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Add support for list-of-directory data format for wandb (#2719)

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Ayush Chaurasia 2021-04-06 20:27:13 +05:30 committed by GitHub
parent ec8979f1d2
commit 3067429307
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1 changed files with 6 additions and 4 deletions
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10
utils/wandb_logging/wandb_utils.py
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@ -57,14 +57,14 @@ def process_wandb_config_ddp_mode(opt):
with open(opt.data) as f:
data_dict = yaml.load(f, Loader=yaml.SafeLoader) # data dict
train_dir, val_dir = None, None
if data_dict['train'].startswith(WANDB_ARTIFACT_PREFIX):
if isinstance(data_dict['train'], str) and data_dict['train'].startswith(WANDB_ARTIFACT_PREFIX):
api = wandb.Api()
train_artifact = api.artifact(remove_prefix(data_dict['train']) + ':' + opt.artifact_alias)
train_dir = train_artifact.download()
train_path = Path(train_dir) / 'data/images/'
data_dict['train'] = str(train_path)
if data_dict['val'].startswith(WANDB_ARTIFACT_PREFIX):
if isinstance(data_dict['val'], str) and data_dict['val'].startswith(WANDB_ARTIFACT_PREFIX):
api = wandb.Api()
val_artifact = api.artifact(remove_prefix(data_dict['val']) + ':' + opt.artifact_alias)
val_dir = val_artifact.download()
@ -158,7 +158,7 @@ class WandbLogger():
return data_dict
def download_dataset_artifact(self, path, alias):
if path and path.startswith(WANDB_ARTIFACT_PREFIX):
if isinstance(path, str) and path.startswith(WANDB_ARTIFACT_PREFIX):
dataset_artifact = wandb.use_artifact(remove_prefix(path, WANDB_ARTIFACT_PREFIX) + ":" + alias)
assert dataset_artifact is not None, "'Error: W&B dataset artifact doesn\'t exist'"
datadir = dataset_artifact.download()
@ -229,7 +229,9 @@ class WandbLogger():
def create_dataset_table(self, dataset, class_to_id, name='dataset'):
# TODO: Explore multiprocessing to slpit this loop parallely| This is essential for speeding up the the logging
artifact = wandb.Artifact(name=name, type="dataset")
for img_file in tqdm([dataset.path]) if Path(dataset.path).is_dir() else tqdm(dataset.img_files):
img_files = tqdm([dataset.path]) if isinstance(dataset.path, str) and Path(dataset.path).is_dir() else None
img_files = tqdm(dataset.img_files) if not img_files else img_files
for img_file in img_files:
if Path(img_file).is_dir():
artifact.add_dir(img_file, name='data/images')
labels_path = 'labels'.join(dataset.path.rsplit('images', 1))