2020-12-25 04:41:29,977 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.9937539794921877 Accuracy: 25.07%)
2020-12-25 04:41:35,673 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.100000 ==> eval_score=25.070000
2020-12-25 04:41:35,673 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:41:36,653 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.302294848632813 Accuracy: 25.97%)
2020-12-25 04:41:41,922 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.200000 ==> eval_score=25.970000
2020-12-25 04:41:41,922 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:41:42,861 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.427123193359375 Accuracy: 26.27%)
2020-12-25 04:41:48,936 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.300000 ==> eval_score=26.270000
2020-12-25 04:41:48,937 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:41:49,904 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.454738647460937 Accuracy: 26.18%)
2020-12-25 04:41:55,963 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.400000 ==> eval_score=26.180000
2020-12-25 04:41:55,963 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:41:57,020 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.466765979003906 Accuracy: 26.32%)
2020-12-25 04:42:02,494 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.500000 ==> eval_score=26.320000
2020-12-25 04:42:02,495 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:42:03,435 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.470900659179687 Accuracy: 26.27%)
2020-12-25 04:42:08,722 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.600000 ==> eval_score=26.270000
2020-12-25 04:42:08,722 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:42:09,747 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.472457165527344 Accuracy: 26.34%)
2020-12-25 04:42:15,073 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.700000 ==> eval_score=26.340000
2020-12-25 04:42:15,073 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:42:16,082 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.473871508789062 Accuracy: 26.32%)
2020-12-25 04:42:21,475 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.800000 ==> eval_score=26.320000
2020-12-25 04:42:21,475 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:42:22,467 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.473880346679688 Accuracy: 26.32%)
2020-12-25 04:42:28,504 - CompRatioSelect - INFO - Layer features.3, comp_ratio 0.900000 ==> eval_score=26.320000
2020-12-25 04:42:28,505 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:42:29,555 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -2.657516162109375 Accuracy: 19.46%)
2020-12-25 04:42:34,095 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.100000 ==> eval_score=19.460000
2020-12-25 04:42:34,096 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:42:35,157 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.526272692871094 Accuracy: 23.48%)
2020-12-25 04:42:39,936 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.200000 ==> eval_score=23.480000
2020-12-25 04:42:39,936 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:42:41,059 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.122827709960937 Accuracy: 25.35%)
2020-12-25 04:42:45,778 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.300000 ==> eval_score=25.350000
2020-12-25 04:42:45,779 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:42:46,774 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.26903017578125 Accuracy: 25.84%)
2020-12-25 04:42:51,579 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.400000 ==> eval_score=25.840000
2020-12-25 04:42:51,580 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:42:52,546 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.369065234375 Accuracy: 26.15%)
2020-12-25 04:42:57,428 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.500000 ==> eval_score=26.150000
2020-12-25 04:42:57,429 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:42:58,634 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.4147089477539065 Accuracy: 26.15%)
2020-12-25 04:43:03,727 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.600000 ==> eval_score=26.150000
2020-12-25 04:43:03,727 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:43:04,952 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.438264562988281 Accuracy: 26.21%)
2020-12-25 04:43:09,909 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.700000 ==> eval_score=26.210000
2020-12-25 04:43:09,910 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:43:11,044 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.466131091308593 Accuracy: 26.22%)
2020-12-25 04:43:16,220 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.800000 ==> eval_score=26.220000
2020-12-25 04:43:16,221 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:43:17,553 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.47099775390625 Accuracy: 26.31%)
