Index

A

AbstractCollateFunction (class in super_gradients.training.datasets.datasets_utils) AbstractYoLoV5Backbone (class in super_gradients.training.models.yolov5) Accuracy (class in super_gradients.training.metrics.classification_metrics) accuracy() (in module super_gradients.training.metrics.classification_metrics) adapt_state_dict_to_fit_model_layer_names() (in module super_gradients.training.utils.checkpoint_utils) adaptive_load_state_dict() (in module super_gradients.training.utils.checkpoint_utils) add_log_to_file() (in module super_gradients.training.utils.sg_model_utils) add_yolo_layer_to_modules_list() (super_gradients.training.models.yolov3.YoloV3 static method) ADNNModelRepositoryDataInterfaces (class in super_gradients.common.data_interface.adnn_model_repository_data_interface) analyze() (super_gradients.training.datasets.datasets_utils.DatasetStatisticsTensorboardLogger method) anchor_grid (super_gradients.training.utils.detection_utils.Anchors property) AnchorGenerator (class in super_gradients.training.utils.detection_utils) Anchors (class in super_gradients.training.utils.detection_utils) anchors (super_gradients.training.utils.detection_utils.Anchors property) AnyBackBoneDDRNet23 (class in super_gradients.training.models.ddrnet)

AnyNetX (class in super_gradients.training.models.regnet) ap_per_class() (in module super_gradients.training.metrics.detection_metrics) async_prefech() (super_gradients.training.legacy.utils.PrefetchDataLoader method) AtomicInteger (class in super_gradients.training.datasets.datasets_utils) AttentionRefinementModule (class in super_gradients.training.models.shelfnet) augment_hsv() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method) AugmentOp (class in super_gradients.training.datasets.auto_augment) auto_contrast() (in module super_gradients.training.datasets.auto_augment) AutoLoggerConfig (class in super_gradients.common.auto_logging.auto_logger) autopad() (in module super_gradients.training.models.csp_darknet53) aux_logits1 (super_gradients.training.models.googlenet.GoogLeNetOutputs property) aux_logits2 (super_gradients.training.models.googlenet.GoogLeNetOutputs property) average (super_gradients.training.utils.utils.AverageMeter property) AverageMeter (class in super_gradients.training.utils.utils) AWSConnector (class in super_gradients.common.aws_connection.aws_connector) AWSSecretsManagerConnector (class in super_gradients.common.aws_connection.aws_secrets_manager_connector)

B

b0() (in module super_gradients.training.models.efficientnet) b1() (in module super_gradients.training.models.efficientnet) b2() (in module super_gradients.training.models.efficientnet) b3() (in module super_gradients.training.models.efficientnet) b4() (in module super_gradients.training.models.efficientnet) b5() (in module super_gradients.training.models.efficientnet) b6() (in module super_gradients.training.models.efficientnet) b7() (in module super_gradients.training.models.efficientnet) b8() (in module super_gradients.training.models.efficientnet) backward_step() (super_gradients.training.sg_model.sg_model.SgModel method) base_detection_collate_fn() (in module super_gradients.training.utils.detection_utils) base_forward() (super_gradients.training.models.laddernet.BaseNet method) BaseNet (class in super_gradients.training.models.laddernet) BaseSgVisionDataset (class in super_gradients.training.datasets.sg_dataset) BasicBlock (class in super_gradients.training.models.laddernet) (class in super_gradients.training.models.resnet) (class in super_gradients.training.models.senet) BasicConv2d (class in super_gradients.training.models.googlenet) BasicDDRBackBone (class in super_gradients.training.models.ddrnet) batch_intersection_union() (in module super_gradients.training.metrics.segmentation_metrics) batch_pix_accuracy() (in module super_gradients.training.metrics.segmentation_metrics)

bbox_view() (super_gradients.training.models.ssd.SSD method) bias (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) Block (class in super_gradients.training.models.mobilenet) BlockArgs (class in super_gradients.training.models.efficientnet) BlockDecoder (class in super_gradients.training.models.efficientnet) BOLD (super_gradients.common.environment.env_helpers.TerminalColours attribute) Bottleneck (class in super_gradients.training.models.csp_darknet53) (class in super_gradients.training.models.dpn) (class in super_gradients.training.models.laddernet) (class in super_gradients.training.models.resnet) (class in super_gradients.training.models.shufflenet) BottleneckCSP (class in super_gradients.training.models.csp_darknet53) box_candidates() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method) box_iou() (in module super_gradients.training.utils.detection_utils) brightness() (in module super_gradients.training.datasets.auto_augment) build_data_loaders() (super_gradients.training.datasets.dataset_interfaces.dataset_interface.DatasetInterface method) build_detection_targets() (in module super_gradients.training.utils.detection_utils) build_efficientnet() (in module super_gradients.training.models.efficientnet) build_model() (super_gradients.training.sg_model.sg_model.SgModel method) build_optimizer() (in module super_gradients.training.utils.optimizer_utils) build_targets() (super_gradients.training.losses.yolo_v5_loss.YoLoV5DetectionLoss method)

C

C3 (class in super_gradients.training.models.csp_darknet53) calc_batch_prediction_accuracy() (in module super_gradients.training.utils.detection_utils) calc_batch_prediction_detection_metrics_per_class() (in module super_gradients.training.metrics.metric_utils) calc_bbox_iou_matrix() (in module super_gradients.training.utils.detection_utils) calculate_bbox_iou_elementwise() (in module super_gradients.training.utils.detection_utils) calculate_bbox_iou_matrix() (in module super_gradients.training.utils.detection_utils) calculate_output_image_size() (in module super_gradients.training.models.efficientnet) calculate_wh_iou() (in module super_gradients.training.utils.detection_utils) CallbackHandler (class in super_gradients.training.utils.callbacks) CellA (class in super_gradients.training.models.pnasnet) CellB (class in super_gradients.training.models.pnasnet) cfg (super_gradients.training.models.mobilenet.MobileNet attribute) change_bbox_bounds_for_image_size() (in module super_gradients.training.utils.detection_utils) check_anchor_order() (in module super_gradients.training.utils.detection_utils) check_img_size_divisibilty() (in module super_gradients.training.utils.detection_utils) check_key_exists() (super_gradients.common.data_connection.s3_connector.S3Connector method) check_models_have_same_weights() (in module super_gradients.training.utils.utils) check_valid_arguments() (super_gradients.training.utils.segmentation_utils.CropImageAndMask method) (super_gradients.training.utils.segmentation_utils.PadShortToCropSize method) (super_gradients.training.utils.segmentation_utils.RandomRescale method) (super_gradients.training.utils.segmentation_utils.RandomRotate method) (super_gradients.training.utils.segmentation_utils.Rescale method) Cifar100DatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) Cifar10DatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) CifarResNet (class in super_gradients.training.models.resnet) CityscapesDataset (class in super_gradients.training.datasets.segmentation_datasets.cityscape_segmentation) CityscapesDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) CLASSIFICATION (super_gradients.common.data_types.enum.deep_learning_task.DeepLearningTask attribute) (super_gradients.training.datasets.all_datasets.SgLibraryDatasets attribute) ClassificationDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) ClassificationTestDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) cleanup() (super_gradients.training.utils.weight_averaging_utils.ModelWeightAveraging method) CoCo2014DetectionDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) CoCoDataSetInterfaceBase (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) COCODetectionDataSet (class in super_gradients.training.datasets.detection_datasets.coco_detection) CoCoDetectionDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) CoCoSegmentationDataSet (class in super_gradients.training.datasets.segmentation_datasets.coco_segmentation) CoCoSegmentationDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) CollateMixup (class in super_gradients.training.datasets.mixup) color() (in module super_gradients.training.datasets.auto_augment) ColouredTextFormatter (class in super_gradients.common.environment.env_helpers) ComposedCollateFunction (class in super_gradients.training.datasets.datasets_utils) compute() (super_gradients.training.metrics.classification_metrics.Top5 method) (super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric method) (super_gradients.training.metrics.detection_metrics.DetectionMetrics method) (super_gradients.training.metrics.segmentation_metrics.PixelAccuracy method) compute_ap() (in module super_gradients.training.metrics.detection_metrics) compute_loss() (super_gradients.training.losses.yolo_v5_loss.YoLoV5DetectionLoss method) compute_model_runtime() (super_gradients.training.sg_model.sg_model.SgModel method) compute_precise_bn_stats() (in module super_gradients.training.utils.distributed_training_utils) Concat (class in super_gradients.training.models.yolov5)

concatenate_layer_output() (super_gradients.training.models.yolov3.TinyYoloV3 static method) (super_gradients.training.models.yolov3.YoloV3 static method) configure_elasticsearch_handler() (super_gradients.common.auto_logging.auto_logger.AutoLoggerConfig static method) confmat (super_gradients.training.metrics.segmentation_metrics.IoU attribute) connect_dataset_interface() (super_gradients.training.sg_model.sg_model.SgModel method) contrast() (in module super_gradients.training.datasets.auto_augment) Conv (class in super_gradients.training.models.csp_darknet53) conv1x1() (in module super_gradients.training.models.resnext) Conv2dDynamicSamePadding (class in super_gradients.training.models.efficientnet) Conv2dStaticSamePadding (class in super_gradients.training.models.efficientnet) conv3x3() (in module super_gradients.training.models.laddernet) (in module super_gradients.training.models.resnext) conv_1x1_bn() (in module super_gradients.training.models.mobilenetv2) (in module super_gradients.training.models.mobilenetv3) conv_3x3_bn() (in module super_gradients.training.models.mobilenetv3) conv_bn() (in module super_gradients.training.models.mobilenetv2) (in module super_gradients.training.models.repvgg) ConvBN() (in module super_gradients.training.models.ddrnet) ConvBNReLU (class in super_gradients.training.models.shelfnet) convert_content_length_to_mb() (super_gradients.common.data_connection.s3_connector.S3Connector static method) convert_to_tensor() (in module super_gradients.training.utils.utils) convert_xywh_bbox_to_xyxy() (in module super_gradients.training.utils.detection_utils) convert_xyxy_bbox_to_xywh() (in module super_gradients.training.utils.detection_utils) copy_attr() (in module super_gradients.training.utils.ema) copy_key() (super_gradients.common.data_connection.s3_connector.S3Connector method) correct (super_gradients.training.metrics.classification_metrics.Accuracy attribute) CosineLRCallback (class in super_gradients.training.utils.callbacks) create_bucket() (super_gradients.common.data_connection.s3_connector.S3Connector method) create_conv_module() (in module super_gradients.training.models.darknet53) create_grids() (super_gradients.training.models.yolov3.YOLOLayer method) create_modules_list() (super_gradients.training.models.yolov3.TinyYoloV3 method) (super_gradients.training.models.yolov3.YoloV3 method) create_presigned_download_url() (super_gradients.common.data_connection.s3_connector.S3Connector method) create_presigned_upload_url() (super_gradients.common.data_connection.s3_connector.S3Connector method) CropImageAndMask (class in super_gradients.training.utils.segmentation_utils) cross_entropy() (in module super_gradients.training.losses.label_smoothing_cross_entropy_loss) CSPDarknet53 (class in super_gradients.training.models.csp_darknet53) current_environment_client (super_gradients.common.aws_connection.aws_secrets_manager_connector.AWSSecretsManagerConnector attribute) custom_mobile_net_v2() (in module super_gradients.training.models.mobilenetv2) Custom_YoLoV5 (class in super_gradients.training.models.yolov5) CustomizedDensnet() (in module super_gradients.training.models.densenet) CustomizedEfficientnet() (in module super_gradients.training.models.efficientnet) CustomizedResnet() (in module super_gradients.training.models.resnet) CustomizedResnet50() (in module super_gradients.training.models.resnet) CustomizedResnet50Cifar() (in module super_gradients.training.models.resnet) CustomizedResnetCifar() (in module super_gradients.training.models.resnet) CustomizedResNeXt() (in module super_gradients.training.models.resnext) CustomizedShuffleNetV2 (class in super_gradients.training.models.shufflenetv2) CustomRegNet (class in super_gradients.training.models.regnet) cutmix_bbox_and_lam() (in module super_gradients.training.datasets.mixup) cutout() (super_gradients.training.datasets.data_augmentation.DataAugmentation static method)

