. type: "Scale"
  1026. scale_param {
  1027. bias_term: true
  1028. }
  1029. }
  1030.  
  1031. layer {
  1032. bottom: "res3d_branch2b"
  1033. top: "res3d_branch2b"
  1034. name: "res3d_branch2b_relu"
  1035. type: "ReLU"
  1036. }
  1037.  
  1038. layer {
  1039. bottom: "res3d_branch2b"
  1040. top: "res3d_branch2c"
  1041. name: "res3d_branch2c"
  1042. type: "Convolution"
  1043. convolution_param {
  1044. num_output: 512
  1045. kernel_size: 1
  1046. pad: 0
  1047. stride: 1
  1048. bias_term: false
  1049. }
  1050. }
  1051.  
  1052. layer {
  1053. bottom: "res3d_branch2c"
  1054. top: "res3d_branch2c"
  1055. name: "bn3d_branch2c"
  1056. type: "BatchNorm"
  1057. batch_norm_param {
  1058. use_global_stats: true
  1059. }
  1060. }
  1061.  
  1062. layer {
  1063. bottom: "res3d_branch2c"
  1064. top: "res3d_branch2c"
  1065. name: "scale3d_branch2c"
  1066. type: "Scale"
  1067. scale_param {
  1068. bias_term: true
  1069. }
  1070. }
  1071.  
  1072. layer {
  1073. bottom: "res3c"
  1074. bottom: "res3d_branch2c"
  1075. top: "res3d"
  1076. name: "res3d"
  1077. type: "Eltwise"
  1078. }
  1079.  
  1080. layer {
  1081. bottom: "res3d"
  1082. top: "res3d"
  1083. name: "res3d_relu"
  1084. type: "ReLU"
  1085. }
  1086.  
  1087. layer {
  1088. bottom: "res3d"
  1089. top: "res4a_branch1"
  1090. name: "res4a_branch1"
  1091. type: "Convolution"
  1092. convolution_param {
  1093. num_output: 1024
  1094. kernel_size: 1
  1095. pad: 0
  1096. stride: 2
  1097. bias_term: false
  1098. }
  1099. }
  1100.  
  1101. layer {
  1102. bottom: "res4a_branch1"
  1103. top: "res4a_branch1"
  1104. name: "bn4a_branch1"
  1105. type: "BatchNorm"
  1106. batch_norm_param {
  1107. use_global_stats: true
  1108. }
  1109. }
  1110.  
  1111. layer {
  1112. bottom: "res4a_branch1"
  1113. top: "res4a_branch1"
  1114. name: "scale4a_branch1"
  1115. type: "Scale"
  1116. scale_param {
  1117. bias_term: true
  1118. }
  1119. }
  1120.  
  1121. layer {
  1122. bottom: "res3d"
  1123. top: "res4a_branch2a"
  1124. name: "res4a_branch2a"
  1125. type: "Convolution"
  1126. convolution_param {
  1127. num_output: 256
  1128. kernel_size: 1
  1129. pad: 0
  1130. stride: 2
  1131. bias_term: false
  1132. }
  1133. }
  1134.  
  1135. layer {
  1136. bottom: "res4a_branch2a"
  1137. top: "res4a_branch2a"
  1138. name: "bn4a_branch2a"
  1139. type: "BatchNorm"
  1140. batch_norm_param {
  1141. use_global_stats: true
  1142. }
  1143. }
  1144.  
  1145. layer {
  1146. bottom: "res4a_branch2a"
  1147. top: "res4a_branch2a"
  1148. name: "scale4a_branch2a"
  1149. type: "Scale"
  1150. scale_param {
  1151. bias_term: true
  1152. }
  1153. }
  1154.  
  1155. layer {
  1156. bottom: "res4a_branch2a"
  1157. top: "res4a_branch2a"
  1158. name: "res4a_branch2a_relu"
  1159. type: "ReLU"
  1160. }
  1161.  
