mask_rcnn-backbone_resnet50-b9ch.yaml

dataset:
    name: &dataset_name 'coco2017'
    root: &root_dir !join ['./resource/dataset/', *dataset_name]
    num_workers: 4
    aspect_ratio_group_factor: 3
    splits:
        train:
            images: !join [*root_dir, '/train2017']
            annotations: !join [*root_dir, '/annotations/instances_train2017.json']
            remove_non_annotated_imgs: True
            jpeg_quality:
        val:
            images: !join [*root_dir, '/val2017']
            annotations: !join [*root_dir, '/annotations/instances_val2017.json']
            remove_non_annotated_imgs: False
            jpeg_quality:
        test:
            images: !join [*root_dir, '/val2017']
            annotations: !join [*root_dir, '/annotations/instances_val2017.json']
            remove_non_annotated_imgs: False
            jpeg_quality:

teacher_model:
    name: &teacher_model_name 'mask_rcnn'
    backbone:
        name: &teacher_backbone_name 'resnet50'
        params:
            pretrained: True
            freeze_layers: True
    params:
        num_classes: 91
        pretrained: True
    experiment: &teacher_experiment !join [*dataset_name, '-', *teacher_model_name, '-backbone_', *teacher_backbone_name]
    ckpt: !join ['./resource/ckpt/org/', *teacher_experiment, '.pt']

student_model:
    name: &student_model_name 'mask_rcnn'
    backbone:
        name: &student_backbone_name 'custom_resnet50'
        params:
            pretrained: True
            freeze_layers: False
            layer1:
                name: 'Bottleneck4LargeResNet'
                bottleneck_channel: &bch 9
    bottleneck_transformer:
        order: ['quantizer', 'dequantizer']
        components:
            quantizer:
                params:
                    num_bits: 8
            dequantizer:
                params:
                    num_bits: 8
    params:
        num_classes: 91
        pretrained: True
    distill_backbone_only: True
    frozen_modules: ['backbone.body.layer2', 'backbone.body.layer3', 'backbone.body.layer4', 'backbone.fpn', 'rpn', 'roi_heads']
    experiment: &student_experiment !join [*dataset_name, '-', *student_model_name, '-backbone_', *student_backbone_name, '_from_', *teacher_model_name, '-backbone_', *teacher_backbone_name, '-b', *bch, 'ch']
    ckpt: !join ['./resource/ckpt/ghnd/', *student_experiment, '.pt']

train:
    num_epochs: 20
    batch_size: 4
    log_freq: 1000
    optimizer:
        type: 'Adam'
        params:
            lr: 0.001
    criterion:
        type: 'general'
        params:
            org_loss_factor: 0.0
        terms:
            layer1:
                ts_modules: ['backbone.body.layer1', 'backbone.body.layer1']
                criterion:
                    type: 'MSELoss'
                    params:
                        reduction: 'sum'
                factor: 1.0
            layer2:
                ts_modules: ['backbone.body.layer2', 'backbone.body.layer2']
                criterion:
                    type: 'MSELoss'
                    params:
                        reduction: 'sum'
                factor: 1.0
            layer3:
                ts_modules: ['backbone.body.layer3', 'backbone.body.layer3']
                criterion:
                    type: 'MSELoss'
                    params:
                        reduction: 'sum'
                factor: 1.0
            layer4:
                ts_modules: ['backbone.body.layer4', 'backbone.body.layer4']
                criterion:
                    type: 'MSELoss'
                    params:
                        reduction: 'sum'
                factor: 1.0
    scheduler:
        type: 'MultiStepLR'
        params:
            milestones: [5, 15]
            gamma: 0.1

test:
    batch_size: 1