2020-12-25 04:43:22,763 - CompRatioSelect - INFO - Layer features.7, comp_ratio 0.900000 ==> eval_score=26.310000
2020-12-25 04:43:22,763 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:43:23,941 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.4297052734375 Accuracy: 23.56%)
2020-12-25 04:43:28,419 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.100000 ==> eval_score=23.560000
2020-12-25 04:43:28,419 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:43:29,609 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.108662158203125 Accuracy: 25.64%)
2020-12-25 04:43:34,491 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.200000 ==> eval_score=25.640000
2020-12-25 04:43:34,491 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:43:35,614 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.286140185546875 Accuracy: 25.89%)
2020-12-25 04:43:40,367 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.300000 ==> eval_score=25.890000
2020-12-25 04:43:40,367 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:43:41,732 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.365822741699219 Accuracy: 26.12%)
2020-12-25 04:43:47,099 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.400000 ==> eval_score=26.120000
2020-12-25 04:43:47,100 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:43:48,462 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.408419006347656 Accuracy: 26.18%)
2020-12-25 04:43:53,643 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.500000 ==> eval_score=26.180000
2020-12-25 04:43:53,643 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:43:54,974 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.429431652832031 Accuracy: 26.22%)
2020-12-25 04:44:00,308 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.600000 ==> eval_score=26.220000
2020-12-25 04:44:00,309 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:44:01,692 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.454393225097657 Accuracy: 26.31%)
2020-12-25 04:44:07,095 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.700000 ==> eval_score=26.310000
2020-12-25 04:44:07,096 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:44:08,546 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.462876599121094 Accuracy: 26.29%)
2020-12-25 04:44:13,948 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.800000 ==> eval_score=26.290000
2020-12-25 04:44:13,949 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:44:15,545 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.470846752929687 Accuracy: 26.33%)
2020-12-25 04:44:21,429 - CompRatioSelect - INFO - Layer features.10, comp_ratio 0.900000 ==> eval_score=26.330000
2020-12-25 04:44:21,429 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:44:22,698 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -2.8578366088867186 Accuracy: 21.33%)
2020-12-25 04:44:27,727 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.100000 ==> eval_score=21.330000
2020-12-25 04:44:27,728 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:44:29,007 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.730611340332031 Accuracy: 24.51%)
2020-12-25 04:44:34,132 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.200000 ==> eval_score=24.510000
2020-12-25 04:44:34,133 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:44:35,510 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.042912268066407 Accuracy: 25.55%)
2020-12-25 04:44:40,732 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.300000 ==> eval_score=25.550000
2020-12-25 04:44:40,733 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:44:42,175 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.2132582763671875 Accuracy: 25.87%)
2020-12-25 04:44:47,420 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.400000 ==> eval_score=25.870000
2020-12-25 04:44:47,421 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:44:48,806 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.3038884643554685 Accuracy: 26.14%)
2020-12-25 04:44:54,095 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.500000 ==> eval_score=26.140000
2020-12-25 04:44:54,096 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:44:55,891 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.367148352050782 Accuracy: 26.17%)
2020-12-25 04:45:01,514 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.600000 ==> eval_score=26.170000
2020-12-25 04:45:01,514 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:45:02,951 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.404570227050781 Accuracy: 26.24%)
2020-12-25 04:45:09,305 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.700000 ==> eval_score=26.240000
2020-12-25 04:45:09,306 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:45:10,867 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.431726611328125 Accuracy: 26.35%)
