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Fix model.get #1287

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merged 9 commits into from
Aug 7, 2023
Merged

Fix model.get #1287

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d7ba737
fix
Louis-Dupont Jul 18, 2023
852c5c7
fix
Louis-Dupont Jul 19, 2023
1f3901e
fix
Louis-Dupont Jul 19, 2023
d60d8e3
fix test
Louis-Dupont Jul 19, 2023
c7accb4
Merge branch 'master' into hotfix/SG-000-fix_model_get_plat
Louis-Dupont Jul 30, 2023
dd11496
Merge branch 'master' into hotfix/SG-000-fix_model_get_plat
Louis-Dupont Aug 1, 2023
1ad4f24
Merge branch 'master' into hotfix/SG-000-fix_model_get_plat
Louis-Dupont Aug 3, 2023
f658450
Merge branch 'master' into hotfix/SG-000-fix_model_get_plat
BloodAxe Aug 7, 2023
9bca9ff
add docstring
Louis-Dupont Aug 7, 2023
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16 changes: 10 additions & 6 deletions src/super_gradients/training/models/model_factory.py
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Original file line number Diff line number Diff line change
Expand Up @@ -132,11 +132,15 @@ def instantiate_model(
if pretrained_weights is None and num_classes is None:
raise ValueError("num_classes or pretrained_weights must be passed to determine net's structure.")

if pretrained_weights and pretrained_weights in PRETRAINED_NUM_CLASSES.keys():
num_classes_new_head = core_utils.get_param(arch_params, "num_classes", PRETRAINED_NUM_CLASSES[pretrained_weights])
arch_params.num_classes = PRETRAINED_NUM_CLASSES[pretrained_weights]
elif pretrained_weights and pretrained_weights is None:
raise ValueError(f"Unknown pretrained_weights - couldn't find pretrained weights in {PRETRAINED_NUM_CLASSES.keys()} or platform.")
if pretrained_weights:
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if pretrained_weights in PRETRAINED_NUM_CLASSES.keys():
num_classes_new_head = core_utils.get_param(arch_params, "num_classes", PRETRAINED_NUM_CLASSES[pretrained_weights])
arch_params.num_classes = PRETRAINED_NUM_CLASSES[pretrained_weights]
elif not download_platform_weights:
raise ValueError(
f'`pretrained_weights="{pretrained_weights}"` is not a valid and was not found in that platform. '
f'Valid pretrained weights are: "{PRETRAINED_NUM_CLASSES.keys()}"'
)

# Most of the SG models work with a single params names "arch_params" of type HpmStruct, but a few take
# **kwargs instead
Expand All @@ -151,7 +155,7 @@ def instantiate_model(
else:
load_pretrained_weights(net, model_name, pretrained_weights)

if num_classes_new_head != arch_params.num_classes:
if pretrained_weights in PRETRAINED_NUM_CLASSES.keys() and num_classes_new_head != arch_params.num_classes:
net.replace_head(new_num_classes=num_classes_new_head)
arch_params.num_classes = num_classes_new_head

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