configuration.yaml

description: Configuration for an instance segmentation task
header: Configuration for an instance segmentation task
learning_parameters:
  batch_size:
    affects_outcome_of: TRAINING
    default_value: 5
    description:
      The number of training samples seen in each iteration of training.
      Increasing this value improves training time and may make the training more
      stable. A larger batch size has higher memory requirements.
    editable: true
    header: Batch size
    max_value: 512
    min_value: 1
    type: INTEGER
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: 5
    visible_in_ui: true
    warning:
      Increasing this value may cause the system to use more memory than available,
      potentially causing out of memory errors, please update with caution.
    auto_hpo_state: NOT_POSSIBLE
  description: Learning Parameters
  header: Learning Parameters
  learning_rate:
    affects_outcome_of: TRAINING
    default_value: 0.01
    description:
      Increasing this value will speed up training convergence but might
      make it unstable.
    editable: true
    header: Learning rate
    max_value: 0.1
    min_value: 1.0e-07
    type: FLOAT
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: 0.01
    visible_in_ui: true
    warning: null
    auto_hpo_state: NOT_POSSIBLE
  learning_rate_warmup_iters:
    affects_outcome_of: TRAINING
    default_value: 100
    description: ""
    editable: true
    header: Number of iterations for learning rate warmup
    max_value: 10000
    min_value: 0
    type: INTEGER
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: 100
    visible_in_ui: true
    warning: null
  num_checkpoints:
    affects_outcome_of: NONE
    default_value: 5
    description: ""
    editable: true
    header: Number of checkpoints that is done during the single training round
    max_value: 100
    min_value: 1
    type: INTEGER
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: 5
    visible_in_ui: true
    warning: null
  num_iters:
    affects_outcome_of: TRAINING
    default_value: 1
    description:
      Increasing this value causes the results to be more robust but training
      time will be longer.
    editable: true
    header: Number of training iterations
    max_value: 100000
    min_value: 1
    type: INTEGER
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: 1
    visible_in_ui: true
    warning: null
  num_workers:
    affects_outcome_of: NONE
    default_value: 5
    description:
      Increasing this value might improve training speed however it might
      cause out of memory errors. If the number of workers is set to zero, data loading
      will happen in the main training thread.
    editable: true
    header: Number of cpu threads to use during batch generation
    max_value: 8
    min_value: 0
    type: INTEGER
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: 0
    visible_in_ui: true
    warning: null
  type: PARAMETER_GROUP
  visible_in_ui: true
postprocessing:
  confidence_threshold:
    affects_outcome_of: INFERENCE
    default_value: 0.35
    description:
      This threshold only takes effect if the threshold is not set based
      on the result.
    editable: true
    header: Confidence threshold
    max_value: 1
    min_value: 0
    type: FLOAT
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    # value: 0.35
    value: 0.01
    visible_in_ui: true
    warning: null
  description: Postprocessing
  header: Postprocessing
  result_based_confidence_threshold:
    affects_outcome_of: INFERENCE
    default_value: true
    description: Confidence threshold is derived from the results
    editable: true
    header: Result based confidence threshold
    type: BOOLEAN
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: true
    visible_in_ui: true
    warning: null
  type: PARAMETER_GROUP
  visible_in_ui: true
algo_backend:
  description: parameters for algo backend
  header: Algo backend parameters
  train_type:
    affects_outcome_of: NONE
    default_value: Incremental
    description: Quantization preset that defines quantization scheme
    editable: false
    enum_name: TrainType
    header: train type
    options:
      Incremental: "Incremental"
    type: SELECTABLE
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: Incremental
    visible_in_ui: True
    warning: null
  type: PARAMETER_GROUP
  visible_in_ui: true
type: CONFIGURABLE_PARAMETERS
visible_in_ui: true
pot_parameters:
  description: POT Parameters
  header: POT Parameters
  preset:
    affects_outcome_of: NONE
    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: Performance
    visible_in_ui: True
    warning: null
  stat_subset_size:
    affects_outcome_of: NONE
    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: true
nncf_optimization:
  description: Optimization by NNCF
  header: Optimization by NNCF
  enable_quantization:
    affects_outcome_of: INFERENCE
    default_value: True
    description: Enable quantization algorithm
    editable: false
    header: Enable quantization algorithm
    type: BOOLEAN
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: true
    visible_in_ui: false
    warning: null
  enable_pruning:
    affects_outcome_of: INFERENCE
    default_value: false
    description: Enable filter pruning algorithm
    editable: true
    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
  maximal_accuracy_degradation:
    affects_outcome_of: NONE
    default_value: 1.0
    description: The maximal allowed accuracy metric drop in absolute values
    editable: True
    header: Maximum accuracy degradation
    max_value: 100.0
    min_value: 0.0
    type: FLOAT
    ui_rules:
      action: DISABLE_EDITING
      operator: AND
      rules: []
      type: UI_RULES
    value: 1.0
    visible_in_ui: True
    warning: null
  type: PARAMETER_GROUP
  visible_in_ui: True