2020-12-25 04:45:17,471 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.800000 ==> eval_score=26.350000
2020-12-25 04:45:17,472 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:45:19,117 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.4540637084960935 Accuracy: 26.33%)
2020-12-25 04:45:24,975 - CompRatioSelect - INFO - Layer features.14, comp_ratio 0.900000 ==> eval_score=26.330000
2020-12-25 04:45:24,976 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:45:26,298 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -2.967351574707031 Accuracy: 22.61%)
2020-12-25 04:45:32,856 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.100000 ==> eval_score=22.610000
2020-12-25 04:45:32,856 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:45:34,400 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.7882016967773438 Accuracy: 24.8%)
2020-12-25 04:45:40,898 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.200000 ==> eval_score=24.800000
2020-12-25 04:45:40,898 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:45:42,567 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.065039904785157 Accuracy: 25.55%)
2020-12-25 04:45:49,479 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.300000 ==> eval_score=25.550000
2020-12-25 04:45:49,479 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:45:51,120 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.136180004882813 Accuracy: 25.47%)
2020-12-25 04:45:57,999 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.400000 ==> eval_score=25.470000
2020-12-25 04:45:58,000 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:45:59,694 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.2271967041015626 Accuracy: 21.34%)
2020-12-25 04:46:06,459 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.500000 ==> eval_score=21.340000
2020-12-25 04:46:06,460 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:46:08,337 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.259498095703125 Accuracy: 25.84%)
2020-12-25 04:46:15,259 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.600000 ==> eval_score=25.840000
2020-12-25 04:46:15,260 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:46:17,288 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.359782446289063 Accuracy: 26.36%)
2020-12-25 04:46:24,120 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.700000 ==> eval_score=26.360000
2020-12-25 04:46:24,120 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:46:26,007 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.373932788085938 Accuracy: 26.28%)
2020-12-25 04:46:31,722 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.800000 ==> eval_score=26.280000
2020-12-25 04:46:31,723 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:46:34,312 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.378542797851562 Accuracy: 26.13%)
2020-12-25 04:46:40,127 - CompRatioSelect - INFO - Layer features.17, comp_ratio 0.900000 ==> eval_score=26.130000
2020-12-25 04:46:40,128 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:46:41,466 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -2.8355881103515626 Accuracy: 22.04%)
2020-12-25 04:46:46,626 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.100000 ==> eval_score=22.040000
2020-12-25 04:46:46,627 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:46:48,043 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.7431603637695314 Accuracy: 24.77%)
2020-12-25 04:46:54,376 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.200000 ==> eval_score=24.770000
2020-12-25 04:46:54,377 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:46:56,046 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.9623151123046876 Accuracy: 25.43%)
2020-12-25 04:47:02,576 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.300000 ==> eval_score=25.430000
2020-12-25 04:47:02,577 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:47:04,264 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.016892028808594 Accuracy: 25.36%)
2020-12-25 04:47:10,927 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.400000 ==> eval_score=25.360000
2020-12-25 04:47:10,928 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:47:12,832 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -2.9982592163085937 Accuracy: 21.62%)
2020-12-25 04:47:18,439 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.500000 ==> eval_score=21.620000
2020-12-25 04:47:18,439 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:47:20,550 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.1691917724609375 Accuracy: 25.68%)
2020-12-25 04:47:27,538 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.600000 ==> eval_score=25.680000
2020-12-25 04:47:27,538 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:47:29,580 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.348636962890625 Accuracy: 26.0%)
