Expose more parame to the UI

external/anomaly/anomaly_classification/configs/padim/configuration.py

@@ -18,7 +18,13 @@
 
 from attr import attrs
 from ote_anomalib.configs.configuration import BaseAnomalyConfig
-from ote_sdk.configuration.elements import string_attribute
+from ote_anomalib.configs.configuration_enums import ModelBackbone
+from ote_sdk.configuration.elements import (
+    ParameterGroup,
+    add_parameter_group,
+    selectable,
+    string_attribute,
+)
 
 
 @attrs
@@ -29,3 +35,20 @@ class PadimAnomalyClassificationConfig(BaseAnomalyConfig):
 
     header = string_attribute("Configuration for Padim")
     description = header
+
+    @attrs
+    class ModelParameters(ParameterGroup):
+        """
+        Parameter Group for tuning the model
+        """
+
+        header = string_attribute("Model Parameters")
+        description = header
+
+        backbone = selectable(
+            default_value=ModelBackbone.RESNET18,
+            header="Model Backbone",
+            description="Pre-trained backbone used for feature extraction",
+        )
+
+    model = add_parameter_group(ModelParameters)

external/anomaly/anomaly_classification/configs/padim/configuration.yaml

@@ -3,6 +3,8 @@ dataset:
   header: Dataset Parameters
   num_workers:
     affects_outcome_of: NONE
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
     default_value: 8
     description:
       Increasing this value might improve training speed however it might
@@ -18,10 +20,13 @@ dataset:
       operator: AND
       rules: []
       type: UI_RULES
+    value: 8
     visible_in_ui: true
     warning: null
   train_batch_size:
     affects_outcome_of: TRAINING
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
     default_value: 32
     description:
       The number of training samples seen in each iteration of training.
@@ -37,6 +42,7 @@ dataset:
       operator: AND
       rules: []
       type: UI_RULES
+    value: 32
     visible_in_ui: true
     warning:
       Increasing this value may cause the system to use more memory than available,
@@ -45,50 +51,56 @@ dataset:
   visible_in_ui: true
 description: Configuration for Padim
 header: Configuration for Padim
-pot_parameters:
-  description: POT Parameters
-  header: POT Parameters
-  preset:
+id: ""
+model:
+  backbone:
     affects_outcome_of: NONE
-    default_value: Performance
-    description: Quantization preset that defines quantization scheme
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
+    default_value: resnet18
+    description: Pre-trained backbone used for feature extraction
     editable: true
-    enum_name: POTQuantizationPreset
-    header: Preset
+    enum_name: ModelBackbone
+    header: Model Backbone
     options:
-      MIXED: Mixed
-      PERFORMANCE: Performance
+      RESNET18: resnet18
+      WIDE_RESNET_50: wide_resnet50_2
     type: SELECTABLE
     ui_rules:
       action: DISABLE_EDITING
       operator: AND
       rules: []
       type: UI_RULES
+    value: resnet18
     visible_in_ui: true
     warning: null
-  stat_subset_size:
+  description: Model Parameters
+  header: Model Parameters
+  type: PARAMETER_GROUP
+  visible_in_ui: true
+nncf_optimization:
+  description: Optimization by NNCF
+  enable_pruning:
     affects_outcome_of: NONE
-    default_value: 300
-    description: Number of data samples used for post-training optimization
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
+    default_value: false
+    description: Enable filter pruning algorithm
     editable: true
-    header: Number of data samples
-    max_value: 9223372036854775807
-    min_value: 1
-    type: INTEGER
+    header: Enable filter pruning algorithm
+    type: BOOLEAN
     ui_rules:
       action: DISABLE_EDITING
       operator: AND
       rules: []
       type: UI_RULES
+    value: false
     visible_in_ui: true
     warning: null
-  type: PARAMETER_GROUP
-  visible_in_ui: true
-nncf_optimization:
-  description: Optimization by NNCF
-  header: Optimization by NNCF
   enable_quantization:
-    affects_outcome_of: TRAINING
+    affects_outcome_of: NONE
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
     default_value: true
     description: Enable quantization algorithm
     editable: true
@@ -102,12 +114,15 @@ nncf_optimization:
     value: true
     visible_in_ui: true
     warning: null
-  enable_pruning:
+  header: Optimization by NNCF
+  pruning_supported:
     affects_outcome_of: TRAINING
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
     default_value: false
-    description: Enable filter pruning algorithm
+    description: Whether filter pruning is supported
     editable: true
-    header: Enable filter pruning algorithm
+    header: Whether filter pruning is supported
     type: BOOLEAN
     ui_rules:
       action: DISABLE_EDITING
@@ -117,20 +132,50 @@ nncf_optimization:
     value: false
     visible_in_ui: true
     warning: null
-  pruning_supported:
-    affects_outcome_of: TRAINING
-    default_value: false
-    description: Whether filter pruning is supported
-    editable: false
-    header: Whether filter pruning is supported
-    type: BOOLEAN
+  type: PARAMETER_GROUP
+  visible_in_ui: true
+pot_parameters:
+  description: POT Parameters
+  header: POT Parameters
+  preset:
+    affects_outcome_of: NONE
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
+    default_value: Performance
+    description: Quantization preset that defines quantization scheme
+    editable: true
+    enum_name: POTQuantizationPreset
+    header: Preset
+    options:
+      MIXED: Mixed
+      PERFORMANCE: Performance
+    type: SELECTABLE
     ui_rules:
       action: DISABLE_EDITING
       operator: AND
       rules: []
       type: UI_RULES
-    value: false
-    visible_in_ui: false
+    value: Performance
+    visible_in_ui: true
+    warning: null
+  stat_subset_size:
+    affects_outcome_of: NONE
+    auto_hpo_state: not_possible
+    auto_hpo_value: null
+    default_value: 300
+    description: Number of data samples used for post-training optimization
+    editable: true
+    header: Number of data samples
+    max_value: 9223372036854775807
+    min_value: 1
+    type: INTEGER
+    ui_rules:
+      action: DISABLE_EDITING
+      operator: AND
+      rules: []
+      type: UI_RULES
+    value: 300
+    visible_in_ui: true
     warning: null
   type: PARAMETER_GROUP
   visible_in_ui: false