D

DAPPM (class in super_gradients.training.models.ddrnet) DAPPMBranch (class in super_gradients.training.models.ddrnet) Darknet53 (class in super_gradients.training.models.darknet53) Darknet53Base (class in super_gradients.training.models.darknet53) DarkResidualBlock (class in super_gradients.training.models.darknet53) DATA_PARALLEL (super_gradients.training.sg_model.sg_model.MultiGPUMode attribute) DataAugmentation (class in super_gradients.training.datasets.data_augmentation) DatasetDataInterface (class in super_gradients.common.data_interface.dataset_data_interface) DataSetDoesNotExistException DatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) DatasetStatisticsTensorboardLogger (class in super_gradients.training.datasets.datasets_utils) dboxes256_coco() (super_gradients.training.utils.ssd_utils.DefaultBoxes static method) dboxes300_coco() (super_gradients.training.utils.ssd_utils.DefaultBoxes static method) dboxes300_coco_from19() (super_gradients.training.utils.ssd_utils.DefaultBoxes static method) DDRBackBoneBase (class in super_gradients.training.models.ddrnet) DDRNet (class in super_gradients.training.models.ddrnet) DDRNet23 (class in super_gradients.training.models.ddrnet) DDRNet23Slim (class in super_gradients.training.models.ddrnet) DDRNetCustom (class in super_gradients.training.models.ddrnet) DDRNetLoss (class in super_gradients.training.losses.ddrnet_loss) deci_class_logger() (in module super_gradients.common.decorators.deci_logger) DECI_ENVIRONMENTS (super_gradients.common.aws_connection.aws_secrets_manager_connector.AWSSecretsManagerConnector attribute) deci_func_logger() (in module super_gradients.common.decorators.deci_logger) DeciLabUploadCallback (class in super_gradients.training.utils.callbacks) decode() (super_gradients.training.models.efficientnet.BlockDecoder static method) decode_segmentation_mask() (super_gradients.training.datasets.segmentation_datasets.pascal_voc_segmentation.PascalVOC2012SegmentationDataSet method) Decoder (class in super_gradients.training.models.laddernet) DecoderBase (class in super_gradients.training.models.shelfnet) DecoderHW (class in super_gradients.training.models.shelfnet) DecoderLW (class in super_gradients.training.models.shelfnet) DeepLearningTask (class in super_gradients.common.data_types.enum.deep_learning_task)

DEFAULT_SUMMARY_PARAMS (super_gradients.training.datasets.datasets_utils.DatasetStatisticsTensorboardLogger attribute) DefaultBoxes (class in super_gradients.training.utils.ssd_utils) delete_bucket() (super_gradients.common.data_connection.s3_connector.S3Connector method) delete_key() (super_gradients.common.data_connection.s3_connector.S3Connector method) DenseNet (class in super_gradients.training.models.densenet) densenet121() (in module super_gradients.training.models.densenet) densenet161() (in module super_gradients.training.models.densenet) densenet169() (in module super_gradients.training.models.densenet) densenet201() (in module super_gradients.training.models.densenet) DEPTH_ESTIMATION (super_gradients.common.data_types.enum.deep_learning_task.DeepLearningTask attribute) Detect (class in super_gradients.training.models.yolov5) detection_layers_num (super_gradients.training.utils.detection_utils.Anchors property) DetectionDataSet (class in super_gradients.training.datasets.detection_datasets.detection_dataset) DetectionMetrics (class in super_gradients.training.metrics.detection_metrics) DetectionPostPredictionCallback (class in super_gradients.training.utils.detection_utils) DetectionTestDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) DetectionVisualization (class in super_gradients.training.utils.detection_utils) dilation (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) DirectoryDataSet (class in super_gradients.training.datasets.sg_dataset) distributed_all_reduce_tensor_average() (in module super_gradients.training.utils.distributed_training_utils) DISTRIBUTED_DATA_PARALLEL (super_gradients.training.sg_model.sg_model.MultiGPUMode attribute) download_file_by_path() (super_gradients.common.data_connection.s3_connector.S3Connector method) download_from_cloud() (super_gradients.training.datasets.dataset_interfaces.dataset_interface.DatasetInterface method) download_key() (super_gradients.common.data_connection.s3_connector.S3Connector method) download_keys_by_prefix() (super_gradients.common.data_connection.s3_connector.S3Connector method) DPN (class in super_gradients.training.models.dpn) DPN26() (in module super_gradients.training.models.dpn) DPN92() (in module super_gradients.training.models.dpn) drop_connect() (in module super_gradients.training.models.efficientnet) DropPath (class in super_gradients.training.utils.regularization_utils)

E

EarlyStop (class in super_gradients.training.utils.early_stopping) EfficientNet (class in super_gradients.training.models.efficientnet) empty_folder_content_by_path_prefix() (super_gradients.common.data_connection.s3_connector.S3Connector method) EmptyCoCoClassesSelectionException encode() (super_gradients.training.models.efficientnet.BlockDecoder static method) ENDC (super_gradients.common.environment.env_helpers.TerminalColours attribute) equalize() (in module super_gradients.training.datasets.auto_augment) evaluate() (super_gradients.training.sg_model.sg_model.SgModel method) EvaluationType (class in super_gradients.training.sg_model.sg_model) exif_size() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method)

expand_ratio (super_gradients.training.models.efficientnet.BlockArgs property) expansion (super_gradients.training.models.laddernet.BasicBlock attribute) (super_gradients.training.models.laddernet.Bottleneck attribute) (super_gradients.training.models.laddernet.LadderBottleneck attribute) (super_gradients.training.models.preact_resnet.PreActBlock attribute) (super_gradients.training.models.preact_resnet.PreActBottleneck attribute) (super_gradients.training.models.resnext.GroupedConvBlock attribute) explicit_params_validation() (in module super_gradients.common.decorators.explicit_params_validator) ExportableHardswish (class in super_gradients.training.utils.export_utils) ExternalDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) extract_features() (super_gradients.training.models.efficientnet.EfficientNet method)