  1162. layer {
  1163. bottom: "res4a_branch2a"
  1164. top: "res4a_branch2b"
  1165. name: "res4a_branch2b"
  1166. type: "Convolution"
  1167. convolution_param {
  1168. num_output: 256
  1169. kernel_size: 3
  1170. pad: 1
  1171. stride: 1
  1172. bias_term: false
  1173. }
  1174. }
  1175.  
  1176. layer {
  1177. bottom: "res4a_branch2b"
  1178. top: "res4a_branch2b"
  1179. name: "bn4a_branch2b"
  1180. type: "BatchNorm"
  1181. batch_norm_param {
  1182. use_global_stats: true
  1183. }
  1184. }
  1185.  
  1186. layer {
  1187. bottom: "res4a_branch2b"
  1188. top: "res4a_branch2b"
  1189. name: "scale4a_branch2b"
  1190. type: "Scale"
  1191. scale_param {
  1192. bias_term: true
  1193. }
  1194. }
  1195.  
  1196. layer {
  1197. bottom: "res4a_branch2b"
  1198. top: "res4a_branch2b"
  1199. name: "res4a_branch2b_relu"
  1200. type: "ReLU"
  1201. }
  1202.  
  1203. layer {
  1204. bottom: "res4a_branch2b"
  1205. top: "res4a_branch2c"
  1206. name: "res4a_branch2c"
  1207. type: "Convolution"
  1208. convolution_param {
  1209. num_output: 1024
  1210. kernel_size: 1
  1211. pad: 0
  1212. stride: 1
  1213. bias_term: false
  1214. }
  1215. }
  1216.  
  1217. layer {
  1218. bottom: "res4a_branch2c"
  1219. top: "res4a_branch2c"
  1220. name: "bn4a_branch2c"
  1221. type: "BatchNorm"
  1222. batch_norm_param {
  1223. use_global_stats: true
  1224. }
  1225. }
  1226.  
  1227. layer {
  1228. bottom: "res4a_branch2c"
  1229. top: "res4a_branch2c"
  1230. name: "scale4a_branch2c"
  1231. type: "Scale"
  1232. scale_param {
  1233. bias_term: true
  1234. }
  1235. }
  1236.  
  1237. layer {
  1238. bottom: "res4a_branch1"
  1239. bottom: "res4a_branch2c"
  1240. top: "res4a"
  1241. name: "res4a"
  1242. type: "Eltwise"
  1243. }
  1244.  
  1245. layer {
  1246. bottom: "res4a"
  1247. top: "res4a"
  1248. name: "res4a_relu"
  1249. type: "ReLU"
  1250. }
  1251.  
  1252. layer {
  1253. bottom: "res4a"
  1254. top: "res4b_branch2a"
  1255. name: "res4b_branch2a"
  1256. type: "Convolution"
  1257. convolution_param {
  1258. num_output: 256
  1259. kernel_size: 1
  1260. pad: 0
  1261. stride: 1
  1262. bias_term: false
  1263. }
  1264. }
  1265.  
  1266. layer {
  1267. bottom: "res4b_branch2a"
  1268. top: "res4b_branch2a"
  1269. name: "bn4b_branch2a"
  1270. type: "BatchNorm"
  1271. batch_norm_param {
  1272. use_global_stats: true
  1273. }
  1274. }
  1275.  
  1276. layer {
  1277. bottom: "res4b_branch2a"
  1278. top: "res4b_branch2a"
  1279. name: "scale4b_branch2a"
  1280. type: "Scale"
  1281. scale_param {
  1282. bias_term: true
  1283. }
  1284. }
  1285.  
  1286. layer {
  1287. bottom: "res4b_branch2a"
  1288. top: "res4b_branch2a"
  1289. name: "res4b_branch2a_relu"
  1290. type: "ReLU"
  1291. }
  1292.  
