🔨 Pass pre-trained from config to ModelLightning (#529)

Pass pre-trained from config to LightningModule
openvinotoolkit · Sep 9, 2022 · baca449 · baca449
1 parent dff86b1
commit baca449
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diff --git a/anomalib/models/cflow/lightning_model.py b/anomalib/models/cflow/lightning_model.py
@@ -185,6 +185,7 @@ def __init__(self, hparams: Union[DictConfig, ListConfig]) -> None:
             input_size=hparams.model.input_size,
             backbone=hparams.model.backbone,
             layers=hparams.model.layers,
+            pre_trained=hparams.model.pre_trained,
             fiber_batch_size=hparams.dataset.fiber_batch_size,
             decoder=hparams.model.decoder,
             condition_vector=hparams.model.condition_vector,

diff --git a/anomalib/models/dfkde/lightning_model.py b/anomalib/models/dfkde/lightning_model.py
@@ -119,6 +119,7 @@ def __init__(self, hparams: Union[DictConfig, ListConfig]) -> None:
         super().__init__(
             layers=hparams.model.layers,
             backbone=hparams.model.backbone,
+            pre_trained=hparams.model.pre_trained,
             max_training_points=hparams.model.max_training_points,
             pre_processing=hparams.model.pre_processing,
             n_components=hparams.model.n_components,

diff --git a/anomalib/models/dfm/lightning_model.py b/anomalib/models/dfm/lightning_model.py
@@ -118,6 +118,7 @@ def __init__(self, hparams: Union[DictConfig, ListConfig]) -> None:
         super().__init__(
             backbone=hparams.model.backbone,
             layer=hparams.model.layer,
+            pre_trained=hparams.model.pre_trained,
             pooling_kernel_size=hparams.model.pooling_kernel_size,
             pca_level=hparams.model.pca_level,
             score_type=hparams.model.score_type,

diff --git a/anomalib/models/fastflow/lightning_model.py b/anomalib/models/fastflow/lightning_model.py
@@ -90,6 +90,7 @@ def __init__(self, hparams: Union[DictConfig, ListConfig]) -> None:
         super().__init__(
             input_size=hparams.model.input_size,
             backbone=hparams.model.backbone,
+            pre_trained=hparams.model.pre_trained,
             flow_steps=hparams.model.flow_steps,
             conv3x3_only=hparams.model.conv3x3_only,
             hidden_ratio=hparams.model.hidden_ratio,

diff --git a/anomalib/models/patchcore/lightning_model.py b/anomalib/models/patchcore/lightning_model.py
@@ -124,6 +124,7 @@ def __init__(self, hparams) -> None:
             input_size=hparams.model.input_size,
             backbone=hparams.model.backbone,
             layers=hparams.model.layers,
+            pre_trained=hparams.model.pre_trained,
             coreset_sampling_ratio=hparams.model.coreset_sampling_ratio,
             num_neighbors=hparams.model.num_neighbors,
         )

diff --git a/anomalib/models/reverse_distillation/lightning_model.py b/anomalib/models/reverse_distillation/lightning_model.py
@@ -121,6 +121,7 @@ def __init__(self, hparams: Union[DictConfig, ListConfig]):
             input_size=hparams.model.input_size,
             backbone=hparams.model.backbone,
             layers=hparams.model.layers,
+            pre_trained=hparams.model.pre_trained,
             anomaly_map_mode=hparams.model.anomaly_map_mode,
             lr=hparams.model.lr,
             beta1=hparams.model.beta1,