F

FAIL (super_gradients.common.environment.env_helpers.TerminalColours attribute) FCNHead (class in super_gradients.training.models.laddernet) (class in super_gradients.training.models.shelfnet) Final_LadderBlock (class in super_gradients.training.models.laddernet) flatten_metrics_dict() (in module super_gradients.training.metrics.metric_utils) FocalLoss (class in super_gradients.training.losses.focal_loss) Focus (class in super_gradients.training.models.csp_darknet53) format_time() (in module super_gradients.training.legacy.utils) forward() (super_gradients.training.datasets.datasets_utils.RandomResizedCropAndInterpolation method) (super_gradients.training.losses.ddrnet_loss.DDRNetLoss method) (super_gradients.training.losses.focal_loss.FocalLoss method) (super_gradients.training.losses.label_smoothing_cross_entropy_loss.LabelSmoothingCrossEntropyLoss method) (super_gradients.training.losses.ohem_ce_loss.OhemCELoss method) (super_gradients.training.losses.r_squared_loss.RSquaredLoss method) (super_gradients.training.losses.shelfnet_ohem_loss.ShelfNetOHEMLoss method) (super_gradients.training.losses.shelfnet_semantic_encoding_loss.ShelfNetSemanticEncodingLoss method) (super_gradients.training.losses.ssd_loss.SSDLoss method) (super_gradients.training.losses.yolo_v3_loss.YoLoV3DetectionLoss method) (super_gradients.training.losses.yolo_v5_loss.YoLoV5DetectionLoss method) (super_gradients.training.models.csp_darknet53.Bottleneck method) (super_gradients.training.models.csp_darknet53.BottleneckCSP method) (super_gradients.training.models.csp_darknet53.C3 method) (super_gradients.training.models.csp_darknet53.Conv method) (super_gradients.training.models.csp_darknet53.CSPDarknet53 method) (super_gradients.training.models.csp_darknet53.Focus method) (super_gradients.training.models.csp_darknet53.SPP method) (super_gradients.training.models.csp_darknet53.SPPF method) (super_gradients.training.models.csp_darknet53.ViewModule method) (super_gradients.training.models.darknet53.Darknet53 method) (super_gradients.training.models.darknet53.Darknet53Base method) (super_gradients.training.models.darknet53.DarkResidualBlock method) (super_gradients.training.models.darknet53.ViewModule method) (super_gradients.training.models.ddrnet.DAPPM method) (super_gradients.training.models.ddrnet.DAPPMBranch method) (super_gradients.training.models.ddrnet.DDRNet method) (super_gradients.training.models.ddrnet.SegmentHead method) (super_gradients.training.models.ddrnet.UpscaleOnline method) (super_gradients.training.models.densenet.DenseNet method) (super_gradients.training.models.dpn.Bottleneck method) (super_gradients.training.models.dpn.DPN method) (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding method) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding method) (super_gradients.training.models.efficientnet.EfficientNet method) (super_gradients.training.models.efficientnet.Identity method) (super_gradients.training.models.efficientnet.MBConvBlock method) (super_gradients.training.models.googlenet.BasicConv2d method) (super_gradients.training.models.googlenet.GoogLeNet method) (super_gradients.training.models.googlenet.Inception method) (super_gradients.training.models.googlenet.InceptionAux method) (super_gradients.training.models.laddernet.BasicBlock method) (super_gradients.training.models.laddernet.Bottleneck method) (super_gradients.training.models.laddernet.Decoder method) (super_gradients.training.models.laddernet.FCNHead method) (super_gradients.training.models.laddernet.Final_LadderBlock method) (super_gradients.training.models.laddernet.Initial_LadderBlock method) (super_gradients.training.models.laddernet.LadderBlock method) (super_gradients.training.models.laddernet.LadderBottleneck method) (super_gradients.training.models.laddernet.LadderHead method) (super_gradients.training.models.laddernet.LadderNet method) (super_gradients.training.models.laddernet.LadderResNet method) (super_gradients.training.models.lenet.LeNet method) (super_gradients.training.models.mobilenet.Block method) (super_gradients.training.models.mobilenet.MobileNet method) (super_gradients.training.models.mobilenetv2.InvertedResidual method) (super_gradients.training.models.mobilenetv2.MobileNetV2 method) (super_gradients.training.models.mobilenetv3.h_sigmoid method) (super_gradients.training.models.mobilenetv3.h_swish method) (super_gradients.training.models.mobilenetv3.InvertedResidual method) (super_gradients.training.models.mobilenetv3.MobileNetV3 method) (super_gradients.training.models.mobilenetv3.SELayer method) (super_gradients.training.models.pnasnet.CellA method) (super_gradients.training.models.pnasnet.CellB method) (super_gradients.training.models.pnasnet.PNASNet method) (super_gradients.training.models.pnasnet.SepConv method) (super_gradients.training.models.preact_resnet.PreActBlock method) (super_gradients.training.models.preact_resnet.PreActBottleneck method) (super_gradients.training.models.preact_resnet.PreActResNet method) (super_gradients.training.models.regnet.AnyNetX method) (super_gradients.training.models.regnet.Head method) (super_gradients.training.models.regnet.Stage method) (super_gradients.training.models.regnet.Stem method) (super_gradients.training.models.regnet.XBlock method) (super_gradients.training.models.repvgg.RepVGG method) (super_gradients.training.models.repvgg.RepVGGBlock method) (super_gradients.training.models.repvgg.SEBlock method) (super_gradients.training.models.resnet.BasicBlock method) (super_gradients.training.models.resnet.Bottleneck method) (super_gradients.training.models.resnet.CifarResNet method) (super_gradients.training.models.resnet.ResNet method) (super_gradients.training.models.resnext.GroupedConvBlock method) (super_gradients.training.models.resnext.ResNeXt method) (super_gradients.training.models.senet.BasicBlock method) (super_gradients.training.models.senet.PreActBlock method) (super_gradients.training.models.senet.SENet method) (super_gradients.training.models.shelfnet.AttentionRefinementModule method) (super_gradients.training.models.shelfnet.ConvBNReLU method) (super_gradients.training.models.shelfnet.DecoderBase method) (super_gradients.training.models.shelfnet.DecoderHW method) (super_gradients.training.models.shelfnet.DecoderLW method) (super_gradients.training.models.shelfnet.FCNHead method) (super_gradients.training.models.shelfnet.LadderBlockBase method) (super_gradients.training.models.shelfnet.LadderBlockHW method) (super_gradients.training.models.shelfnet.LadderBlockLW method) (super_gradients.training.models.shelfnet.NetOutput method) (super_gradients.training.models.shelfnet.ShelfBlock method) (super_gradients.training.models.shelfnet.ShelfNetBase method) (super_gradients.training.models.shelfnet.ShelfNetHW method) (super_gradients.training.models.shelfnet.ShelfNetLW method) (super_gradients.training.models.shelfnet.ShelfNetModuleBase method) (super_gradients.training.models.shelfnet.ShelfResNetBackBone method) (super_gradients.training.models.shufflenet.Bottleneck method) (super_gradients.training.models.shufflenet.ShuffleBlock method) (super_gradients.training.models.shufflenet.ShuffleNet method) (super_gradients.training.models.shufflenetv2.ShuffleNetV2Base method) (super_gradients.training.models.ssd.SSD method) (super_gradients.training.models.vgg.VGG method) (super_gradients.training.models.yolov3.SPPLayer method) (super_gradients.training.models.yolov3.Upsample method) (super_gradients.training.models.yolov3.YOLOLayer method) (super_gradients.training.models.yolov3.YoloV3 method) (super_gradients.training.models.yolov5.AbstractYoLoV5Backbone method) (super_gradients.training.models.yolov5.Concat method) (super_gradients.training.models.yolov5.Detect method) (super_gradients.training.models.yolov5.YoLoV5Base method) (super_gradients.training.models.yolov5.YoLoV5DarknetBackbone method) (super_gradients.training.models.yolov5.YoLoV5Head method) (super_gradients.training.models.yolov5.YoloV5PostPredictionCallback method) (super_gradients.training.utils.detection_utils.DetectionPostPredictionCallback method) (super_gradients.training.utils.detection_utils.YoloV3NonMaxSuppression method) (super_gradients.training.utils.export_utils.ExportableHardswish static method) (super_gradients.training.utils.module_utils.MultiOutputModule method) (super_gradients.training.utils.regularization_utils.DropPath method) (super_gradients.training.utils.ssd_utils.SSDPostPredictCallback method) (super_gradients.training.utils.utils.WrappedModel method)

FunctionLRCallback (class in super_gradients.training.utils.callbacks) fuse_block_residual_branches() (super_gradients.training.models.repvgg.RepVGGBlock method) fuse_conv_and_bn() (in module super_gradients.training.utils.detection_utils) fuse_conv_bn() (in module super_gradients.training.utils.export_utils) fuse_repvgg_blocks_residual_branches() (in module super_gradients.training.utils.module_utils) fuseforward() (super_gradients.training.models.csp_darknet53.Conv method)

G

generate_config_for_module_name() (super_gradients.common.auto_logging.auto_logger.AutoLoggerConfig static method) get_all_available_datasets() (super_gradients.training.datasets.all_datasets.SgLibraryDatasets static method) get_arch_params() (super_gradients.training.sg_model.sg_model.SgModel method) get_architecture() (super_gradients.training.sg_model.sg_model.SgModel method) get_average_model() (super_gradients.training.utils.weight_averaging_utils.ModelWeightAveraging method) get_aws_client_for_service_name() (super_gradients.common.aws_connection.aws_connector.AWSConnector static method) get_aws_resource_for_service_name() (super_gradients.common.aws_connection.aws_connector.AWSConnector static method) get_aws_session() (super_gradients.common.aws_connection.aws_connector.AWSConnector static method) get_backbone_output_number_of_channels() (super_gradients.training.models.ddrnet.DDRBackBoneBase method) get_ckpt_local_path() (in module super_gradients.training.utils.checkpoint_utils) get_color_augmentation() (in module super_gradients.training.datasets.datasets_utils) get_data_loaders() (super_gradients.training.datasets.dataset_interfaces.dataset_interface.DatasetInterface method) (super_gradients.training.datasets.dataset_interfaces.dataset_interface.ExternalDatasetInterface method) (super_gradients.training.datasets.dataset_interfaces.dataset_interface.TestDatasetInterface method) get_dataset() (super_gradients.training.datasets.all_datasets.SgLibraryDatasets static method) get_dataset_params() (super_gradients.training.datasets.dataset_interfaces.dataset_interface.DatasetInterface method) get_environ_as_type() (in module super_gradients.common.environment.env_helpers) get_exclude_attributes() (super_gradients.training.models.sg_module.SgModule method) get_filename_suffix_by_framework() (in module super_gradients.training.utils.utils) get_include_attributes() (super_gradients.training.models.sg_module.SgModule method) (super_gradients.training.models.yolov5.YoLoV5Base method) get_logger() (in module super_gradients.common.abstractions.abstract_logger) get_logging_values() (in module super_gradients.training.metrics.metric_utils) get_mean_and_std() (in module super_gradients.training.datasets.datasets_utils)

get_mean_and_std_torch() (in module super_gradients.training.datasets.datasets_utils) get_metrics_dict() (in module super_gradients.training.metrics.metric_utils) get_metrics_results_tuple() (in module super_gradients.training.metrics.metric_utils) get_metrics_titles() (in module super_gradients.training.metrics.metric_utils) get_module() (super_gradients.training.sg_model.sg_model.SgModel method) get_modules_list() (super_gradients.training.models.darknet53.Darknet53 method) get_object_by_etag() (super_gradients.common.data_connection.s3_connector.S3Connector method) get_object_metadata() (super_gradients.common.data_connection.s3_connector.S3Connector method) get_param() (in module super_gradients.training.utils.utils) get_params() (super_gradients.training.models.shelfnet.ShelfNetModuleBase method) get_same_padding_conv2d() (in module super_gradients.training.models.efficientnet) get_secret_value_for_secret_key (super_gradients.common.aws_connection.aws_secrets_manager_connector.AWSSecretsManagerConnector attribute) get_secret_values_dict_for_secret_key_properties (super_gradients.common.aws_connection.aws_secrets_manager_connector.AWSSecretsManagerConnector attribute) get_structure() (super_gradients.training.sg_model.sg_model.SgModel method) get_train_ids_color_palette() (super_gradients.training.datasets.segmentation_datasets.cityscape_segmentation.CityscapesDataset method) get_train_loop_description_dict() (in module super_gradients.training.metrics.metric_utils) get_val_sample() (super_gradients.training.datasets.dataset_interfaces.dataset_interface.DatasetInterface method) get_yolo_layers_indices() (super_gradients.training.models.yolov3.YoloV3 method) GoogLeNet (class in super_gradients.training.models.googlenet) googlenet_v1() (in module super_gradients.training.models.googlenet) GoogLeNetOutputs (class in super_gradients.training.models.googlenet) GroupedConvBlock (class in super_gradients.training.models.resnext) groups (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute)

H

h_sigmoid (class in super_gradients.training.models.mobilenetv3) h_swish (class in super_gradients.training.models.mobilenetv3)

Head (class in super_gradients.training.models.regnet) HEADER (super_gradients.common.environment.env_helpers.TerminalColours attribute) HpmStruct (class in super_gradients.training.utils.utils)