  1293. layer {
  1294. bottom: "res4b_branch2a"
  1295. top: "res4b_branch2b"
  1296. name: "res4b_branch2b"
  1297. type: "Convolution"
  1298. convolution_param {
  1299. num_output: 256
  1300. kernel_size: 3
  1301. pad: 1
  1302. stride: 1
  1303. bias_term: false
  1304. }
  1305. }
  1306.  
  1307. layer {
  1308. bottom: "res4b_branch2b"
  1309. top: "res4b_branch2b"
  1310. name: "bn4b_branch2b"
  1311. type: "BatchNorm"
  1312. batch_norm_param {
  1313. use_global_stats: true
  1314. }
  1315. }
  1316.  
  1317. layer {
  1318. bottom: "res4b_branch2b"
  1319. top: "res4b_branch2b"
  1320. name: "scale4b_branch2b"
  1321. type: "Scale"
  1322. scale_param {
  1323. bias_term: true
  1324. }
  1325. }
  1326.  
  1327. layer {
  1328. bottom: "res4b_branch2b"
  1329. top: "res4b_branch2b"
  1330. name: "res4b_branch2b_relu"
  1331. type: "ReLU"
  1332. }
  1333.  
  1334. layer {
  1335. bottom: "res4b_branch2b"
  1336. top: "res4b_branch2c"
  1337. name: "res4b_branch2c"
  1338. type: "Convolution"
  1339. convolution_param {
  1340. num_output: 1024
  1341. kernel_size: 1
  1342. pad: 0
  1343. stride: 1
  1344. bias_term: false
  1345. }
  1346. }
  1347.  
  1348. layer {
  1349. bottom: "res4b_branch2c"
  1350. top: "res4b_branch2c"
  1351. name: "bn4b_branch2c"
  1352. type: "BatchNorm"
  1353. batch_norm_param {
  1354. use_global_stats: true
  1355. }
  1356. }
  1357.  
  1358. layer {
  1359. bottom: "res4b_branch2c"
  1360. top: "res4b_branch2c"
  1361. name: "scale4b_branch2c"
  1362. type: "Scale"
  1363. scale_param {
  1364. bias_term: true
  1365. }
  1366. }
  1367.  
  1368. layer {
  1369. bottom: "res4a"
  1370. bottom: "res4b_branch2c"
  1371. top: "res4b"
  1372. name: "res4b"
  1373. type: "Eltwise"
  1374. }
  1375.  
  1376. layer {
  1377. bottom: "res4b"
  1378. top: "res4b"
  1379. name: "res4b_relu"
  1380. type: "ReLU"
  1381. }
  1382.  
  1383. layer {
  1384. bottom: "res4b"
  1385. top: "res4c_branch2a"
  1386. name: "res4c_branch2a"
  1387. type: "Convolution"
  1388. convolution_param {
  1389. num_output: 256
  1390. kernel_size: 1
  1391. pad: 0
  1392. stride: 1
  1393. bias_term: false
  1394. }
  1395. }
  1396.  
  1397. layer {
  1398. bottom: "res4c_branch2a"
  1399. top: "res4c_branch2a"
  1400. name: "bn4c_branch2a"
  1401. type: "BatchNorm"
  1402. batch_norm_param {
  1403. use_global_stats: true
  1404. }
  1405. }
  1406.  
  1407. layer {
  1408. bottom: "res4c_branch2a"
  1409. top: "res4c_branch2a"
  1410. name: "scale4c_branch2a"
  1411. type: "Scale"
  1412. scale_param {
  1413. bias_term: true
  1414. }
  1415. }
  1416.  
  1417. layer {
  1418. bottom: "res4c_branch2a"
  1419. top: "res4c_branch2a"
  1420. name: "res4c_branch2a_relu"
  1421. type: "ReLU"
  1422. }
  1423.  
  1424. layer {
  1425. bottom: "res4c_branch2a"
  1426. top: "res4c_branch2b"
  1427. name: "res4c_branch2b"
  1428. type: "Convolution"
  1429. convolution_param {
  1430. num_output: 256
  1431. kernel_size: 3
  1432. pad: 1
  1433. stride: 1
  1434. bias_term: false
  1435. }
  1436. }
  1437.  