2020-12-25 04:47:36,471 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.700000 ==> eval_score=26.000000
2020-12-25 04:47:36,471 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:47:38,537 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.365845581054687 Accuracy: 26.11%)
2020-12-25 04:47:45,273 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.800000 ==> eval_score=26.110000
2020-12-25 04:47:45,274 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:47:47,869 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.377284094238282 Accuracy: 26.21%)
2020-12-25 04:47:54,944 - CompRatioSelect - INFO - Layer features.20, comp_ratio 0.900000 ==> eval_score=26.210000
2020-12-25 04:47:54,944 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:47:56,500 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.0340448608398436 Accuracy: 21.96%)
2020-12-25 04:48:03,271 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.100000 ==> eval_score=21.960000
2020-12-25 04:48:03,272 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:48:04,924 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.7629205200195313 Accuracy: 24.75%)
2020-12-25 04:48:11,443 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.200000 ==> eval_score=24.750000
2020-12-25 04:48:11,444 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:48:13,242 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.9391884521484375 Accuracy: 25.29%)
2020-12-25 04:48:19,852 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.300000 ==> eval_score=25.290000
2020-12-25 04:48:19,853 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:48:21,681 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.3705059326171876 Accuracy: 24.66%)
2020-12-25 04:48:28,411 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.400000 ==> eval_score=24.660000
2020-12-25 04:48:28,412 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:48:30,648 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.092959033203125 Accuracy: 25.74%)
2020-12-25 04:48:37,312 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.500000 ==> eval_score=25.740000
2020-12-25 04:48:37,312 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:48:39,172 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.28777431640625 Accuracy: 26.1%)
2020-12-25 04:48:44,849 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.600000 ==> eval_score=26.100000
2020-12-25 04:48:44,850 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:48:46,773 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.3485037719726565 Accuracy: 26.15%)
2020-12-25 04:48:52,562 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.700000 ==> eval_score=26.150000
2020-12-25 04:48:52,563 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:48:54,458 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.346389123535157 Accuracy: 26.23%)
2020-12-25 04:49:00,556 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.800000 ==> eval_score=26.230000
2020-12-25 04:49:00,557 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:49:03,036 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.352585900878906 Accuracy: 26.15%)
2020-12-25 04:49:09,009 - CompRatioSelect - INFO - Layer features.24, comp_ratio 0.900000 ==> eval_score=26.150000
2020-12-25 04:49:09,010 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:49:10,548 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.7801083251953127 Accuracy: 25.25%)
2020-12-25 04:49:17,052 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.100000 ==> eval_score=25.250000
2020-12-25 04:49:17,053 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:49:19,019 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -3.7332941650390623 Accuracy: 25.15%)
2020-12-25 04:49:25,730 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.200000 ==> eval_score=25.150000
2020-12-25 04:49:25,730 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:49:27,792 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.2871577880859375 Accuracy: 26.15%)
2020-12-25 04:49:33,562 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.300000 ==> eval_score=26.150000
2020-12-25 04:49:33,562 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:49:35,739 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.318684301757813 Accuracy: 26.15%)
2020-12-25 04:49:41,820 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.400000 ==> eval_score=26.150000
2020-12-25 04:49:41,820 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:49:44,487 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.331072131347656 Accuracy: 26.23%)
2020-12-25 04:49:51,106 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.500000 ==> eval_score=26.230000
2020-12-25 04:49:51,107 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:49:53,532 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.3412935791015625 Accuracy: 26.06%)