I

id_skip (super_gradients.training.models.efficientnet.BlockArgs property) Identity (class in super_gradients.training.models.efficientnet) ignore_index (super_gradients.training.losses.label_smoothing_cross_entropy_loss.LabelSmoothingCrossEntropyLoss attribute) (super_gradients.training.losses.shelfnet_semantic_encoding_loss.ShelfNetSemanticEncodingLoss attribute) IllegalDatasetParameterException IllegalLRSchedulerMetric ILogger (class in super_gradients.common.abstractions.abstract_logger) ImageNetDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) Inception (class in super_gradients.training.models.googlenet) InceptionAux (class in super_gradients.training.models.googlenet) init_log_file() (in module super_gradients.training.utils.sg_model_utils) init_params() (in module super_gradients.training.legacy.utils) init_summary_writer() (in module super_gradients.training.utils.sg_model_utils) init_trainer() (in module super_gradients.common.environment.env_helpers) init_weight() (super_gradients.training.models.shelfnet.AttentionRefinementModule method) (super_gradients.training.models.shelfnet.ConvBNReLU method) (super_gradients.training.models.shelfnet.NetOutput method) Initial_LadderBlock (class in super_gradients.training.models.laddernet)

initialize_param_groups() (super_gradients.training.models.sg_module.SgModule method) (super_gradients.training.models.shelfnet.ShelfNetHW method) (super_gradients.training.models.shelfnet.ShelfNetLW method) (super_gradients.training.models.yolov3.YoloV3 method) (super_gradients.training.models.yolov5.YoLoV5Base method) initialize_weight() (super_gradients.training.models.regnet.AnyNetX method) input_filters (super_gradients.training.models.efficientnet.BlockArgs property) intersection_and_union() (in module super_gradients.training.metrics.segmentation_metrics) invert() (in module super_gradients.training.datasets.auto_augment) InvertedResidual (class in super_gradients.training.models.mobilenetv2) (class in super_gradients.training.models.mobilenetv3) IoU (class in super_gradients.training.metrics.segmentation_metrics) IouThreshold (class in super_gradients.training.utils.detection_utils) is_better() (in module super_gradients.training.legacy.utils) is_client_error() (super_gradients.common.aws_connection.aws_connector.AWSConnector static method) is_distributed() (in module super_gradients.common.environment.env_helpers) is_range() (super_gradients.training.utils.detection_utils.IouThreshold method) ITERATIVE (super_gradients.training.utils.detection_utils.NMS_Type attribute)

K

kernel_size (super_gradients.training.models.efficientnet.BlockArgs property) (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute)

KeyNotExistInBucketError

L

l2() (in module super_gradients.training.models.efficientnet) LabelSmoothingCrossEntropyLoss (class in super_gradients.training.losses.label_smoothing_cross_entropy_loss) LadderBlock (class in super_gradients.training.models.laddernet) LadderBlockBase (class in super_gradients.training.models.shelfnet) LadderBlockHW (class in super_gradients.training.models.shelfnet) LadderBlockLW (class in super_gradients.training.models.shelfnet) LadderBottleneck (class in super_gradients.training.models.laddernet) LadderHead (class in super_gradients.training.models.laddernet) LadderNet (class in super_gradients.training.models.laddernet) LadderNet101 (class in super_gradients.training.models.laddernet) LadderNet50 (class in super_gradients.training.models.laddernet) LadderNet503433 (class in super_gradients.training.models.laddernet) LadderNetBackBone101 (class in super_gradients.training.models.laddernet) LadderNetBackBone50 (class in super_gradients.training.models.laddernet) LadderNetBackBone503433 (class in super_gradients.training.models.laddernet) LadderResNet (class in super_gradients.training.models.laddernet) launch_tensorboard_process() (in module super_gradients.training.utils.sg_model_utils) LeNet (class in super_gradients.training.models.lenet) letterbox() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method) LibraryDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) Lighting (class in super_gradients.training.datasets.data_augmentation)

list_bucket_objects() (super_gradients.common.data_connection.s3_connector.S3Connector method) ListDataset (class in super_gradients.training.datasets.sg_dataset) load_all_remote_log_files() (super_gradients.common.data_interface.adnn_model_repository_data_interface.ADNNModelRepositoryDataInterfaces method) load_checkpoint_to_model() (in module super_gradients.training.utils.checkpoint_utils) load_func() (in module super_gradients.training.utils.utils) load_mosaic() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet method) load_pretrained_weights() (in module super_gradients.training.utils.checkpoint_utils) load_remote_checkpoints_file() (super_gradients.common.data_interface.adnn_model_repository_data_interface.ADNNModelRepositoryDataInterfaces method) load_remote_dataset_file() (super_gradients.common.data_interface.dataset_data_interface.DatasetDataInterface method) load_remote_logging_files() (super_gradients.common.data_interface.adnn_model_repository_data_interface.ADNNModelRepositoryDataInterfaces method) load_state_dict() (super_gradients.training.models.efficientnet.EfficientNet method) (super_gradients.training.models.googlenet.GoogLeNet method) (super_gradients.training.models.resnet.ResNet method) (super_gradients.training.models.shufflenetv2.ShuffleNetV2Base method) (super_gradients.training.models.yolov5.YoLoV5Base method) log_ (super_gradients.training.models.googlenet.GoogLeNetOutputs property) log_uncaught_exceptions() (in module super_gradients.training.utils.sg_model_utils) logger (super_gradients.training.datasets.datasets_utils.DatasetStatisticsTensorboardLogger attribute) (super_gradients.training.utils.detection_utils.AnchorGenerator attribute) LRCallbackBase (class in super_gradients.training.utils.callbacks) LRSchedulerCallback (class in super_gradients.training.utils.callbacks)

M

make_divisible() (in module super_gradients.training.models.mobilenetv2) (in module super_gradients.training.utils.detection_utils) makedirs_if_not_exists() (in module super_gradients.training.legacy.utils) MAP_05 (super_gradients.training.utils.detection_utils.IouThreshold attribute) MAP_05_TO_095 (super_gradients.training.utils.detection_utils.IouThreshold attribute) match_dboxes() (super_gradients.training.losses.ssd_loss.SSDLoss method) MATRIX (super_gradients.training.utils.detection_utils.NMS_Type attribute) matrix_non_max_suppression() (in module super_gradients.training.utils.detection_utils) MBConvBlock (class in super_gradients.training.models.efficientnet) MetricsUpdateCallback (class in super_gradients.training.utils.callbacks) MissingMonitorKeyException MissingPretrainedWeightsException mixup_target() (in module super_gradients.training.datasets.mixup) mobile_net_v2() (in module super_gradients.training.models.mobilenetv2) mobile_net_v2_135() (in module super_gradients.training.models.mobilenetv2) MobileNet (class in super_gradients.training.models.mobilenet) MobileNetV2 (class in super_gradients.training.models.mobilenetv2) MobileNetV3 (class in super_gradients.training.models.mobilenetv3) mobilenetv3_custom() (in module super_gradients.training.models.mobilenetv3) mobilenetv3_large() (in module super_gradients.training.models.mobilenetv3) mobilenetv3_small() (in module super_gradients.training.models.mobilenetv3) mode_dict (super_gradients.training.utils.early_stopping.EarlyStop attribute) ModelCheckpointNotFoundException ModelConversionCheckCallback (class in super_gradients.training.utils.callbacks) ModelEMA (class in super_gradients.training.utils.ema) ModelWeightAveraging (class in super_gradients.training.utils.weight_averaging_utils) module super_gradients super_gradients.common super_gradients.common.abstractions super_gradients.common.abstractions.abstract_logger super_gradients.common.auto_logging super_gradients.common.auto_logging.auto_logger super_gradients.common.aws_connection super_gradients.common.aws_connection.aws_connector super_gradients.common.aws_connection.aws_secrets_manager_connector super_gradients.common.data_connection super_gradients.common.data_connection.s3_connector super_gradients.common.data_interface super_gradients.common.data_interface.adnn_model_repository_data_interface super_gradients.common.data_interface.dataset_data_interface super_gradients.common.data_types super_gradients.common.data_types.enum super_gradients.common.data_types.enum.deep_learning_task super_gradients.common.decorators super_gradients.common.decorators.deci_logger super_gradients.common.decorators.explicit_params_validator super_gradients.common.decorators.singleton super_gradients.common.environment super_gradients.common.environment.env_helpers super_gradients.common.environment.environment_config super_gradients.training super_gradients.training.datasets super_gradients.training.datasets.all_datasets super_gradients.training.datasets.auto_augment super_gradients.training.datasets.classification_datasets super_gradients.training.datasets.data_augmentation super_gradients.training.datasets.dataset_interfaces super_gradients.training.datasets.dataset_interfaces.dataset_interface super_gradients.training.datasets.datasets_conf super_gradients.training.datasets.datasets_utils super_gradients.training.datasets.detection_datasets super_gradients.training.datasets.detection_datasets.coco_detection super_gradients.training.datasets.detection_datasets.detection_dataset super_gradients.training.datasets.detection_datasets.pascal_voc_detection super_gradients.training.datasets.mixup super_gradients.training.datasets.segmentation_datasets super_gradients.training.datasets.segmentation_datasets.cityscape_segmentation super_gradients.training.datasets.segmentation_datasets.coco_segmentation super_gradients.training.datasets.segmentation_datasets.pascal_aug_segmentation super_gradients.training.datasets.segmentation_datasets.pascal_voc_segmentation super_gradients.training.datasets.segmentation_datasets.segmentation_dataset super_gradients.training.datasets.sg_dataset super_gradients.training.exceptions super_gradients.training.exceptions.dataset_exceptions super_gradients.training.exceptions.sg_model_exceptions super_gradients.training.legacy super_gradients.training.legacy.utils super_gradients.training.losses super_gradients.training.losses.all_losses super_gradients.training.losses.ddrnet_loss super_gradients.training.losses.focal_loss super_gradients.training.losses.label_smoothing_cross_entropy_loss super_gradients.training.losses.ohem_ce_loss super_gradients.training.losses.r_squared_loss super_gradients.training.losses.shelfnet_ohem_loss super_gradients.training.losses.shelfnet_semantic_encoding_loss super_gradients.training.losses.ssd_loss super_gradients.training.losses.yolo_v3_loss super_gradients.training.losses.yolo_v5_loss super_gradients.training.metrics super_gradients.training.metrics.classification_metrics super_gradients.training.metrics.detection_metrics super_gradients.training.metrics.metric_utils super_gradients.training.metrics.segmentation_metrics super_gradients.training.models super_gradients.training.models.all_architectures super_gradients.training.models.csp_darknet53 super_gradients.training.models.darknet53 super_gradients.training.models.ddrnet super_gradients.training.models.densenet super_gradients.training.models.dpn super_gradients.training.models.efficientnet super_gradients.training.models.googlenet super_gradients.training.models.laddernet super_gradients.training.models.lenet super_gradients.training.models.mobilenet super_gradients.training.models.mobilenetv2 super_gradients.training.models.mobilenetv3 super_gradients.training.models.pnasnet super_gradients.training.models.preact_resnet super_gradients.training.models.regnet super_gradients.training.models.repvgg super_gradients.training.models.resnet super_gradients.training.models.resnext super_gradients.training.models.senet super_gradients.training.models.sg_module super_gradients.training.models.shelfnet super_gradients.training.models.shufflenet super_gradients.training.models.shufflenetv2 super_gradients.training.models.ssd super_gradients.training.models.vgg super_gradients.training.models.yolov3 super_gradients.training.models.yolov5 super_gradients.training.params super_gradients.training.pretrained_models super_gradients.training.sg_model super_gradients.training.sg_model.sg_model super_gradients.training.utils super_gradients.training.utils.callbacks super_gradients.training.utils.checkpoint_utils super_gradients.training.utils.detection_utils super_gradients.training.utils.distributed_training_utils super_gradients.training.utils.early_stopping super_gradients.training.utils.ema super_gradients.training.utils.export_utils super_gradients.training.utils.module_utils super_gradients.training.utils.optimizer_utils super_gradients.training.utils.optimizers super_gradients.training.utils.optimizers.rmsprop_tf super_gradients.training.utils.regularization_utils super_gradients.training.utils.segmentation_utils super_gradients.training.utils.sg_model_utils super_gradients.training.utils.ssd_utils super_gradients.training.utils.utils super_gradients.training.utils.weight_averaging_utils

