def _perform_git_commit(filename, git_commit, git_message):
if git_commit and git.is_git():
reset('git') # resets git commit info
git.commit(git_message)
log('Git repository identified. Performing git commit...')
git_info = {
'repository': git.get_remote(),
'commit': git.get_current_commit(),
'filename': filename,
'path': git.get_relative_path(),
'branch': git.get_branch()
}
log_git(git_info, verbose=False)
def on_train_begin(self, n_epochs: int, metrics_names: list, **ka):
if self.reset_tracking:
reset('hyperparams', 'metrics')
hyp_dict = {
'epochs': n_epochs,
'batch_size': self.learn.data.batch_size,
'loss_func': str(self.learn.loss_func.func),
'opt_func': str(self.learn.opt_func.func).split("'")[1],
'weight_decay': self.learn.wd,
'learning_rate': str(self.learn.opt.lr)
}
if self.arch_name:
hyp_dict['arch_name'] = self.arch_name
log_hyperparams(hyp_dict)
if self.valid_set:
self.met_names.extend(metrics_names)
def on_train_begin(self, logs=None):
# Reset state if required
if self.reset_tracking:
reset('hyperparams', 'metrics')
hyp_dict = {
'epochs': self.params['epochs'],
'batch_size': self.params['batch_size'],
'loss_func': self.model.loss,
'opt':
str(self.model.optimizer.__class__).split("'")[1].split('.')[-1],
'wt_decay': self.model.optimizer.initial_decay,
'lr': str(get_value(self.model.optimizer.lr))
}
if self.arch_name:
hyp_dict['arch'] = self.arch_name
log_hyperparams(hyp_dict, verbose=False)
self.hyperparams = hyp_dict
def test_reset_hyperparams(self):
reset('hyperparams')
expected_result = [('fake_slug_metrics_1', 'metrics', {}),
('fake_slug_metrics_2', 'metrics', {})]
self.assertEqual(jovian.utils.records._data_blocks, expected_result)
def test_reset(self):
reset()
expected_result = []
self.assertEqual(jovian.utils.records._data_blocks, expected_result)
def test_reset_all():
with fake_records():
reset()
assert jovian.utils.records._data_blocks == []
def test_reset(metric_type, expected_result):
with fake_records():
reset(*metric_type)
assert jovian.utils.records._data_blocks == expected_result