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飞浆测试日志

时间:2020-09-24 21:44:01      阅读:37      评论:0      收藏:0      [点我收藏+]

标签:padding   filter   read   ide   lse   eating   horizon   fuse   snapshot   

飞浆测试日志

-----------  Configuration Arguments -----------
MASK_ON: 1
anchor_sizes: [32, 64, 128, 256, 512]
aspect_ratios: [0.5, 1.0, 2.0]
batch_size_per_im: 512
class_num: 81
data_dir: coco30
dataset: coco2017
draw_threshold: 0.8
enable_ce: False
freeze_model_save_dir: freeze_model
im_per_batch: 1
image_path: dataset/coco/val2017
learning_rate: 0.01
log_window: 20
max_iter: 3000
max_size: 1333
model_save_dir: output/
nms_thresh: 0.5
padding_minibatch: False
parallel: False
pixel_means: [102.9801, 115.9465, 122.7717]
pretrained_model: imagenet_resnet50_fusebn
rpn_nms_thresh: 0.7
rpn_stride: [16.0, 16.0]
scales: [800]
score_thresh: 0.05
snapshot_stride: 10000
use_gpu: 1
use_profile: False
use_pyreader: False
variance: [1.0, 1.0, 1.0, 1.0]
------------------------------------------------
W0924 08:33:53.154363   447 device_context.cc:237] Please NOTE: device: 0, CUDA Capability: 70, Driver API Version: 9.2, Runtime API Version: 9.0
W0924 08:33:53.159633   447 device_context.cc:245] device: 0, cuDNN Version: 7.3.
Creating: coco2017
loading annotations into memory...
Done (t=0.01s)
creating index...
index created!
_add_gt_annotations took 0.007s
Appending horizontally-flipped training examples...
Loaded dataset: coco2017
60 roidb entries
Filtered 0 roidb entries: 60 -> 60
train on coco2017 with 60 roidbs
2020-09-24 08:33:55.278096, iter: 0, lr: 0.00333, loss: 6.767, loss_cls: 4.367, loss_bbox: 0.266, loss_rpn_cls: 0.684, loss_rpn_bbox: 0.285, loss_mask: 1.165, time: 0.017
2020-09-24 08:34:11.975181, iter: 50, lr: 0.00400, loss: 1.941, loss_cls: 0.392, loss_bbox: 0.116, loss_rpn_cls: 0.388, loss_rpn_bbox: 0.229, loss_mask: 0.704, time: 0.334
2020-09-24 08:34:27.886392, iter: 100, lr: 0.00467, loss: 1.872, loss_cls: 0.459, loss_bbox: 0.116, loss_rpn_cls: 0.362, loss_rpn_bbox: 0.128, loss_mask: 0.655, time: 0.451
2020-09-24 08:34:44.891129, iter: 150, lr: 0.00533, loss: 1.974, loss_cls: 0.559, loss_bbox: 0.192, loss_rpn_cls: 0.423, loss_rpn_bbox: 0.221, loss_mask: 0.621, time: 0.324
2020-09-24 08:35:01.442434, iter: 200, lr: 0.00600, loss: 1.729, loss_cls: 0.44, loss_bbox: 0.118, loss_rpn_cls: 0.366, loss_rpn_bbox: 0.134, loss_mask: 0.656, time: 0.337
2020-09-24 08:35:17.942153, iter: 250, lr: 0.00667, loss: 1.753, loss_cls: 0.483, loss_bbox: 0.127, loss_rpn_cls: 0.344, loss_rpn_bbox: 0.132, loss_mask: 0.609, time: 0.339
2020-09-24 08:35:35.343191, iter: 300, lr: 0.00733, loss: 1.69, loss_cls: 0.411, loss_bbox: 0.119, loss_rpn_cls: 0.305, loss_rpn_bbox: 0.102, loss_mask: 0.624, time: 0.319
2020-09-24 08:35:53.152731, iter: 350, lr: 0.00800, loss: 1.808, loss_cls: 0.479, loss_bbox: 0.194, loss_rpn_cls: 0.227, loss_rpn_bbox: 0.174, loss_mask: 0.554, time: 0.479
2020-09-24 08:36:10.946375, iter: 400, lr: 0.00867, loss: 1.708, loss_cls: 0.518, loss_bbox: 0.175, loss_rpn_cls: 0.301, loss_rpn_bbox: 0.133, loss_mask: 0.567, time: 0.344