move_state_dict_to_device() (in module super_gradients.training.utils.utils) MultiGPUMode (class in super_gradients.training.sg_model.sg_model) MultiGPUModeAutocastWrapper (class in super_gradients.training.utils.distributed_training_utils) MultiOutputModule (class in super_gradients.training.utils.module_utils) MultiScaleCollateFunction (class in super_gradients.training.datasets.datasets_utils)

N

named_sequential_module() (super_gradients.training.models.yolov3.YoloV3 static method) NASRegNet (class in super_gradients.training.models.regnet) NetOutput (class in super_gradients.training.models.shelfnet) NLP (super_gradients.common.data_types.enum.deep_learning_task.DeepLearningTask attribute) NMS_Type (class in super_gradients.training.utils.detection_utils) NO_KEY_MATCHING (super_gradients.training.sg_model.sg_model.StrictLoad attribute)

non_max_suppression() (in module super_gradients.training.utils.detection_utils) normalize() (super_gradients.training.datasets.data_augmentation.DataAugmentation static method) num_anchors (super_gradients.training.utils.detection_utils.Anchors property) num_repeat (super_gradients.training.models.efficientnet.BlockArgs property) NumClassesMissingException numpy_loader_func() (super_gradients.training.datasets.sg_dataset.BaseSgVisionDataset static method)

O

OBJECT_DETECTION (super_gradients.common.data_types.enum.deep_learning_task.DeepLearningTask attribute) (super_gradients.training.datasets.all_datasets.SgLibraryDatasets attribute) OFF (super_gradients.training.sg_model.sg_model.MultiGPUMode attribute) (super_gradients.training.sg_model.sg_model.StrictLoad attribute) OhemCELoss (class in super_gradients.training.losses.ohem_ce_loss) OKBLUE (super_gradients.common.environment.env_helpers.TerminalColours attribute) OKCYAN (super_gradients.common.environment.env_helpers.TerminalColours attribute) OKGREEN (super_gradients.common.environment.env_helpers.TerminalColours attribute) ON (super_gradients.training.sg_model.sg_model.StrictLoad attribute)

one_hot() (in module super_gradients.training.datasets.mixup) onehot() (in module super_gradients.training.losses.label_smoothing_cross_entropy_loss) OTHER (super_gradients.common.data_types.enum.deep_learning_task.DeepLearningTask attribute) out_channels (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) output_filters (super_gradients.training.models.efficientnet.BlockArgs property) output_padding (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) override() (super_gradients.training.params.TrainingParams method) (super_gradients.training.utils.utils.HpmStruct method)

P

padding (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) padding_mode (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) PadShortToCropSize (class in super_gradients.training.utils.segmentation_utils) parse_xml_file() (super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet method) PascalAUG2012SegmentationDataSet (class in super_gradients.training.datasets.segmentation_datasets.pascal_aug_segmentation) PascalAUG2012SegmentationDataSetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) PascalVOC2012DetectionDataSet (class in super_gradients.training.datasets.detection_datasets.pascal_voc_detection) PascalVOC2012DetectionDataSetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) PascalVOC2012SegmentationDataSet (class in super_gradients.training.datasets.segmentation_datasets.pascal_voc_segmentation) PascalVOC2012SegmentationDataSetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) Phase (class in super_gradients.training.utils.callbacks) PhaseCallback (class in super_gradients.training.utils.callbacks) PhaseContext (class in super_gradients.training.utils.callbacks) PhaseContextTestCallback (class in super_gradients.training.utils.callbacks) pixel_accuracy() (in module super_gradients.training.metrics.segmentation_metrics) PixelAccuracy (class in super_gradients.training.metrics.segmentation_metrics) plot_coco_datasaet_images_with_detections() (in module super_gradients.training.utils.detection_utils) PNASNet (class in super_gradients.training.models.pnasnet) PNASNetA() (in module super_gradients.training.models.pnasnet) PNASNetB() (in module super_gradients.training.models.pnasnet) PolyLRCallback (class in super_gradients.training.utils.callbacks)

POSE_ESTIMATION (super_gradients.common.data_types.enum.deep_learning_task.DeepLearningTask attribute) POST_TRAINING (super_gradients.training.utils.callbacks.Phase attribute) posterize() (in module super_gradients.training.datasets.auto_augment) PRE_TRAINING (super_gradients.training.utils.callbacks.Phase attribute) PreActBlock (class in super_gradients.training.models.preact_resnet) (class in super_gradients.training.models.senet) PreActBottleneck (class in super_gradients.training.models.preact_resnet) PreActResNet (class in super_gradients.training.models.preact_resnet) PreActResNet101() (in module super_gradients.training.models.preact_resnet) PreActResNet152() (in module super_gradients.training.models.preact_resnet) PreActResNet18() (in module super_gradients.training.models.preact_resnet) PreActResNet34() (in module super_gradients.training.models.preact_resnet) PreActResNet50() (in module super_gradients.training.models.preact_resnet) predict() (super_gradients.training.sg_model.sg_model.SgModel method) prefetch_dataset() (in module super_gradients.training.legacy.utils) PrefetchDataLoader (class in super_gradients.training.legacy.utils) prep_model_for_conversion() (super_gradients.training.models.repvgg.RepVGG method) (super_gradients.training.models.sg_module.SgModule method) (super_gradients.training.models.yolov3.YoloV3 method) (super_gradients.training.models.yolov5.YoLoV5Base method) print_coloured_text() (super_gradients.common.environment.env_helpers.ColouredTextFormatter static method) print_dataset_details() (super_gradients.training.datasets.dataset_interfaces.dataset_interface.DatasetInterface method) print_once() (in module super_gradients.training.utils.utils)

R

raise_informative_runtime_error() (in module super_gradients.training.utils.checkpoint_utils) rand_augment_ops() (in module super_gradients.training.datasets.auto_augment) rand_augment_transform() (in module super_gradients.training.datasets.auto_augment) rand_bbox() (in module super_gradients.training.datasets.mixup) rand_bbox_minmax() (in module super_gradients.training.datasets.mixup) RandAugment (class in super_gradients.training.datasets.auto_augment) random_perspective() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet method) random_seed() (in module super_gradients.training.utils.utils) RandomErase (class in super_gradients.training.datasets.data_augmentation) RandomFlip (class in super_gradients.training.utils.segmentation_utils) RandomGaussianBlur (class in super_gradients.training.utils.segmentation_utils) RandomRescale (class in super_gradients.training.utils.segmentation_utils) RandomResizedCropAndInterpolation (class in super_gradients.training.datasets.datasets_utils) RandomRotate (class in super_gradients.training.utils.segmentation_utils) re_build_model() (super_gradients.training.sg_model.sg_model.SgModel method) read_ckpt_state_dict() (in module super_gradients.training.utils.checkpoint_utils) reduce_results_tuple_for_ddp() (in module super_gradients.training.utils.distributed_training_utils) reduction (super_gradients.training.losses.ddrnet_loss.DDRNetLoss attribute) (super_gradients.training.losses.focal_loss.FocalLoss attribute) (super_gradients.training.losses.ohem_ce_loss.OhemCELoss attribute) (super_gradients.training.losses.r_squared_loss.RSquaredLoss attribute) (super_gradients.training.losses.shelfnet_ohem_loss.ShelfNetOHEMLoss attribute) (super_gradients.training.losses.ssd_loss.SSDLoss attribute) (super_gradients.training.losses.yolo_v3_loss.YoLoV3DetectionLoss attribute) (super_gradients.training.losses.yolo_v5_loss.YoLoV5DetectionLoss attribute) RegnetDDRBackBone (class in super_gradients.training.models.ddrnet) RegNetX (class in super_gradients.training.models.regnet) RegNetY (class in super_gradients.training.models.regnet) RegNetY200 (class in super_gradients.training.models.regnet) RegNetY400 (class in super_gradients.training.models.regnet) RegNetY600 (class in super_gradients.training.models.regnet)