2020-12-25 04:50:00,514 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.600000 ==> eval_score=26.060000
2020-12-25 04:50:00,514 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:50:02,973 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.335660168457031 Accuracy: 26.12%)
2020-12-25 04:50:09,331 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.700000 ==> eval_score=26.120000
2020-12-25 04:50:09,331 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:50:11,725 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.341002026367187 Accuracy: 26.2%)
2020-12-25 04:50:18,641 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.800000 ==> eval_score=26.200000
2020-12-25 04:50:18,641 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:50:21,077 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.321689184570313 Accuracy: 26.14%)
2020-12-25 04:50:28,207 - CompRatioSelect - INFO - Layer features.27, comp_ratio 0.900000 ==> eval_score=26.140000
2020-12-25 04:50:28,208 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:50:30,146 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.106214758300781 Accuracy: 26.06%)
2020-12-25 04:50:36,570 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.100000 ==> eval_score=26.060000
2020-12-25 04:50:36,570 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:50:38,711 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.141429211425781 Accuracy: 26.05%)
2020-12-25 04:50:45,328 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.200000 ==> eval_score=26.050000
2020-12-25 04:50:45,329 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:50:47,553 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.3922559204101566 Accuracy: 26.28%)
2020-12-25 04:50:54,127 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.300000 ==> eval_score=26.280000
2020-12-25 04:50:54,128 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:50:56,457 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.41832626953125 Accuracy: 26.31%)
2020-12-25 04:51:03,088 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.400000 ==> eval_score=26.310000
2020-12-25 04:51:03,089 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:51:05,738 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.41874228515625 Accuracy: 26.29%)
2020-12-25 04:51:12,448 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.500000 ==> eval_score=26.290000
2020-12-25 04:51:12,449 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:51:14,971 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.428370166015625 Accuracy: 26.34%)
2020-12-25 04:51:20,535 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.600000 ==> eval_score=26.340000
2020-12-25 04:51:20,535 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:51:23,104 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.425316186523437 Accuracy: 26.32%)
2020-12-25 04:51:28,800 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.700000 ==> eval_score=26.320000
2020-12-25 04:51:28,801 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:51:31,313 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.424797448730469 Accuracy: 26.33%)
2020-12-25 04:51:38,298 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.800000 ==> eval_score=26.330000
2020-12-25 04:51:38,298 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:51:40,846 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.425589099121094 Accuracy: 26.3%)
2020-12-25 04:51:47,909 - CompRatioSelect - INFO - Layer features.30, comp_ratio 0.900000 ==> eval_score=26.300000
2020-12-25 04:51:47,909 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:51:49,787 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.202631921386719 Accuracy: 26.16%)
2020-12-25 04:51:55,078 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.100000 ==> eval_score=26.160000
2020-12-25 04:51:55,078 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:51:56,859 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.437729772949218 Accuracy: 26.33%)
2020-12-25 04:52:03,866 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.200000 ==> eval_score=26.330000
2020-12-25 04:52:03,866 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:52:05,984 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.447308581542969 Accuracy: 26.28%)
2020-12-25 04:52:12,854 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.300000 ==> eval_score=26.280000
2020-12-25 04:52:12,855 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:52:14,919 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.448629248046875 Accuracy: 26.34%)
2020-12-25 04:52:21,235 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.400000 ==> eval_score=26.340000
2020-12-25 04:52:21,235 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:52:23,858 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.453668115234375 Accuracy: 26.35%)
2020-12-25 04:52:30,910 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.500000 ==> eval_score=26.350000