  1438. layer {
  1439. bottom: "res4c_branch2b"
  1440. top: "res4c_branch2b"
  1441. name: "bn4c_branch2b"
  1442. type: "BatchNorm"
  1443. batch_norm_param {
  1444. use_global_stats: true
  1445. }
  1446. }
  1447.  
  1448. layer {
  1449. bottom: "res4c_branch2b"
  1450. top: "res4c_branch2b"
  1451. name: "scale4c_branch2b"
  1452. type: "Scale"
  1453. scale_param {
  1454. bias_term: true
  1455. }
  1456. }
  1457.  
  1458. layer {
  1459. bottom: "res4c_branch2b"
  1460. top: "res4c_branch2b"
  1461. name: "res4c_branch2b_relu"
  1462. type: "ReLU"
  1463. }
  1464.  
  1465. layer {
  1466. bottom: "res4c_branch2b"
  1467. top: "res4c_branch2c"
  1468. name: "res4c_branch2c"
  1469. type: "Convolution"
  1470. convolution_param {
  1471. num_output: 1024
  1472. kernel_size: 1
  1473. pad: 0
  1474. stride: 1
  1475. bias_term: false
  1476. }
  1477. }
  1478.  
  1479. layer {
  1480. bottom: "res4c_branch2c"
  1481. top: "res4c_branch2c"
  1482. name: "bn4c_branch2c"
  1483. type: "BatchNorm"
  1484. batch_norm_param {
  1485. use_global_stats: true
  1486. }
  1487. }
  1488.  
  1489. layer {
  1490. bottom: "res4c_branch2c"
  1491. top: "res4c_branch2c"
  1492. name: "scale4c_branch2c"
  1493. type: "Scale"
  1494. scale_param {
  1495. bias_term: true
  1496. }
  1497. }
  1498.  
  1499. layer {
  1500. bottom: "res4b"
  1501. bottom: "res4c_branch2c"
  1502. top: "res4c"
  1503. name: "res4c"
  1504. type: "Eltwise"
  1505. }
  1506.  
  1507. layer {
  1508. bottom: "res4c"
  1509. top: "res4c"
  1510. name: "res4c_relu"
  1511. type: "ReLU"
  1512. }
  1513.  
  1514. layer {
  1515. bottom: "res4c"
  1516. top: "res4d_branch2a"
  1517. name: "res4d_branch2a"
  1518. type: "Convolution"
  1519. convolution_param {
  1520. num_output: 256
  1521. kernel_size: 1
  1522. pad: 0
  1523. stride: 1
  1524. bias_term: false
  1525. }
  1526. }
  1527.  
  1528. layer {
  1529. bottom: "res4d_branch2a"
  1530. top: "res4d_branch2a"
  1531. name: "bn4d_branch2a"
  1532. type: "BatchNorm"
  1533. batch_norm_param {
  1534. use_global_stats: true
  1535. }
  1536. }
  1537.  
  1538. layer {
  1539. bottom: "res4d_branch2a"
  1540. top: "res4d_branch2a"
  1541. name: "scale4d_branch2a"
  1542. type: "Scale"
  1543. scale_param {
  1544. bias_term: true
  1545. }
  1546. }
  1547.  
  1548. layer {
  1549. bottom: "res4d_branch2a"
  1550. top: "res4d_branch2a"
  1551. name: "res4d_branch2a_relu"
  1552. type: "ReLU"
  1553. }
  1554.  
  1555. layer {
  1556. bottom: "res4d_branch2a"
  1557. top: "res4d_branch2b"
  1558. name: "res4d_branch2b"
  1559. type: "Convolution"
  1560. convolution_param {
  1561. num_output: 256
  1562. kernel_size: 3
  1563. pad: 1
  1564. stride: 1
  1565. bias_term: false
  1566. }
  1567. }
  1568.  