2020-09-24 08:36:28.794567, iter: 450, lr: 0.00933, loss: 1.626, loss_cls: 0.391, loss_bbox: 0.148, loss_rpn_cls: 0.285, loss_rpn_bbox: 0.079, loss_mask: 0.588, time: 0.364
2020-09-24 08:36:46.632116, iter: 500, lr: 0.01000, loss: 1.626, loss_cls: 0.492, loss_bbox: 0.162, loss_rpn_cls: 0.236, loss_rpn_bbox: 0.14, loss_mask: 0.527, time: 0.336
2020-09-24 08:37:04.517153, iter: 550, lr: 0.01000, loss: 1.61, loss_cls: 0.522, loss_bbox: 0.202, loss_rpn_cls: 0.237, loss_rpn_bbox: 0.123, loss_mask: 0.513, time: 0.349
2020-09-24 08:37:22.511315, iter: 600, lr: 0.01000, loss: 1.632, loss_cls: 0.529, loss_bbox: 0.214, loss_rpn_cls: 0.232, loss_rpn_bbox: 0.096, loss_mask: 0.527, time: 0.318
2020-09-24 08:37:40.284773, iter: 650, lr: 0.01000, loss: 1.742, loss_cls: 0.545, loss_bbox: 0.239, loss_rpn_cls: 0.207, loss_rpn_bbox: 0.142, loss_mask: 0.526, time: 0.365
2020-09-24 08:37:58.228054, iter: 700, lr: 0.01000, loss: 1.714, loss_cls: 0.614, loss_bbox: 0.24, loss_rpn_cls: 0.202, loss_rpn_bbox: 0.16, loss_mask: 0.541, time: 0.357
2020-09-24 08:38:16.355890, iter: 750, lr: 0.01000, loss: 1.895, loss_cls: 0.727, loss_bbox: 0.335, loss_rpn_cls: 0.174, loss_rpn_bbox: 0.137, loss_mask: 0.511, time: 0.359
2020-09-24 08:38:34.499911, iter: 800, lr: 0.01000, loss: 1.544, loss_cls: 0.542, loss_bbox: 0.257, loss_rpn_cls: 0.173, loss_rpn_bbox: 0.109, loss_mask: 0.491, time: 0.364
2020-09-24 08:38:52.584202, iter: 850, lr: 0.01000, loss: 1.422, loss_cls: 0.43, loss_bbox: 0.275, loss_rpn_cls: 0.153, loss_rpn_bbox: 0.079, loss_mask: 0.424, time: 0.351
2020-09-24 08:39:10.455090, iter: 900, lr: 0.01000, loss: 1.605, loss_cls: 0.545, loss_bbox: 0.321, loss_rpn_cls: 0.143, loss_rpn_bbox: 0.101, loss_mask: 0.451, time: 0.355
2020-09-24 08:39:28.424582, iter: 950, lr: 0.01000, loss: 1.624, loss_cls: 0.579, loss_bbox: 0.353, loss_rpn_cls: 0.142, loss_rpn_bbox: 0.076, loss_mask: 0.473, time: 0.357
2020-09-24 08:39:46.051659, iter: 1000, lr: 0.01000, loss: 1.235, loss_cls: 0.465, loss_bbox: 0.261, loss_rpn_cls: 0.082, loss_rpn_bbox: 0.074, loss_mask: 0.41, time: 0.352
2020-09-24 08:40:03.976767, iter: 1050, lr: 0.01000, loss: 1.249, loss_cls: 0.45, loss_bbox: 0.307, loss_rpn_cls: 0.079, loss_rpn_bbox: 0.06, loss_mask: 0.37, time: 0.358
2020-09-24 08:40:21.874165, iter: 1100, lr: 0.01000, loss: 1.565, loss_cls: 0.639, loss_bbox: 0.372, loss_rpn_cls: 0.113, loss_rpn_bbox: 0.066, loss_mask: 0.463, time: 0.363
2020-09-24 08:40:39.554604, iter: 1150, lr: 0.01000, loss: 1.22, loss_cls: 0.421, loss_bbox: 0.317, loss_rpn_cls: 0.077, loss_rpn_bbox: 0.076, loss_mask: 0.349, time: 0.368
2020-09-24 08:40:57.417578, iter: 1200, lr: 0.01000, loss: 1.486, loss_cls: 0.585, loss_bbox: 0.298, loss_rpn_cls: 0.099, loss_rpn_bbox: 0.058, loss_mask: 0.39, time: 0.355
2020-09-24 08:41:15.127133, iter: 1250, lr: 0.01000, loss: 1.434, loss_cls: 0.536, loss_bbox: 0.308, loss_rpn_cls: 0.082, loss_rpn_bbox: 0.086, loss_mask: 0.389, time: 0.347