2020-12-25 04:52:30,910 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:52:33,562 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.459936291503906 Accuracy: 26.32%)
2020-12-25 04:52:39,488 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.600000 ==> eval_score=26.320000
2020-12-25 04:52:39,489 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:52:41,953 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.454297351074219 Accuracy: 26.32%)
2020-12-25 04:52:47,902 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.700000 ==> eval_score=26.320000
2020-12-25 04:52:47,903 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:52:50,178 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.4582498779296875 Accuracy: 26.34%)
2020-12-25 04:52:56,230 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.800000 ==> eval_score=26.340000
2020-12-25 04:52:56,231 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:52:58,577 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.457487329101562 Accuracy: 26.32%)
2020-12-25 04:53:05,134 - CompRatioSelect - INFO - Layer features.34, comp_ratio 0.900000 ==> eval_score=26.320000
2020-12-25 04:53:05,135 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:53:07,051 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.4527604858398435 Accuracy: 26.35%)
2020-12-25 04:53:13,869 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.100000 ==> eval_score=26.350000
2020-12-25 04:53:13,870 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:53:15,929 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.473125329589844 Accuracy: 26.3%)
2020-12-25 04:53:22,774 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.200000 ==> eval_score=26.300000
2020-12-25 04:53:22,775 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:53:24,962 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.470657238769531 Accuracy: 26.33%)
2020-12-25 04:53:32,119 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.300000 ==> eval_score=26.330000
2020-12-25 04:53:32,120 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:53:34,558 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.471886071777344 Accuracy: 26.33%)
2020-12-25 04:53:41,363 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.400000 ==> eval_score=26.330000
2020-12-25 04:53:41,363 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:53:44,200 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.4731350463867185 Accuracy: 26.35%)
2020-12-25 04:53:51,487 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.500000 ==> eval_score=26.350000
2020-12-25 04:53:51,488 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:53:54,195 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.472640344238282 Accuracy: 26.35%)
2020-12-25 04:54:01,592 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.600000 ==> eval_score=26.350000
2020-12-25 04:54:01,593 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:54:03,982 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.471326416015625 Accuracy: 26.34%)
2020-12-25 04:54:11,214 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.700000 ==> eval_score=26.340000
2020-12-25 04:54:11,214 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:54:13,659 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.470440930175781 Accuracy: 26.32%)
2020-12-25 04:54:19,516 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.800000 ==> eval_score=26.320000
2020-12-25 04:54:19,517 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:54:21,905 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.472367053222656 Accuracy: 26.34%)
2020-12-25 04:54:29,256 - CompRatioSelect - INFO - Layer features.37, comp_ratio 0.900000 ==> eval_score=26.340000
2020-12-25 04:54:29,257 - CompRatioSelect - INFO - Analyzing compression ratio: 0.1 =====================>
2020-12-25 04:54:31,205 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.45629208984375 Accuracy: 26.36%)
2020-12-25 04:54:38,147 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.100000 ==> eval_score=26.360000
2020-12-25 04:54:38,147 - CompRatioSelect - INFO - Analyzing compression ratio: 0.2 =====================>
2020-12-25 04:54:40,219 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.468901538085937 Accuracy: 26.34%)
2020-12-25 04:54:47,188 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.200000 ==> eval_score=26.340000
2020-12-25 04:54:47,188 - CompRatioSelect - INFO - Analyzing compression ratio: 0.3 =====================>
2020-12-25 04:54:49,283 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.471708813476562 Accuracy: 26.34%)
2020-12-25 04:54:56,266 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.300000 ==> eval_score=26.340000
2020-12-25 04:54:56,267 - CompRatioSelect - INFO - Analyzing compression ratio: 0.4 =====================>
2020-12-25 04:54:58,486 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.4703867065429685 Accuracy: 26.32%)