RegNetY800 (class in super_gradients.training.models.regnet) replace_activations() (in module super_gradients.training.utils.module_utils) RepVGG (class in super_gradients.training.models.repvgg) RepVggA0 (class in super_gradients.training.models.repvgg) RepVggA1 (class in super_gradients.training.models.repvgg) RepVggA2 (class in super_gradients.training.models.repvgg) RepVggB0 (class in super_gradients.training.models.repvgg) RepVggB1 (class in super_gradients.training.models.repvgg) RepVggB2 (class in super_gradients.training.models.repvgg) RepVggB3 (class in super_gradients.training.models.repvgg) RepVGGBlock (class in super_gradients.training.models.repvgg) RepVggCustom (class in super_gradients.training.models.repvgg) RepVggD2SE (class in super_gradients.training.models.repvgg) Rescale (class in super_gradients.training.utils.segmentation_utils) rescale_bboxes_for_image_size() (in module super_gradients.training.utils.detection_utils) ResNet (class in super_gradients.training.models.resnet) ResNet101() (in module super_gradients.training.models.resnet) ResNet152() (in module super_gradients.training.models.resnet) ResNet18() (in module super_gradients.training.models.resnet) ResNet18Cifar() (in module super_gradients.training.models.resnet) ResNet34() (in module super_gradients.training.models.resnet) ResNet50() (in module super_gradients.training.models.resnet) ResNet50_3343() (in module super_gradients.training.models.resnet) ResNeXt (class in super_gradients.training.models.resnext) ResNeXt101() (in module super_gradients.training.models.resnext) ResNeXt50() (in module super_gradients.training.models.resnext) RMSpropTF (class in super_gradients.training.utils.optimizers.rmsprop_tf) rotate() (in module super_gradients.training.datasets.auto_augment) round_filters() (in module super_gradients.training.models.efficientnet) round_repeats() (in module super_gradients.training.models.efficientnet) RSquaredLoss (class in super_gradients.training.losses.r_squared_loss)

S

S3Connector (class in super_gradients.common.data_connection.s3_connector) sample_loader() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method) (super_gradients.training.datasets.segmentation_datasets.segmentation_dataset.SegmentationDataSet static method) sample_post_process() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method) sample_transform() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet method) (super_gradients.training.datasets.segmentation_datasets.segmentation_dataset.SegmentationDataSet static method) save_all_remote_checkpoint_files() (super_gradients.common.data_interface.adnn_model_repository_data_interface.ADNNModelRepositoryDataInterfaces method) save_checkpoint() (super_gradients.training.sg_model.sg_model.SgModel method) save_output_hook() (super_gradients.training.utils.module_utils.MultiOutputModule method) save_remote_checkpoints_file() (super_gradients.common.data_interface.adnn_model_repository_data_interface.ADNNModelRepositoryDataInterfaces method) save_remote_tensorboard_event_files() (super_gradients.common.data_interface.adnn_model_repository_data_interface.ADNNModelRepositoryDataInterfaces method) scale_img() (in module super_gradients.training.utils.detection_utils) scale_wh (super_gradients.training.utils.ssd_utils.DefaultBoxes property) scale_xy (super_gradients.training.utils.ssd_utils.DefaultBoxes property) scaled_all_reduce() (in module super_gradients.training.utils.distributed_training_utils) se_ratio (super_gradients.training.models.efficientnet.BlockArgs property) SEBlock (class in super_gradients.training.models.repvgg) SegmentationDataSet (class in super_gradients.training.datasets.segmentation_datasets.segmentation_dataset) SegmentationTestDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) SegmentHead (class in super_gradients.training.models.ddrnet) SELayer (class in super_gradients.training.models.mobilenetv3) SEMANTIC_SEGMENTATION (super_gradients.common.data_types.enum.deep_learning_task.DeepLearningTask attribute) (super_gradients.training.datasets.all_datasets.SgLibraryDatasets attribute) SENet (class in super_gradients.training.models.senet) SENet18() (in module super_gradients.training.models.senet) separate_zero_wd_params_groups_for_optimizer() (in module super_gradients.training.utils.optimizer_utils) SepConv (class in super_gradients.training.models.pnasnet) SeperableConv2d() (in module super_gradients.training.models.ssd) set_experiment_name() (super_gradients.training.sg_model.sg_model.SgModel method) set_module() (super_gradients.training.sg_model.sg_model.SgModel method) set_schema() (super_gradients.training.utils.utils.HpmStruct method) SgLibraryDatasets (class in super_gradients.training.datasets.all_datasets) SgModel (class in super_gradients.training.sg_model.sg_model) SgModule (class in super_gradients.training.models.sg_module) sharpness() (in module super_gradients.training.datasets.auto_augment) shear_x() (in module super_gradients.training.datasets.auto_augment) shear_y() (in module super_gradients.training.datasets.auto_augment) ShelfBlock (class in super_gradients.training.models.shelfnet) ShelfNet101 (class in super_gradients.training.models.shelfnet) ShelfNet18 (class in super_gradients.training.models.shelfnet) ShelfNet34 (class in super_gradients.training.models.shelfnet) ShelfNet50 (class in super_gradients.training.models.shelfnet) ShelfNet503343 (class in super_gradients.training.models.shelfnet) ShelfNetBase (class in super_gradients.training.models.shelfnet) ShelfNetHW (class in super_gradients.training.models.shelfnet) ShelfNetLW (class in super_gradients.training.models.shelfnet) ShelfNetModuleBase (class in super_gradients.training.models.shelfnet) ShelfNetOHEMLoss (class in super_gradients.training.losses.shelfnet_ohem_loss) ShelfNetSemanticEncodingLoss (class in super_gradients.training.losses.shelfnet_semantic_encoding_loss) ShelfResNetBackBone (class in super_gradients.training.models.shelfnet) ShelfResNetBackBone101 (class in super_gradients.training.models.shelfnet) ShelfResNetBackBone18 (class in super_gradients.training.models.shelfnet) ShelfResNetBackBone34 (class in super_gradients.training.models.shelfnet) ShelfResNetBackBone50 (class in super_gradients.training.models.shelfnet) ShelfResNetBackBone503343 (class in super_gradients.training.models.shelfnet) ShuffleBlock (class in super_gradients.training.models.shufflenet) ShuffleNet (class in super_gradients.training.models.shufflenet) ShuffleNetG2() (in module super_gradients.training.models.shufflenet) ShuffleNetG3() (in module super_gradients.training.models.shufflenet) ShufflenetV2_x0_5 (class in super_gradients.training.models.shufflenetv2) ShufflenetV2_x1_0 (class in super_gradients.training.models.shufflenetv2) ShufflenetV2_x1_5 (class in super_gradients.training.models.shufflenetv2) ShufflenetV2_x2_0 (class in super_gradients.training.models.shufflenetv2) ShuffleNetV2Base (class in super_gradients.training.models.shufflenetv2) singleton() (in module super_gradients.common.decorators.singleton) SingletonMeta (class in super_gradients.common.decorators.singleton) solarize() (in module super_gradients.training.datasets.auto_augment) solarize_add() (in module super_gradients.training.datasets.auto_augment) SPP (class in super_gradients.training.models.csp_darknet53) SPPF (class in super_gradients.training.models.csp_darknet53) SPPLayer (class in super_gradients.training.models.yolov3) SSD (class in super_gradients.training.models.ssd) SSDLiteMobileNetV2 (class in super_gradients.training.models.ssd) SSDLoss (class in super_gradients.training.losses.ssd_loss) SSDMobileNetV1 (class in super_gradients.training.models.ssd) SSDPostPredictCallback (class in super_gradients.training.utils.ssd_utils) Stage (class in super_gradients.training.models.regnet) start() (super_gradients.training.utils.utils.Timer method) static_vars() (in module super_gradients.training.utils.utils) Stem (class in super_gradients.training.models.regnet) step() (super_gradients.training.utils.optimizers.rmsprop_tf.RMSpropTF method) StepLRCallback (class in super_gradients.training.utils.callbacks) stop() (super_gradients.training.utils.utils.Timer method) StrictLoad (class in super_gradients.training.sg_model.sg_model) stride (super_gradients.training.models.efficientnet.BlockArgs property) (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) (super_gradients.training.utils.detection_utils.Anchors property) super_gradients module super_gradients.common module super_gradients.common.abstractions module super_gradients.common.abstractions.abstract_logger module super_gradients.common.auto_logging module super_gradients.common.auto_logging.auto_logger module super_gradients.common.aws_connection module super_gradients.common.aws_connection.aws_connector module super_gradients.common.aws_connection.aws_secrets_manager_connector module super_gradients.common.data_connection module super_gradients.common.data_connection.s3_connector module super_gradients.common.data_interface module super_gradients.common.data_interface.adnn_model_repository_data_interface module super_gradients.common.data_interface.dataset_data_interface module super_gradients.common.data_types module super_gradients.common.data_types.enum module super_gradients.common.data_types.enum.deep_learning_task module super_gradients.common.decorators module super_gradients.common.decorators.deci_logger module super_gradients.common.decorators.explicit_params_validator module super_gradients.common.decorators.singleton module super_gradients.common.environment module super_gradients.common.environment.env_helpers module super_gradients.common.environment.environment_config module super_gradients.training module super_gradients.training.datasets module super_gradients.training.datasets.all_datasets module super_gradients.training.datasets.auto_augment module super_gradients.training.datasets.classification_datasets module super_gradients.training.datasets.data_augmentation module super_gradients.training.datasets.dataset_interfaces module super_gradients.training.datasets.dataset_interfaces.dataset_interface module super_gradients.training.datasets.datasets_conf module super_gradients.training.datasets.datasets_utils module super_gradients.training.datasets.detection_datasets module super_gradients.training.datasets.detection_datasets.coco_detection module super_gradients.training.datasets.detection_datasets.detection_dataset module super_gradients.training.datasets.detection_datasets.pascal_voc_detection module