2020-09-24 08:41:32.967730, iter: 1300, lr: 0.01000, loss: 1.458, loss_cls: 0.582, loss_bbox: 0.376, loss_rpn_cls: 0.066, loss_rpn_bbox: 0.071, loss_mask: 0.382, time: 0.352
2020-09-24 08:41:50.548665, iter: 1350, lr: 0.01000, loss: 1.023, loss_cls: 0.372, loss_bbox: 0.243, loss_rpn_cls: 0.055, loss_rpn_bbox: 0.057, loss_mask: 0.286, time: 0.337
2020-09-24 08:42:08.142527, iter: 1400, lr: 0.01000, loss: 1.064, loss_cls: 0.394, loss_bbox: 0.269, loss_rpn_cls: 0.058, loss_rpn_bbox: 0.061, loss_mask: 0.312, time: 0.361
2020-09-24 08:42:25.724010, iter: 1450, lr: 0.01000, loss: 1.182, loss_cls: 0.446, loss_bbox: 0.293, loss_rpn_cls: 0.064, loss_rpn_bbox: 0.069, loss_mask: 0.325, time: 0.344
2020-09-24 08:42:43.264335, iter: 1500, lr: 0.01000, loss: 1.222, loss_cls: 0.398, loss_bbox: 0.339, loss_rpn_cls: 0.055, loss_rpn_bbox: 0.048, loss_mask: 0.329, time: 0.325
2020-09-24 08:43:00.940032, iter: 1550, lr: 0.01000, loss: 1.169, loss_cls: 0.386, loss_bbox: 0.323, loss_rpn_cls: 0.048, loss_rpn_bbox: 0.051, loss_mask: 0.319, time: 0.342
2020-09-24 08:43:18.724287, iter: 1600, lr: 0.01000, loss: 1.146, loss_cls: 0.377, loss_bbox: 0.323, loss_rpn_cls: 0.05, loss_rpn_bbox: 0.036, loss_mask: 0.327, time: 0.364
2020-09-24 08:43:36.394810, iter: 1650, lr: 0.01000, loss: 1.221, loss_cls: 0.417, loss_bbox: 0.361, loss_rpn_cls: 0.051, loss_rpn_bbox: 0.077, loss_mask: 0.357, time: 0.349
2020-09-24 08:43:53.890714, iter: 1700, lr: 0.01000, loss: 1.097, loss_cls: 0.374, loss_bbox: 0.256, loss_rpn_cls: 0.052, loss_rpn_bbox: 0.042, loss_mask: 0.28, time: 0.341
2020-09-24 08:44:11.450522, iter: 1750, lr: 0.01000, loss: 1.21, loss_cls: 0.396, loss_bbox: 0.292, loss_rpn_cls: 0.048, loss_rpn_bbox: 0.079, loss_mask: 0.321, time: 0.357
2020-09-24 08:44:29.031365, iter: 1800, lr: 0.01000, loss: 0.838, loss_cls: 0.261, loss_bbox: 0.233, loss_rpn_cls: 0.033, loss_rpn_bbox: 0.055, loss_mask: 0.23, time: 0.345
2020-09-24 08:44:46.495400, iter: 1850, lr: 0.01000, loss: 0.887, loss_cls: 0.318, loss_bbox: 0.243, loss_rpn_cls: 0.033, loss_rpn_bbox: 0.041, loss_mask: 0.255, time: 0.353
2020-09-24 08:45:04.082444, iter: 1900, lr: 0.01000, loss: 0.99, loss_cls: 0.351, loss_bbox: 0.275, loss_rpn_cls: 0.027, loss_rpn_bbox: 0.039, loss_mask: 0.298, time: 0.334
2020-09-24 08:45:21.654515, iter: 1950, lr: 0.01000, loss: 1.008, loss_cls: 0.363, loss_bbox: 0.265, loss_rpn_cls: 0.037, loss_rpn_bbox: 0.046, loss_mask: 0.283, time: 0.351
2020-09-24 08:45:39.081204, iter: 2000, lr: 0.01000, loss: 0.898, loss_cls: 0.287, loss_bbox: 0.283, loss_rpn_cls: 0.033, loss_rpn_bbox: 0.039, loss_mask: 0.263, time: 0.358
2020-09-24 08:45:56.724422, iter: 2050, lr: 0.01000, loss: 0.862, loss_cls: 0.229, loss_bbox: 0.234, loss_rpn_cls: 0.028, loss_rpn_bbox: 0.029, loss_mask: 0.296, time: 0.349
2020-09-24 08:46:14.279525, iter: 2100, lr: 0.01000, loss: 0.931, loss_cls: 0.326, loss_bbox: 0.273, loss_rpn_cls: 0.029, loss_rpn_bbox: 0.045, loss_mask: 0.278, time: 0.363
2020-09-24 08:46:31.880817, iter: 2150, lr: 0.01000, loss: 0.918, loss_cls: 0.254, loss_bbox: 0.265, loss_rpn_cls: 0.037, loss_rpn_bbox: 0.05, loss_mask: 0.293, time: 0.340
