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Remove unused parameter num_shuffles from check_for_weights function. #2360

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Merged
MMathisLab merged 6 commits into from
Sep 13, 2023
Merged

Remove unused parameter num_shuffles from check_for_weights function. #2360

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1c7c34a
Update auxfun_models.py
Tetra-quark Aug 24, 2023
71588fe
Update trainingsetmanipulation.py
Tetra-quark Aug 24, 2023
af0d164
Update multiple_individuals_trainingsetmanipulation.py
Tetra-quark Aug 24, 2023
b9e7c94
Update test_auxfun_models.py
Tetra-quark Aug 24, 2023
94a45a5
Update modelzoo.py
Tetra-quark Aug 24, 2023
ede902f
Minor fix
jeylau Aug 31, 2023
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2 changes: 1 addition & 1 deletion deeplabcut/create_project/modelzoo.py
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Expand Up @@ -273,7 +273,7 @@ def create_pretrained_project(
auxiliaryfunctions.edit_config(cfg, dict_)

# downloading base encoder / not required unless on re-trains (but when a training set is created this happens anyway)
# model_path, num_shuffles=auxfun_models.Check4weights(pose_cfg['net_type'], parent_path, num_shuffles= 1)
# model_path = auxfun_models.check_for_weights(pose_cfg['net_type'], parent_path)

# Updating training and test pose_cfg:
snapshotname = [fn for fn in os.listdir(train_dir) if ".meta" in fn][0].split(
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4 changes: 2 additions & 2 deletions deeplabcut/generate_training_dataset/multiple_individuals_trainingsetmanipulation.py
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Expand Up @@ -272,8 +272,8 @@ def create_multianimaltraining_dataset(
# Loading the encoder (if necessary downloading from TF)
dlcparent_path = auxiliaryfunctions.get_deeplabcut_path()
defaultconfigfile = os.path.join(dlcparent_path, "pose_cfg.yaml")
model_path, num_shuffles = auxfun_models.check_for_weights(
net_type, Path(dlcparent_path), num_shuffles
model_path = auxfun_models.check_for_weights(
net_type, Path(dlcparent_path)
)

if Shuffles is None:
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4 changes: 2 additions & 2 deletions deeplabcut/generate_training_dataset/trainingsetmanipulation.py
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Expand Up @@ -916,8 +916,8 @@ def create_training_dataset(
defaultconfigfile = os.path.join(dlcparent_path, "pose_cfg.yaml")
elif posecfg_template:
defaultconfigfile = posecfg_template
model_path, num_shuffles = auxfun_models.check_for_weights(
net_type, Path(dlcparent_path), num_shuffles
model_path = auxfun_models.check_for_weights(
net_type, Path(dlcparent_path)
)

if Shuffles is None:
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6 changes: 3 additions & 3 deletions deeplabcut/utils/auxfun_models.py
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Expand Up @@ -44,15 +44,15 @@
}


def check_for_weights(modeltype, parent_path, num_shuffles):
def check_for_weights(modeltype, parent_path):
"""gets local path to network weights and checks if they are present. If not, downloads them from tensorflow.org"""

if modeltype not in MODELTYPE_FILEPATH_MAP.keys():
print(
"Currently ResNet (50, 101, 152), MobilenetV2 (1, 0.75, 0.5 and 0.35) and EfficientNet (b0-b6) are supported, please change 'resnet' entry in config.yaml!"
)
# Exit the function early if an unknown modeltype is provided.
return parent_path, -1
return parent_path

exists = False
model_path = parent_path / MODELTYPE_FILEPATH_MAP[modeltype]
Expand All @@ -70,7 +70,7 @@ def check_for_weights(modeltype, parent_path, num_shuffles):
else:
download_weights(modeltype, model_path)

return str(model_path), num_shuffles
return str(model_path)


def download_weights(modeltype, model_path):
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7 changes: 3 additions & 4 deletions tests/test_auxfun_models.py
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Expand Up @@ -25,7 +25,7 @@ def test_filepaths_for_modeltypes(self):
"deeplabcut.utils.auxfun_models.download_weights"
) as mocked_download:
for modeltype, expected_path in MODELTYPE_FILEPATH_MAP.items():
actual_path, _ = check_for_weights(modeltype, Path(tmpdir), 1)
actual_path = check_for_weights(modeltype, Path(tmpdir))
self.assertIn(str(expected_path), actual_path)
if "efficientnet" in modeltype:
mocked_download.assert_called_with(
Expand All @@ -37,8 +37,7 @@ def test_filepaths_for_modeltypes(self):
)

def test_bad_modeltype(self):
actual_path, actual_num_shuffles = check_for_weights(
"dummymodel", "nonexistentpath", 1
actual_path = check_for_weights(
"dummymodel", "nonexistentpath"
)
self.assertEqual(actual_path, "nonexistentpath")
self.assertEqual(actual_num_shuffles, -1)