2020-12-25 04:55:05,295 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.400000 ==> eval_score=26.320000
2020-12-25 04:55:05,295 - CompRatioSelect - INFO - Analyzing compression ratio: 0.5 =====================>
2020-12-25 04:55:08,158 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.470028295898437 Accuracy: 26.33%)
2020-12-25 04:55:15,340 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.500000 ==> eval_score=26.330000
2020-12-25 04:55:15,341 - CompRatioSelect - INFO - Analyzing compression ratio: 0.6 =====================>
2020-12-25 04:55:18,115 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.471591943359375 Accuracy: 26.33%)
2020-12-25 04:55:25,419 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.600000 ==> eval_score=26.330000
2020-12-25 04:55:25,419 - CompRatioSelect - INFO - Analyzing compression ratio: 0.7 =====================>
2020-12-25 04:55:27,797 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.472099169921875 Accuracy: 26.32%)
2020-12-25 04:55:33,704 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.700000 ==> eval_score=26.320000
2020-12-25 04:55:33,704 - CompRatioSelect - INFO - Analyzing compression ratio: 0.8 =====================>
2020-12-25 04:55:36,037 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.471060083007813 Accuracy: 26.33%)
2020-12-25 04:55:42,865 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.800000 ==> eval_score=26.330000
2020-12-25 04:55:42,865 - CompRatioSelect - INFO - Analyzing compression ratio: 0.9 =====================>
2020-12-25 04:55:45,208 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.471531066894531 Accuracy: 26.33%)
2020-12-25 04:55:52,249 - CompRatioSelect - INFO - Layer features.40, comp_ratio 0.900000 ==> eval_score=26.330000
2020-12-25 04:55:52,250 - CompRatioSelect - INFO - Greedy selection: Saved eval dict to ./data/greedy_selection_eval_scores_dict.pkl
2020-12-25 04:55:52,255 - CompRatioSelect - INFO - Greedy selection: overall_min_score=19.460000, overall_max_score=26.360000
2020-12-25 04:55:52,255 - CompRatioSelect - INFO - Greedy selection: Original model cost=(Cost: memory=14715584, mac=313201664)
2020-12-25 04:56:42,651 - CompRatioSelect - INFO - Greedy selection: final choice - comp_ratio=0.749572, score=26.319991
2020-12-25 04:56:44,120 - ChannelPruning - INFO - finished linear regression fit
2020-12-25 04:56:45,965 - ChannelPruning - INFO - finished linear regression fit
2020-12-25 04:56:47,749 - ChannelPruning - INFO - finished linear regression fit
2020-12-25 04:56:50,293 - ChannelPruning - INFO - finished linear regression fit
2020-12-25 04:56:52,415 - ChannelPruning - INFO - finished linear regression fit
2020-12-25 04:56:54,523 - ChannelPruning - INFO - finished linear regression fit
--------------------testing----------------------------
Computing :Loss: -4.47374072265625 Accuracy: 26.32%)
--------------------testing----------------------------
Computing :Loss: -3.9216089111328123 Accuracy: 26.15%)
VGG01(
(features): Sequential(
(0): Conv2d(3, 44, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(1): BatchNorm2d(44, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU(inplace=True)
(3): Conv2d(44, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(4): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(5): ReLU(inplace=True)
(6): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(7): Conv2d(64, 115, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(8): BatchNorm2d(115, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(9): ReLU(inplace=True)
(10): Conv2d(115, 102, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(11): BatchNorm2d(102, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(12): ReLU(inplace=True)
(13): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(14): Conv2d(102, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(15): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(16): ReLU(inplace=True)
(17): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(18): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(19): ReLU(inplace=True)
(20): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(21): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(22): ReLU(inplace=True)
(23): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(24): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(25): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(26): ReLU(inplace=True)
(27): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(28): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(29): ReLU(inplace=True)
(30): Conv2d(512, 204, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(31): BatchNorm2d(204, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(32): ReLU(inplace=True)
(33): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(34): Conv2d(204, 51, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(35): BatchNorm2d(51, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(36): ReLU(inplace=True)