2020-09-24 08:46:49.439249, iter: 2200, lr: 0.01000, loss: 0.896, loss_cls: 0.297, loss_bbox: 0.276, loss_rpn_cls: 0.031, loss_rpn_bbox: 0.035, loss_mask: 0.248, time: 0.348
2020-09-24 08:47:06.864158, iter: 2250, lr: 0.01000, loss: 0.84, loss_cls: 0.257, loss_bbox: 0.208, loss_rpn_cls: 0.034, loss_rpn_bbox: 0.037, loss_mask: 0.237, time: 0.350
2020-09-24 08:47:24.302922, iter: 2300, lr: 0.01000, loss: 0.691, loss_cls: 0.195, loss_bbox: 0.177, loss_rpn_cls: 0.025, loss_rpn_bbox: 0.044, loss_mask: 0.246, time: 0.358
2020-09-24 08:47:41.697441, iter: 2350, lr: 0.01000, loss: 0.678, loss_cls: 0.189, loss_bbox: 0.232, loss_rpn_cls: 0.019, loss_rpn_bbox: 0.04, loss_mask: 0.219, time: 0.341
2020-09-24 08:47:59.279332, iter: 2400, lr: 0.01000, loss: 0.747, loss_cls: 0.192, loss_bbox: 0.237, loss_rpn_cls: 0.026, loss_rpn_bbox: 0.034, loss_mask: 0.219, time: 0.349
2020-09-24 08:48:16.736787, iter: 2450, lr: 0.01000, loss: 0.612, loss_cls: 0.178, loss_bbox: 0.192, loss_rpn_cls: 0.015, loss_rpn_bbox: 0.03, loss_mask: 0.23, time: 0.359
2020-09-24 08:48:34.234305, iter: 2500, lr: 0.01000, loss: 0.555, loss_cls: 0.158, loss_bbox: 0.149, loss_rpn_cls: 0.016, loss_rpn_bbox: 0.02, loss_mask: 0.171, time: 0.339
2020-09-24 08:48:51.707827, iter: 2550, lr: 0.01000, loss: 0.587, loss_cls: 0.142, loss_bbox: 0.192, loss_rpn_cls: 0.021, loss_rpn_bbox: 0.038, loss_mask: 0.23, time: 0.356
2020-09-24 08:49:09.077950, iter: 2600, lr: 0.01000, loss: 0.566, loss_cls: 0.137, loss_bbox: 0.186, loss_rpn_cls: 0.015, loss_rpn_bbox: 0.022, loss_mask: 0.202, time: 0.332
2020-09-24 08:49:26.564700, iter: 2650, lr: 0.01000, loss: 0.507, loss_cls: 0.134, loss_bbox: 0.142, loss_rpn_cls: 0.011, loss_rpn_bbox: 0.027, loss_mask: 0.169, time: 0.332
2020-09-24 08:49:44.117975, iter: 2700, lr: 0.01000, loss: 0.75, loss_cls: 0.204, loss_bbox: 0.246, loss_rpn_cls: 0.019, loss_rpn_bbox: 0.03, loss_mask: 0.241, time: 0.353
2020-09-24 08:50:01.599832, iter: 2750, lr: 0.01000, loss: 0.552, loss_cls: 0.152, loss_bbox: 0.147, loss_rpn_cls: 0.018, loss_rpn_bbox: 0.036, loss_mask: 0.177, time: 0.348
2020-09-24 08:50:19.073621, iter: 2800, lr: 0.01000, loss: 0.598, loss_cls: 0.169, loss_bbox: 0.145, loss_rpn_cls: 0.017, loss_rpn_bbox: 0.02, loss_mask: 0.199, time: 0.351
2020-09-24 08:50:36.563157, iter: 2850, lr: 0.01000, loss: 0.685, loss_cls: 0.229, loss_bbox: 0.199, loss_rpn_cls: 0.018, loss_rpn_bbox: 0.027, loss_mask: 0.218, time: 0.352
2020-09-24 08:50:54.105322, iter: 2900, lr: 0.01000, loss: 0.645, loss_cls: 0.187, loss_bbox: 0.151, loss_rpn_cls: 0.014, loss_rpn_bbox: 0.035, loss_mask: 0.234, time: 0.363
2020-09-24 08:51:11.638857, iter: 2950, lr: 0.01000, loss: 0.463, loss_cls: 0.119, loss_bbox: 0.13, loss_rpn_cls: 0.015, loss_rpn_bbox: 0.03, loss_mask: 0.201, time: 0.345

 

飞浆测试日志

标签:padding   filter   read   ide   lse   eating   horizon   fuse   snapshot   

原文地址:https://www.cnblogs.com/herd/p/13722394.html

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