  1569. layer {
  1570. bottom: "res4d_branch2b"
  1571. top: "res4d_branch2b"
  1572. name: "bn4d_branch2b"
  1573. type: "BatchNorm"
  1574. batch_norm_param {
  1575. use_global_stats: true
  1576. }
  1577. }
  1578.  
  1579. layer {
  1580. bottom: "res4d_branch2b"
  1581. top: "res4d_branch2b"
  1582. name: "scale4d_branch2b"
  1583. type: "Scale"
  1584. scale_param {
  1585. bias_term: true
  1586. }
  1587. }
  1588.  
  1589. layer {
  1590. bottom: "res4d_branch2b"
  1591. top: "res4d_branch2b"
  1592. name: "res4d_branch2b_relu"
  1593. type: "ReLU"
  1594. }
  1595.  
  1596. layer {
  1597. bottom: "res4d_branch2b"
  1598. top: "res4d_branch2c"
  1599. name: "res4d_branch2c"
  1600. type: "Convolution"
  1601. convolution_param {
  1602. num_output: 1024
  1603. kernel_size: 1
  1604. pad: 0
  1605. stride: 1
  1606. bias_term: false
  1607. }
  1608. }
  1609.  
  1610. layer {
  1611. bottom: "res4d_branch2c"
  1612. top: "res4d_branch2c"
  1613. name: "bn4d_branch2c"
  1614. type: "BatchNorm"
  1615. batch_norm_param {
  1616. use_global_stats: true
  1617. }
  1618. }
  1619.  
  1620. layer {
  1621. bottom: "res4d_branch2c"
  1622. top: "res4d_branch2c"
  1623. name: "scale4d_branch2c"
  1624. type: "Scale"
  1625. scale_param {
  1626. bias_term: true
  1627. }
  1628. }
  1629.  
  1630. layer {
  1631. bottom: "res4c"
  1632. bottom: "res4d_branch2c"
  1633. top: "res4d"
  1634. name: "res4d"
  1635. type: "Eltwise"
  1636. }
  1637.  
  1638. layer {
  1639. bottom: "res4d"
  1640. top: "res4d"
  1641. name: "res4d_relu"
  1642. type: "ReLU"
  1643. }
  1644.  
  1645. layer {
  1646. bottom: "res4d"
  1647. top: "res4e_branch2a"
  1648. name: "res4e_branch2a"
  1649. type: "Convolution"
  1650. convolution_param {
  1651. num_output: 256
  1652. kernel_size: 1
  1653. pad: 0
  1654. stride: 1
  1655. bias_term: false
  1656. }
  1657. }
  1658.  
  1659. layer {
  1660. bottom: "res4e_branch2a"
  1661. top: "res4e_branch2a"
  1662. name: "bn4e_branch2a"
  1663. type: "BatchNorm"
  1664. batch_norm_param {
  1665. use_global_stats: true
  1666. }
  1667. }
  1668.  
  1669. layer {
  1670. bottom: "res4e_branch2a"
  1671. top: "res4e_branch2a"
  1672. name: "scale4e_branch2a"
  1673. type: "Scale"
  1674. scale_param {
  1675. bias_term: true
  1676. }
  1677. }
  1678.  
  1679. layer {
  1680. bottom: "res4e_branch2a"
  1681. top: "res4e_branch2a"
  1682. name: "res4e_branch2a_relu"
  1683. type: "ReLU"
  1684. }
  1685.  
  1686. layer {
  1687. bottom: "res4e_branch2a"
  1688. top: "res4e_branch2b"
  1689. name: "res4e_branch2b"
  1690. type: "Convolution"
  1691. convolution_param {
  1692. num_output: 256
  1693. kernel_size: 3
  1694. pad: 1
  1695. stride: 1
  1696. bias_term: false
  1697. }
  1698. }
  1699.  
  1700. layer {
  1701. bottom: "res4e_branch2b"
  1702. top: "res4e_branch2b"
  1703. name: "bn4e_branch2b"
  1704. type: "BatchNorm"
  1705. batch_norm_param {
  1706. use_global_stats: true
  1707. }
  1708. }
  1709.  