(37): Conv2d(51, 51, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(38): BatchNorm2d(51, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(39): ReLU(inplace=True)
(40): Conv2d(51, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(41): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(42): ReLU(inplace=True)
(43): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(44): AvgPool2d(kernel_size=1, stride=1, padding=0)
)
(classifier): Linear(in_features=512, out_features=10, bias=True)
)
**********************************************************************************************
Compressed Model Statistics
Baseline model accuracy: 26.320000, Compressed model accuracy: 26.150000
Compression ratio for memory=0.438253, mac=0.749572
**********************************************************************************************
Per-layer Stats
Name:features.3, compression-ratio: 0.7
Name:features.7, compression-ratio: None
Name:features.10, compression-ratio: 0.9
Name:features.14, compression-ratio: 0.8
Name:features.17, compression-ratio: None
Name:features.20, compression-ratio: None
Name:features.24, compression-ratio: None
Name:features.27, compression-ratio: None
Name:features.30, compression-ratio: None
Name:features.34, compression-ratio: 0.4
Name:features.37, compression-ratio: 0.1
Name:features.40, compression-ratio: 0.1
**********************************************************************************************
Greedy Eval Dict
Layer: features.3
Ratio=0.1, Eval score=25.07
Ratio=0.2, Eval score=25.97
Ratio=0.3, Eval score=26.27
Ratio=0.4, Eval score=26.18
Ratio=0.5, Eval score=26.32
Ratio=0.6, Eval score=26.27
Ratio=0.7, Eval score=26.34
Ratio=0.8, Eval score=26.32
Ratio=0.9, Eval score=26.32
Layer: features.7
Ratio=0.1, Eval score=19.46
Ratio=0.2, Eval score=23.48
Ratio=0.3, Eval score=25.35
Ratio=0.4, Eval score=25.84
Ratio=0.5, Eval score=26.15
Ratio=0.6, Eval score=26.15
Ratio=0.7, Eval score=26.21
Ratio=0.8, Eval score=26.22
Ratio=0.9, Eval score=26.31
Layer: features.10
Ratio=0.1, Eval score=23.56
Ratio=0.2, Eval score=25.64
Ratio=0.3, Eval score=25.89
Ratio=0.4, Eval score=26.12
Ratio=0.5, Eval score=26.18
Ratio=0.6, Eval score=26.22
Ratio=0.7, Eval score=26.31
Ratio=0.8, Eval score=26.29
Ratio=0.9, Eval score=26.33
Layer: features.14
Ratio=0.1, Eval score=21.33
Ratio=0.2, Eval score=24.51
Ratio=0.3, Eval score=25.55
Ratio=0.4, Eval score=25.87
Ratio=0.5, Eval score=26.14
Ratio=0.6, Eval score=26.17
Ratio=0.7, Eval score=26.24
Ratio=0.8, Eval score=26.35
Ratio=0.9, Eval score=26.33
Layer: features.17
Ratio=0.1, Eval score=22.61
Ratio=0.2, Eval score=24.8
Ratio=0.3, Eval score=25.55
Ratio=0.4, Eval score=25.47
Ratio=0.5, Eval score=21.34
Ratio=0.6, Eval score=25.84
Ratio=0.7, Eval score=26.36
Ratio=0.8, Eval score=26.28
Ratio=0.9, Eval score=26.13
Layer: features.20
Ratio=0.1, Eval score=22.04
Ratio=0.2, Eval score=24.77
Ratio=0.3, Eval score=25.43
Ratio=0.4, Eval score=25.36
Ratio=0.5, Eval score=21.62
Ratio=0.6, Eval score=25.68
Ratio=0.7, Eval score=26.0
Ratio=0.8, Eval score=26.11
Ratio=0.9, Eval score=26.21
Layer: features.24
Ratio=0.1, Eval score=21.96
Ratio=0.2, Eval score=24.75
Ratio=0.3, Eval score=25.29
Ratio=0.4, Eval score=24.66
Ratio=0.5, Eval score=25.74
Ratio=0.6, Eval score=26.1
Ratio=0.7, Eval score=26.15
Ratio=0.8, Eval score=26.23
Ratio=0.9, Eval score=26.15
Layer: features.27
Ratio=0.1, Eval score=25.25
Ratio=0.2, Eval score=25.15
Ratio=0.3, Eval score=26.15
Ratio=0.4, Eval score=26.15
Ratio=0.5, Eval score=26.23
Ratio=0.6, Eval score=26.06
Ratio=0.7, Eval score=26.12
Ratio=0.8, Eval score=26.2
Ratio=0.9, Eval score=26.14
Layer: features.30
Ratio=0.1, Eval score=26.06
Ratio=0.2, Eval score=26.05
Ratio=0.3, Eval score=26.28
Ratio=0.4, Eval score=26.31
Ratio=0.5, Eval score=26.29
Ratio=0.6, Eval score=26.34
Ratio=0.7, Eval score=26.32
Ratio=0.8, Eval score=26.33
Ratio=0.9, Eval score=26.3
Layer: features.34
Ratio=0.1, Eval score=26.16
Ratio=0.2, Eval score=26.33
Ratio=0.3, Eval score=26.28
Ratio=0.4, Eval score=26.34
Ratio=0.5, Eval score=26.35
Ratio=0.6, Eval score=26.32
Ratio=0.7, Eval score=26.32
Ratio=0.8, Eval score=26.34
Ratio=0.9, Eval score=26.32
Layer: features.37
Ratio=0.1, Eval score=26.35
Ratio=0.2, Eval score=26.3
Ratio=0.3, Eval score=26.33
Ratio=0.4, Eval score=26.33
Ratio=0.5, Eval score=26.35
Ratio=0.6, Eval score=26.35
Ratio=0.7, Eval score=26.34
Ratio=0.8, Eval score=26.32
Ratio=0.9, Eval score=26.34
Layer: features.40
Ratio=0.1, Eval score=26.36
Ratio=0.2, Eval score=26.34
Ratio=0.3, Eval score=26.34
Ratio=0.4, Eval score=26.32
Ratio=0.5, Eval score=26.33
Ratio=0.6, Eval score=26.33
Ratio=0.7, Eval score=26.32
Ratio=0.8, Eval score=26.33
Ratio=0.9, Eval score=26.33
**********************************************************************************************
Process finished with exit code 0