super_gradients.training.datasets.mixup module super_gradients.training.datasets.segmentation_datasets module super_gradients.training.datasets.segmentation_datasets.cityscape_segmentation module super_gradients.training.datasets.segmentation_datasets.coco_segmentation module super_gradients.training.datasets.segmentation_datasets.pascal_aug_segmentation module super_gradients.training.datasets.segmentation_datasets.pascal_voc_segmentation module super_gradients.training.datasets.segmentation_datasets.segmentation_dataset module super_gradients.training.datasets.sg_dataset module super_gradients.training.exceptions module super_gradients.training.exceptions.dataset_exceptions module super_gradients.training.exceptions.sg_model_exceptions module super_gradients.training.legacy module super_gradients.training.legacy.utils module super_gradients.training.losses module super_gradients.training.losses.all_losses module super_gradients.training.losses.ddrnet_loss module super_gradients.training.losses.focal_loss module super_gradients.training.losses.label_smoothing_cross_entropy_loss module super_gradients.training.losses.ohem_ce_loss module super_gradients.training.losses.r_squared_loss module super_gradients.training.losses.shelfnet_ohem_loss module super_gradients.training.losses.shelfnet_semantic_encoding_loss module super_gradients.training.losses.ssd_loss module super_gradients.training.losses.yolo_v3_loss module super_gradients.training.losses.yolo_v5_loss module super_gradients.training.metrics module super_gradients.training.metrics.classification_metrics module super_gradients.training.metrics.detection_metrics module super_gradients.training.metrics.metric_utils module super_gradients.training.metrics.segmentation_metrics module super_gradients.training.models module super_gradients.training.models.all_architectures module super_gradients.training.models.csp_darknet53 module super_gradients.training.models.darknet53 module super_gradients.training.models.ddrnet module super_gradients.training.models.densenet module super_gradients.training.models.dpn module super_gradients.training.models.efficientnet module super_gradients.training.models.googlenet module super_gradients.training.models.laddernet module super_gradients.training.models.lenet module super_gradients.training.models.mobilenet module super_gradients.training.models.mobilenetv2 module super_gradients.training.models.mobilenetv3 module super_gradients.training.models.pnasnet module super_gradients.training.models.preact_resnet module super_gradients.training.models.regnet module super_gradients.training.models.repvgg module super_gradients.training.models.resnet module super_gradients.training.models.resnext module super_gradients.training.models.senet module super_gradients.training.models.sg_module module super_gradients.training.models.shelfnet module super_gradients.training.models.shufflenet module super_gradients.training.models.shufflenetv2 module super_gradients.training.models.ssd module super_gradients.training.models.vgg module super_gradients.training.models.yolov3 module super_gradients.training.models.yolov5 module super_gradients.training.params module super_gradients.training.pretrained_models module super_gradients.training.sg_model module super_gradients.training.sg_model.sg_model module super_gradients.training.utils module super_gradients.training.utils.callbacks module super_gradients.training.utils.checkpoint_utils module super_gradients.training.utils.detection_utils module super_gradients.training.utils.distributed_training_utils module super_gradients.training.utils.early_stopping module super_gradients.training.utils.ema module super_gradients.training.utils.export_utils module super_gradients.training.utils.module_utils module super_gradients.training.utils.optimizer_utils module super_gradients.training.utils.optimizers module super_gradients.training.utils.optimizers.rmsprop_tf module super_gradients.training.utils.regularization_utils module super_gradients.training.utils.segmentation_utils module super_gradients.training.utils.sg_model_utils module super_gradients.training.utils.ssd_utils module super_gradients.training.utils.utils module super_gradients.training.utils.weight_averaging_utils module supported_phases (super_gradients.training.utils.early_stopping.EarlyStop attribute)

T

target_loader() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method) (super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet method) (super_gradients.training.datasets.segmentation_datasets.cityscape_segmentation.CityscapesDataset method) (super_gradients.training.datasets.segmentation_datasets.coco_segmentation.CoCoSegmentationDataSet method) (super_gradients.training.datasets.segmentation_datasets.pascal_aug_segmentation.PascalAUG2012SegmentationDataSet static method) (super_gradients.training.datasets.segmentation_datasets.segmentation_dataset.SegmentationDataSet static method) target_transform() (super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet static method) (super_gradients.training.datasets.segmentation_datasets.cityscape_segmentation.CityscapesDataset static method) (super_gradients.training.datasets.segmentation_datasets.segmentation_dataset.SegmentationDataSet static method) tensor_container_to_device() (in module super_gradients.training.utils.utils) TerminalColours (class in super_gradients.common.environment.env_helpers) TEST (super_gradients.training.sg_model.sg_model.EvaluationType attribute) test() (in module super_gradients.training.models.dpn) (in module super_gradients.training.models.pnasnet) (in module super_gradients.training.models.preact_resnet) (in module super_gradients.training.models.senet) (in module super_gradients.training.models.shufflenet) (in module super_gradients.training.models.vgg) (super_gradients.training.sg_model.sg_model.SgModel method) TEST_BATCH_END (super_gradients.training.utils.callbacks.Phase attribute) TEST_END (super_gradients.training.utils.callbacks.Phase attribute) TestDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) TestYoloDetectionDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) text_file_loader_func() (super_gradients.training.datasets.sg_dataset.BaseSgVisionDataset static method) Timer (class in super_gradients.training.utils.utils) TinyImageNetDatasetInterface (class in super_gradients.training.datasets.dataset_interfaces.dataset_interface) TinyYoloV3 (class in super_gradients.training.models.yolov3) to_dict() (super_gradients.training.utils.utils.HpmStruct method) to_tensor() (super_gradients.training.datasets.data_augmentation.DataAugmentation static method) Top5 (class in super_gradients.training.metrics.classification_metrics) total (super_gradients.training.metrics.classification_metrics.Accuracy attribute) ToyTestClassificationMetric (class in super_gradients.training.metrics.classification_metrics) train() (super_gradients.training.models.repvgg.RepVGG method) (super_gradients.training.sg_model.sg_model.SgModel method) TRAIN_BATCH_END (super_gradients.training.utils.callbacks.Phase attribute) TRAIN_BATCH_STEP (super_gradients.training.utils.callbacks.Phase attribute) TRAIN_EPOCH_END (super_gradients.training.utils.callbacks.Phase attribute) TRAIN_EPOCH_START (super_gradients.training.utils.callbacks.Phase attribute) training (super_gradients.training.datasets.data_augmentation.RandomErase attribute) (super_gradients.training.datasets.datasets_utils.RandomResizedCropAndInterpolation attribute) (super_gradients.training.losses.shelfnet_ohem_loss.ShelfNetOHEMLoss attribute) (super_gradients.training.metrics.classification_metrics.Top5 attribute) (super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric attribute) (super_gradients.training.metrics.detection_metrics.DetectionMetrics attribute) (super_gradients.training.metrics.segmentation_metrics.PixelAccuracy attribute) (super_gradients.training.models.csp_darknet53.Bottleneck attribute) (super_gradients.training.models.csp_darknet53.BottleneckCSP attribute) (super_gradients.training.models.csp_darknet53.C3 attribute) (super_gradients.training.models.csp_darknet53.Conv attribute) (super_gradients.training.models.csp_darknet53.CSPDarknet53 attribute) (super_gradients.training.models.csp_darknet53.Focus attribute) (super_gradients.training.models.csp_darknet53.SPP attribute) (super_gradients.training.models.csp_darknet53.SPPF attribute) (super_gradients.training.models.csp_darknet53.ViewModule attribute) (super_gradients.training.models.darknet53.Darknet53 attribute) (super_gradients.training.models.darknet53.Darknet53Base attribute) (super_gradients.training.models.darknet53.DarkResidualBlock attribute) (super_gradients.training.models.darknet53.ViewModule attribute) (super_gradients.training.models.ddrnet.AnyBackBoneDDRNet23 attribute) (super_gradients.training.models.ddrnet.BasicDDRBackBone attribute) (super_gradients.training.models.ddrnet.DAPPM attribute) (super_gradients.training.models.ddrnet.DAPPMBranch attribute) (super_gradients.training.models.ddrnet.DDRBackBoneBase attribute) (super_gradients.training.models.ddrnet.DDRNet attribute) (super_gradients.training.models.ddrnet.DDRNet23 attribute) (super_gradients.training.models.ddrnet.DDRNet23Slim attribute) (super_gradients.training.models.ddrnet.DDRNetCustom attribute) (super_gradients.training.models.ddrnet.RegnetDDRBackBone attribute) (super_gradients.training.models.ddrnet.SegmentHead attribute) (super_gradients.training.models.ddrnet.UpscaleOnline attribute) (super_gradients.training.models.densenet.DenseNet attribute) (super_gradients.training.models.dpn.Bottleneck attribute) (super_gradients.training.models.dpn.DPN attribute) (super_gradients.training.models.efficientnet.EfficientNet attribute) (super_gradients.training.models.efficientnet.Identity attribute) (super_gradients.training.models.efficientnet.MBConvBlock attribute) (super_gradients.training.models.googlenet.BasicConv2d attribute) (super_gradients.training.models.googlenet.GoogLeNet attribute) (super_gradients.training.models.googlenet.Inception attribute) (super_gradients.training.models.googlenet.InceptionAux attribute) (super_gradients.training.models.laddernet.BaseNet attribute) (super_gradients.training.models.laddernet.BasicBlock attribute) (super_gradients.training.models.laddernet.Bottleneck attribute) (super_gradients.training.models.laddernet.Decoder attribute) (super_gradients.training.models.laddernet.FCNHead attribute) (super_gradients.training.models.laddernet.Final_LadderBlock attribute) (super_gradients.training.models.laddernet.Initial_LadderBlock attribute) (super_gradients.training.models.laddernet.LadderBlock attribute) (super_gradients.training.models.laddernet.LadderBottleneck attribute) (super_gradients.training.models.laddernet.LadderHead attribute) (super_gradients.training.models.laddernet.LadderNet attribute) (super_gradients.training.models.laddernet.LadderNet101 attribute) (super_gradients.training.models.laddernet.LadderNet50 attribute) (super_gradients.training.models.laddernet.LadderNet503433 attribute) (super_gradients.training.models.laddernet.LadderNetBackBone101 attribute) (super_gradients.training.models.laddernet.LadderNetBackBone50 attribute) (super_gradients.training.models.laddernet.LadderNetBackBone503433 attribute) (super_gradients.training.models.laddernet.LadderResNet attribute) (super_gradients.training.models.lenet.LeNet attribute) (super_gradients.training.models.mobilenet.Block attribute) (super_gradients.training.models.mobilenet.MobileNet attribute) (super_gradients.training.models.mobilenetv2.InvertedResidual attribute) (super_gradients.training.models.mobilenetv2.MobileNetV2 attribute) (super_gradients.training.models.mobilenetv3.h_sigmoid attribute) (super_gradients.training.models.mobilenetv3.h_swish attribute) (super_gradients.training.models.mobilenetv3.InvertedResidual attribute) (super_gradients.training.models.mobilenetv3.MobileNetV3 attribute) (super_gradients.training.models.mobilenetv3.SELayer attribute) (super_gradients.training.models.pnasnet.CellA attribute) (super_gradients.training.models.pnasnet.CellB attribute) (super_gradients.training.models.pnasnet.PNASNet attribute) (super_gradients.training.models.pnasnet.SepConv attribute) (super_gradients.training.models.preact_resnet.PreActBlock attribute) (super_gradients.training.models.preact_resnet.PreActBottleneck attribute) (super_gradients.training.models.preact_resnet.PreActResNet attribute) (super_gradients.training.models.regnet.AnyNetX attribute) (super_gradients.training.models.regnet.CustomRegNet attribute) (super_gradients.training.models.regnet.Head attribute) (super_gradients.training.models.regnet.NASRegNet attribute) (super_gradients.training.models.regnet.RegNetX attribute) (super_gradients.training.models.regnet.RegNetY attribute) (super_gradients.training.models.regnet.RegNetY200 attribute) (super_gradients.training.models.regnet.RegNetY400 attribute) (super_gradients.training.models.regnet.RegNetY600 attribute) (super_gradients.training.models.regnet.RegNetY800 attribute) (super_gradients.training.models.regnet.Stage attribute) (super_gradients.training.models.regnet.Stem attribute) (super_gradients.training.models.regnet.XBlock attribute) (super_gradients.training.models.repvgg.RepVGG attribute) (super_gradients.training.models.repvgg.RepVggA0 attribute) (super_gradients.training.models.repvgg.RepVggA1 attribute) (super_gradients.training.models.repvgg.RepVggA2 attribute) (super_gradients.training.models.repvgg.RepVggB0 attribute) (super_gradients.training.models.repvgg.RepVggB1 attribute) (super_gradients.training.models.repvgg.RepVggB2 attribute) (super_gradients.training.models.repvgg.RepVggB3 attribute) (super_gradients.training.models.repvgg.RepVGGBlock attribute) (super_gradients.training.models.repvgg.RepVggCustom attribute) (super_gradients.training.models.repvgg.RepVggD2SE attribute) (super_gradients.training.models.repvgg.SEBlock attribute) (super_gradients.training.models.resnet.BasicBlock attribute) (super_gradients.training.models.resnet.Bottleneck attribute) (super_gradients.training.models.resnet.CifarResNet attribute) (super_gradients.training.models.resnet.ResNet attribute) (super_gradients.training.models.resnext.GroupedConvBlock attribute) (super_gradients.training.models.resnext.ResNeXt attribute) (super_gradients.training.models.senet.BasicBlock attribute) (super_gradients.training.models.senet.PreActBlock attribute) (super_gradients.training.models.senet.SENet attribute) (super_gradients.training.models.sg_module.SgModule attribute) (super_gradients.training.models.shelfnet.AttentionRefinementModule attribute) (super_gradients.training.models.shelfnet.ConvBNReLU attribute) (super_gradients.training.models.shelfnet.DecoderBase attribute) (super_gradients.training.models.shelfnet.DecoderHW attribute) (super_gradients.training.models.shelfnet.DecoderLW attribute) (super_gradients.training.models.shelfnet.FCNHead attribute) (super_gradients.training.models.shelfnet.LadderBlockBase attribute) (super_gradients.training.models.shelfnet.LadderBlockHW attribute) (super_gradients.training.models.shelfnet.LadderBlockLW attribute) (super_gradients.training.models.shelfnet.NetOutput attribute) (super_gradients.training.models.shelfnet.ShelfBlock attribute) (super_gradients.training.models.shelfnet.ShelfNet101 attribute) (super_gradients.training.models.shelfnet.ShelfNet18 attribute) (super_gradients.training.models.shelfnet.ShelfNet34 attribute) (super_gradients.training.models.shelfnet.ShelfNet50 attribute) (super_gradients.training.models.shelfnet.ShelfNet503343 attribute) (super_gradients.training.models.shelfnet.ShelfNetBase attribute) (super_gradients.training.models.shelfnet.ShelfNetHW attribute) (super_gradients.training.models.shelfnet.ShelfNetLW attribute) (super_gradients.training.models.shelfnet.ShelfNetModuleBase attribute) (super_gradients.training.models.shelfnet.ShelfResNetBackBone attribute) (super_gradients.training.models.shelfnet.ShelfResNetBackBone101 attribute) (super_gradients.training.models.shelfnet.ShelfResNetBackBone18 attribute) (super_gradients.training.models.shelfnet.ShelfResNetBackBone34 attribute) (super_gradients.training.models.shelfnet.ShelfResNetBackBone50 attribute) (super_gradients.training.models.shelfnet.ShelfResNetBackBone503343 attribute) (super_gradients.training.models.shufflenet.Bottleneck attribute) (super_gradients.training.models.shufflenet.ShuffleBlock attribute) (super_gradients.training.models.shufflenet.ShuffleNet attribute) (super_gradients.training.models.shufflenetv2.CustomizedShuffleNetV2 attribute) (super_gradients.training.models.shufflenetv2.ShufflenetV2_x0_5 attribute) (super_gradients.training.models.shufflenetv2.ShufflenetV2_x1_0 attribute) (super_gradients.training.models.shufflenetv2.ShufflenetV2_x1_5 attribute) (super_gradients.training.models.shufflenetv2.ShufflenetV2_x2_0 attribute) (super_gradients.training.models.shufflenetv2.ShuffleNetV2Base attribute) (super_gradients.training.models.ssd.SSD attribute) (super_gradients.training.models.ssd.SSDLiteMobileNetV2 attribute) (super_gradients.training.models.ssd.SSDMobileNetV1 attribute) (super_gradients.training.models.vgg.VGG attribute) (super_gradients.training.models.yolov3.SPPLayer attribute) (super_gradients.training.models.yolov3.TinyYoloV3 attribute) (super_gradients.training.models.yolov3.Upsample attribute) (super_gradients.training.models.yolov3.YOLOLayer attribute) (super_gradients.training.models.yolov3.YoloV3 attribute) (super_gradients.training.models.yolov5.Concat attribute) (super_gradients.training.models.yolov5.Custom_YoLoV5 attribute) (super_gradients.training.models.yolov5.Detect attribute) (super_gradients.training.models.yolov5.YoLoV5Base attribute) (super_gradients.training.models.yolov5.YoLoV5DarknetBackbone attribute) (super_gradients.training.models.yolov5.YoLoV5Head attribute) (super_gradients.training.models.yolov5.YoLoV5L attribute) (super_gradients.training.models.yolov5.YoLoV5M attribute) (super_gradients.training.models.yolov5.YoloV5PostPredictionCallback attribute) (super_gradients.training.models.yolov5.YoLoV5S attribute) (super_gradients.training.models.yolov5.YoLoV5X attribute) (super_gradients.training.utils.detection_utils.Anchors attribute) (super_gradients.training.utils.detection_utils.DetectionPostPredictionCallback attribute) (super_gradients.training.utils.detection_utils.YoloV3NonMaxSuppression attribute) (super_gradients.training.utils.export_utils.ExportableHardswish attribute) (super_gradients.training.utils.module_utils.MultiOutputModule attribute) (super_gradients.training.utils.regularization_utils.DropPath attribute) (super_gradients.training.utils.ssd_utils.SSDPostPredictCallback attribute) (super_gradients.training.utils.utils.WrappedModel attribute)