  1710. layer {
  1711. bottom: "res4e_branch2b"
  1712. top: "res4e_branch2b"
  1713. name: "scale4e_branch2b"
  1714. type: "Scale"
  1715. scale_param {
  1716. bias_term: true
  1717. }
  1718. }
  1719.  
  1720. layer {
  1721. bottom: "res4e_branch2b"
  1722. top: "res4e_branch2b"
  1723. name: "res4e_branch2b_relu"
  1724. type: "ReLU"
  1725. }
  1726.  
  1727. layer {
  1728. bottom: "res4e_branch2b"
  1729. top: "res4e_branch2c"
  1730. name: "res4e_branch2c"
  1731. type: "Convolution"
  1732. convolution_param {
  1733. num_output: 1024
  1734. kernel_size: 1
  1735. pad: 0
  1736. stride: 1
  1737. bias_term: false
  1738. }
  1739. }
  1740.  
  1741. layer {
  1742. bottom: "res4e_branch2c"
  1743. top: "res4e_branch2c"
  1744. name: "bn4e_branch2c"
  1745. type: "BatchNorm"
  1746. batch_norm_param {
  1747. use_global_stats: true
  1748. }
  1749. }
  1750.  
  1751. layer {
  1752. bottom: "res4e_branch2c"
  1753. top: "res4e_branch2c"
  1754. name: "scale4e_branch2c"
  1755. type: "Scale"
  1756. scale_param {
  1757. bias_term: true
  1758. }
  1759. }
  1760.  
  1761. layer {
  1762. bottom: "res4d"
  1763. bottom: "res4e_branch2c"
  1764. top: "res4e"
  1765. name: "res4e"
  1766. type: "Eltwise"
  1767. }
  1768.  
  1769. layer {
  1770. bottom: "res4e"
  1771. top: "res4e"
  1772. name: "res4e_relu"
  1773. type: "ReLU"
  1774. }
  1775.  
  1776. layer {
  1777. bottom: "res4e"
  1778. top: "res4f_branch2a"
  1779. name: "res4f_branch2a"
  1780. type: "Convolution"
  1781. convolution_param {
  1782. num_output: 256
  1783. kernel_size: 1
  1784. pad: 0
  1785. stride: 1
  1786. bias_term: false
  1787. }
  1788. }
  1789.  
  1790. layer {
  1791. bottom: "res4f_branch2a"
  1792. top: "res4f_branch2a"
  1793. name: "bn4f_branch2a"
  1794. type: "BatchNorm"
  1795. batch_norm_param {
  1796. use_global_stats: true
  1797. }
  1798. }
  1799.  
  1800. layer {
  1801. bottom: "res4f_branch2a"
  1802. top: "res4f_branch2a"
  1803. name: "scale4f_branch2a"
  1804. type: "Scale"
  1805. scale_param {
  1806. bias_term: true
  1807. }
  1808. }
  1809.  
  1810. layer {
  1811. bottom: "res4f_branch2a"
  1812. top: "res4f_branch2a"
  1813. name: "res4f_branch2a_relu"
  1814. type: "ReLU"
  1815. }
  1816.  
  1817. layer {
  1818. bottom: "res4f_branch2a"
  1819. top: "res4f_branch2b"
  1820. name: "res4f_branch2b"
  1821. type: "Convolution"
  1822. convolution_param {
  1823. num_output: 256
  1824. kernel_size: 3
  1825. pad: 1
  1826. stride: 1
  1827. bias_term: false
  1828. }
  1829. }
  1830.  
  1831. layer {
  1832. bottom: "res4f_branch2b"
  1833. top: "res4f_branch2b"
  1834. name: "bn4f_branch2b"
  1835. type: "BatchNorm"
  1836. batch_norm_param {
  1837. use_global_stats: true
  1838. }
  1839. }
  1840.  
