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hahattpro / crowd_counting_framework (public) (License: Unspecified) (since 2020-12-23) (hash sha1)

backupfrom https://github.com/ttpro1995/crowd_counting_framework

Clone URLs: https://rocketgit.com/user/hahattpro/crowd_counting_framework ssh://rocketgit@ssh.rocketgit.com/user/hahattpro/crowd_counting_framework git://git.rocketgit.com/user/hahattpro/crowd_counting_framework

List of commits:

Subject	Hash	Author	Date (UTC)
add evaluation only	d86462407743bd2ac65c778aeb7e172faea806e1	Thai Thien	2020-08-04 17:26:45
s	d2c5d384ed61127c4fd3351692381b80a30c74aa	Thai Thien	2020-08-04 17:02:33
WIP	fce5736b0f6104fa3549884fbaa1f6508086af06	Thai Thien	2020-08-03 17:14:11
debug sha keepful	e14c3307499356c7a7ed0d5f33818bd798276d94	Thai Thien	2020-08-03 15:44:02
adamw2_bigtail13i_t3_sha	f769948ddd511865f62cddc80957663508e25976	Thai Thien	2020-08-02 04:25:08
g	56048b30fb4a19ae52c641b07754756f43ddcefb	Thai Thien	2020-08-02 04:00:46
a	d4e0e0d63613536a18f7ae0f39e4798f12abe7e8	Thai Thien	2020-08-02 03:59:14
adamw1_bigtail13i_t4_sha	bc07d19cfcc88c4271d1c6f1984c1c96ff5a9413	Thai Thien	2020-08-01 16:19:17
adamw1_bigtail13i_t3_sha	17c169d6ef648e8c4f2c5383fb9226cfce48d626	Thai Thien	2020-08-01 16:11:33
adamw1_bigtail13i_t2_sha	8bc23f1401eacdc2e28f30a825503f0dd96bacc9	Thai Thien	2020-08-01 15:59:29
adamw1_bigtail13i_t2_shb	aadc7244daabdad64a548342865a22beda073d94	Thai Thien	2020-08-01 15:47:08
gpu4	95c356f61c49d9f1927da7f86135a9bb60d21a59	Thai Thien	2020-08-01 14:46:30
adamw1_bigtail13i_t1_sha	34434bd013a4b05134c5ce42aa8f9956d424467d	Thai Thien	2020-08-01 14:44:56
a	140443bb072f8086b6cef253bcadfb0d925ba606	Thai Thien	2020-08-01 12:09:09
adamw	57f61e52a024e91f57347c85a8c14813df16d15d	Thai Thien	2020-08-01 12:05:36
adam1_bigtail13i_t1_shb	713dd1d5a0f13a2c881b00687fabb1174383da5b	Thai Thien	2020-08-01 10:22:17
g1_BigTail14i_t8_sha	eb361a5e64d38062fa6e5aa61ae21adc5a536aef	Thai Thien	2020-07-31 15:45:50
g1_BigTail14i_t7_sha	32ff746fa0c272af36eadcd713cda94ef8f1b8e2	Thai Thien	2020-07-31 14:57:15
g1_BigTail14i_t6_sha	0656f2ac088bd2790b560931839bfa1d4bed98c4	Thai Thien	2020-07-30 19:32:13
sgd -6 g1_BigTail14i_t6_sha.sh	4c2877d478c40382109800e5a4b873d7a11b345c	Thai Thien	2020-07-30 19:29:58

Commit d86462407743bd2ac65c778aeb7e172faea806e1 - add evaluation only
Author: Thai Thien
Author date (UTC): 2020-08-04 17:26
Committer name: Thai Thien
Committer date (UTC): 2020-08-04 17:26
Parent(s): d2c5d384ed61127c4fd3351692381b80a30c74aa
Signing key:
Tree: f3d2c1622be23d3eee4b5488b46c837ac35f4f21

File	Lines added	Lines deleted
args_util.py	1	0
experiment_main.py	41	1

File args_util.py changed (mode: 100644) (index 5867a39..8eb8fa4)
...	...	def meow_parse():
132	132	# help="if true, use mse and negative ssim as loss function")	# help="if true, use mse and negative ssim as loss function")
133	133	parser.add_argument('--loss_fn', action="store", default="MSE", type=str)	parser.add_argument('--loss_fn', action="store", default="MSE", type=str)
134	134	parser.add_argument('--optim', action="store", default="adam", type=str)	parser.add_argument('--optim', action="store", default="adam", type=str)
	135		parser.add_argument('--eval_only', action="store_true", default=False)
135	136	arg = parser.parse_args()	arg = parser.parse_args()
136	137	return arg	return arg
137	138

File experiment_main.py changed (mode: 100644) (index 34c6625..74787c7)
...	...	if __name__ == "__main__":
339	339	trainer.add_event_handler(Events.EPOCH_COMPLETED(every=10), save_handler)	trainer.add_event_handler(Events.EPOCH_COMPLETED(every=10), save_handler)
340	340	evaluator_validate.add_event_handler(Events.EPOCH_COMPLETED(every=1), save_handler_best)	evaluator_validate.add_event_handler(Events.EPOCH_COMPLETED(every=1), save_handler_best)
341	341
342		trainer.run(train_loader, max_epochs=args.epochs)
	342		if args.eval_only:
	343		print("evaluation only, no training")
	344		evaluate_validate_timer.resume()
	345		evaluator_validate.run(val_loader)
	346		evaluate_validate_timer.pause()
	347		evaluate_validate_timer.step()
	348
	349		metrics = evaluator_validate.state.metrics
	350		timestamp = get_readable_time()
	351		print(timestamp + " Validation set Results - Avg mae: {:.2f} Avg mse: {:.2f} Avg loss: {:.2f}"
	352		.format( metrics['mae'], metrics['mse'], 0))
	353		experiment.log_metric("valid_mae", metrics['mae'])
	354		experiment.log_metric("valid_mse", metrics['mse'])
	355
	356		# timer
	357		experiment.log_metric("evaluate_valid_timer", evaluate_validate_timer.value())
	358		print("evaluate_valid_timer ", evaluate_validate_timer.value())
	359
	360		# check if that validate is best
	361		flag_mae = best_mae.checkAndRecord(metrics['mae'], metrics['mse'])
	362		flag_mse = best_mse.checkAndRecord(metrics['mae'], metrics['mse'])
	363
	364		if flag_mae or flag_mse:
	365		experiment.log_metric("valid_best_mae", metrics['mae'])
	366		experiment.log_metric("valid_best_mse", metrics['mse'])
	367		print("BEST VAL, evaluating on test set")
	368		evaluate_test_timer.resume()
	369		evaluator_test.run(test_loader)
	370		evaluate_test_timer.pause()
	371		evaluate_test_timer.step()
	372		test_metrics = evaluator_test.state.metrics
	373		timestamp = get_readable_time()
	374		print(timestamp + " Test set Results - Avg mae: {:.2f} Avg mse: {:.2f} Avg loss: {:.2f}"
	375		.format( test_metrics['mae'], test_metrics['mse'], 0))
	376		experiment.log_metric("test_mae", test_metrics['mae'])
	377		experiment.log_metric("test_mse", test_metrics['mse'])
	378		experiment.log_metric("evaluate_test_timer", evaluate_test_timer.value())
	379		print("evaluate_test_timer ", evaluate_test_timer.value())
	380		# experiment.log_metric("test_loss", test_metrics['loss'])
	381		else:
	382		trainer.run(train_loader, max_epochs=args.epochs)

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