external/anomaly/anomaly_classification/configs/stfpm/configuration.py

@@ -18,10 +18,11 @@
 
 from attr import attrs
 from ote_anomalib.configs.configuration import BaseAnomalyConfig
-from ote_anomalib.configs.configuration_enums import EarlyStoppingMetrics
+from ote_anomalib.configs.configuration_enums import EarlyStoppingMetrics, ModelBackbone
 from ote_sdk.configuration.elements import (
     ParameterGroup,
     add_parameter_group,
+    configurable_float,
     configurable_integer,
     selectable,
     string_attribute,
@@ -47,6 +48,36 @@ class ModelParameters(ParameterGroup):
         header = string_attribute("Model Parameters")
         description = header
 
+        backbone = selectable(
+            default_value=ModelBackbone.RESNET18,
+            header="Model Backbone",
+            description="Pre-trained backbone used for teacher and student network",
+        )
+
+        lr = configurable_float(
+            default_value=0.4,
+            header="Learning Rate",
+            min_value=1e-3,
+            max_value=1,
+            description="Learning rate used for optimizing the Student network.",
+        )
+
+        momentum = configurable_float(
+            default_value=0.9,
+            header="Momentum",
+            min_value=0.1,
+            max_value=1.0,
+            description="Momentum used for SGD optimizer",
+        )
+
+        weight_decay = configurable_float(
+            default_value=0.0001,
+            header="Weight Decay",
+            min_value=1e-5,
+            max_value=1,
+            description="Decay for SGD optimizer",
+        )
+
         @attrs
         class EarlyStoppingParameters(ParameterGroup):
             """