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fix a number of bugs in textual inversion #1190

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Merged
merged 1 commit into from
Oct 21, 2022
Merged

fix a number of bugs in textual inversion #1190

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26 changes: 6 additions & 20 deletions main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -439,7 +439,7 @@ def __init__(
self.rescale = rescale
self.batch_freq = batch_frequency
self.max_images = max_images
self.logger_log_images = { pl.loggers.TestTubeLogger: self._testtube, } if torch.cuda.is_available() else { }
self.logger_log_images = { }
self.log_steps = [
2**n for n in range(int(np.log2(self.batch_freq)) + 1)
]
Expand All @@ -451,17 +451,6 @@ def __init__(
self.log_images_kwargs = log_images_kwargs if log_images_kwargs else {}
self.log_first_step = log_first_step

@rank_zero_only
def _testtube(self, pl_module, images, batch_idx, split):
for k in images:
grid = torchvision.utils.make_grid(images[k])
grid = (grid + 1.0) / 2.0 # -1,1 -> 0,1; c,h,w

tag = f'{split}/{k}'
pl_module.logger.experiment.add_image(
tag, grid, global_step=pl_module.global_step
)

@rank_zero_only
def log_local(
self, save_dir, split, images, global_step, current_epoch, batch_idx
Expand Down Expand Up @@ -714,7 +703,7 @@ def on_train_epoch_start(self, trainer, pl_module):
# merge trainer cli with config
trainer_config = lightning_config.get('trainer', OmegaConf.create())
# default to ddp
trainer_config['accelerator'] = 'ddp'
trainer_config['accelerator'] = 'auto'
for k in nondefault_trainer_args(opt):
trainer_config[k] = getattr(opt, k)
if not 'gpus' in trainer_config:
Expand Down Expand Up @@ -751,12 +740,8 @@ def on_train_epoch_start(self, trainer, pl_module):
trainer_kwargs = dict()

# default logger configs
if torch.cuda.is_available():
def_logger = 'testtube'
def_logger_target = 'TestTubeLogger'
else:
def_logger = 'csv'
def_logger_target = 'CSVLogger'
def_logger = 'csv'
def_logger_target = 'CSVLogger'
default_logger_cfgs = {
'wandb': {
'target': 'pytorch_lightning.loggers.WandbLogger',
Expand Down Expand Up @@ -918,7 +903,8 @@ def on_train_epoch_start(self, trainer, pl_module):
config.model.base_learning_rate,
)
if not cpu:
ngpu = len(lightning_config.trainer.gpus.strip(',').split(','))
gpus = str(lightning_config.trainer.gpus).strip(', ').split(',')
ngpu = len(gpus)
else:
ngpu = 1
if 'accumulate_grad_batches' in lightning_config.trainer:
Expand Down