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W&B: More improvements and refactoring (#4205) 

* Improve docstrings and run names

* default wandb login prompt with timeout

* return key

* Update api_key check logic

* Properly support zipped dataset feature

* update docstring

* Revert tuorial change

* extend changes to log_dataset

* add run name

* bug fix

* bug fix

* Update comment

* fix import check

* remove unused import

* Hardcore .yaml file extension

* reduce code

* Reformat using pycharm

* Remove redundant try catch

* More refactoring and bug fixes

* retry

* Reformat using pycharm

* respect LOGGERS include list

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
pull/4224/head
Ayush Chaurasia 2021-07-29 02:55:15 +05:30 committed by GitHub
parent e016b15555
commit 750465edae
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2 changed files with 8 additions and 7 deletions
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8
utils/loggers/__init__.py
View File

@ -48,12 +48,12 @@ class Loggers():
self.tb = SummaryWriter(str(s))
# W&B
try:
assert 'wandb' in self.include and wandb
run_id = torch.load(self.weights).get('wandb_id') if self.opt.resume else None
if wandb and 'wandb' in self.include:
wandb_artifact_resume = isinstance(self.opt.resume, str) and self.opt.resume.startswith('wandb-artifact://')
run_id = torch.load(self.weights).get('wandb_id') if self.opt.resume and not wandb_artifact_resume else None
self.opt.hyp = self.hyp # add hyperparameters
self.wandb = WandbLogger(self.opt, run_id)
except:
else:
self.wandb = None
return self

7
utils/loggers/wandb/wandb_utils.py
View File

@ -158,11 +158,12 @@ class WandbLogger():
self.data_dict = check_dataset(opt.data)
self.setup_training(opt)
# write data_dict to config. useful for resuming from artifacts
if not self.wandb_artifact_data_dict:
self.wandb_artifact_data_dict = self.data_dict
self.wandb_run.config.update({'data_dict': self.wandb_artifact_data_dict},
allow_val_change=True)
# write data_dict to config. useful for resuming from artifacts. Do this only when not resuming.
if not opt.resume:
self.wandb_run.config.update({'data_dict': self.wandb_artifact_data_dict},
allow_val_change=True)
if self.job_type == 'Dataset Creation':
self.data_dict = self.check_and_upload_dataset(opt)