  1841. layer {
  1842. bottom: "res4f_branch2b"
  1843. top: "res4f_branch2b"
  1844. name: "scale4f_branch2b"
  1845. type: "Scale"
  1846. scale_param {
  1847. bias_term: true
  1848. }
  1849. }
  1850.  
  1851. layer {
  1852. bottom: "res4f_branch2b"
  1853. top: "res4f_branch2b"
  1854. name: "res4f_branch2b_relu"
  1855. type: "ReLU"
  1856. }
  1857.  
  1858. layer {
  1859. bottom: "res4f_branch2b"
  1860. top: "res4f_branch2c"
  1861. name: "res4f_branch2c"
  1862. type: "Convolution"
  1863. convolution_param {
  1864. num_output: 1024
  1865. kernel_size: 1
  1866. pad: 0
  1867. stride: 1
  1868. bias_term: false
  1869. }
  1870. }
  1871.  
  1872. layer {
  1873. bottom: "res4f_branch2c"
  1874. top: "res4f_branch2c"
  1875. name: "bn4f_branch2c"
  1876. type: "BatchNorm"
  1877. batch_norm_param {
  1878. use_global_stats: true
  1879. }
  1880. }
  1881.  
  1882. layer {
  1883. bottom: "res4f_branch2c"
  1884. top: "res4f_branch2c"
  1885. name: "scale4f_branch2c"
  1886. type: "Scale"
  1887. scale_param {
  1888. bias_term: true
  1889. }
  1890. }
  1891.  
  1892. layer {
  1893. bottom: "res4e"
  1894. bottom: "res4f_branch2c"
  1895. top: "res4f"
  1896. name: "res4f"
  1897. type: "Eltwise"
  1898. }
  1899.  
  1900. layer {
  1901. bottom: "res4f"
  1902. top: "res4f"
  1903. name: "res4f_relu"
  1904. type: "ReLU"
  1905. }
  1906.  
  1907.  
  1908.  
  1909. layer {
  1910. bottom: "res4f"
  1911. top: "res4f"
  1912. name: "bn4f"
  1913. type: "BatchNorm"
  1914. batch_norm_param {
  1915. use_global_stats: true
  1916. }
  1917. }
  1918.  
  1919. layer {
  1920. bottom: "res4f"
  1921. top: "res4f"
  1922. name: "scale4f"
  1923. type: "Scale"
  1924. scale_param {
  1925. bias_term: true
  1926. }
  1927. }
  1928.  
  1929. layer {
  1930. bottom: "res4f"
  1931. top: "fc1"
  1932. name: "fc1"
  1933. type: "InnerProduct"
  1934. inner_product_param {
  1935. num_output: 256
  1936. }
  1937. }
  1938.  
  1939.  
  1940.  
  1941. layer {
  1942. bottom: "fc1"
  1943. top: "fc1"
  1944. name: "fc1_relu"
  1945. type: "ReLU"
  1946. }
  1947.  
  1948. layer {
  1949. bottom: "fc1"
  1950. top: "fc2"
  1951. name: "fc2"
  1952. type: "InnerProduct"
  1953. inner_product_param {
  1954. num_output: 256
  1955. }
  1956. }
  1957.  
  1958.  
  1959. layer {
  1960. bottom: "fc2"
  1961. top: "fc2"
  1962. name: "fc2_relu"
  1963. type: "ReLU"
  1964. }
  1965.  
  1966. layer {
  1967. bottom: "fc2"
  1968. top: "prob_fc"
  1969. name: "prob_fc"
  1970. type: "InnerProduct"
  1971. inner_product_param {
  1972. num_output: 2
  1973. }
  1974. }
  1975.  
  1976. layer {
  1977. bottom: "prob_fc"
  1978. top: "prob_fc"
  1979. name: "prob_relu"
  1980. type: "ReLU"
  1981. }
  1982.  
  1983. layer {
  1984. bottom: "prob_fc"
  1985. top: "prob"
  1986. name: "prob"
  1987. type: "Softmax"
  1988. }
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