TrainingParams (class in super_gradients.training.params) translate_x_abs() (in module super_gradients.training.datasets.auto_augment) translate_x_rel() (in module super_gradients.training.datasets.auto_augment) translate_y_abs() (in module super_gradients.training.datasets.auto_augment) translate_y_rel() (in module super_gradients.training.datasets.auto_augment) transposed (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute) try_port() (in module super_gradients.training.utils.sg_model_utils)

U

UNDERLINE (super_gradients.common.environment.env_helpers.TerminalColours attribute) undo_image_preprocessing() (in module super_gradients.training.utils.detection_utils) unpack_batch_items() (in module super_gradients.training.utils.sg_model_utils) UnsupportedBatchItemsFormat UnsupportedOptimizerFormat UnsupportedTrainingParameterFormat update() (super_gradients.training.metrics.classification_metrics.Accuracy method) (super_gradients.training.metrics.classification_metrics.Top5 method) (super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric method) (super_gradients.training.metrics.detection_metrics.DetectionMetrics method) (super_gradients.training.metrics.segmentation_metrics.IoU method) (super_gradients.training.metrics.segmentation_metrics.PixelAccuracy method) (super_gradients.training.utils.ema.ModelEMA method) (super_gradients.training.utils.utils.AverageMeter method)

update_architecture() (super_gradients.training.sg_model.sg_model.SgModel method) update_attr() (super_gradients.training.utils.ema.ModelEMA method) update_context() (super_gradients.training.utils.callbacks.PhaseContext method) update_lr() (super_gradients.training.utils.callbacks.LRCallbackBase method) update_param_groups() (super_gradients.training.models.sg_module.SgModule method) (super_gradients.training.models.shelfnet.ShelfNetBase method) (super_gradients.training.models.yolov5.YoLoV5Base method) update_snapshots_dict() (super_gradients.training.utils.weight_averaging_utils.ModelWeightAveraging method) upload_buffer() (super_gradients.common.data_connection.s3_connector.S3Connector method) upload_file() (super_gradients.common.data_connection.s3_connector.S3Connector method) upload_file_from_stream() (super_gradients.common.data_connection.s3_connector.S3Connector method) Upsample (class in super_gradients.training.models.yolov3) UpscaleOnline (class in super_gradients.training.models.ddrnet)

V

validate() (super_gradients.training.utils.utils.HpmStruct method) validate_backbone_attributes() (super_gradients.training.models.ddrnet.DDRBackBoneBase method) VALIDATION (super_gradients.training.sg_model.sg_model.EvaluationType attribute) VALIDATION_BATCH_END (super_gradients.training.utils.callbacks.Phase attribute) VALIDATION_EPOCH_END (super_gradients.training.utils.callbacks.Phase attribute)

verify_correctness_of_parameters() (in module super_gradients.training.models.regnet) VGG (class in super_gradients.training.models.vgg) ViewModule (class in super_gradients.training.models.csp_darknet53) (class in super_gradients.training.models.darknet53) visualize_batch() (super_gradients.training.utils.detection_utils.DetectionVisualization static method)

W

WarmupLRCallback (class in super_gradients.training.utils.callbacks) WARNING (super_gradients.common.environment.env_helpers.TerminalColours attribute) weight (super_gradients.training.models.efficientnet.Conv2dDynamicSamePadding attribute) (super_gradients.training.models.efficientnet.Conv2dStaticSamePadding attribute)

width_multiplier() (in module super_gradients.training.models.csp_darknet53) (in module super_gradients.training.models.resnet) WrappedModel (class in super_gradients.training.utils.utils) write_hpms() (in module super_gradients.training.utils.sg_model_utils) write_training_results() (in module super_gradients.training.utils.sg_model_utils)

X

XBlock (class in super_gradients.training.models.regnet)

Y

yolo_v3_non_max_suppression() (in module super_gradients.training.utils.detection_utils) YOLOLayer (class in super_gradients.training.models.yolov3) YoloV3 (class in super_gradients.training.models.yolov3) YoLoV3DetectionLoss (class in super_gradients.training.losses.yolo_v3_loss) YoloV3NonMaxSuppression (class in super_gradients.training.utils.detection_utils) YoLoV5Base (class in super_gradients.training.models.yolov5) YoLoV5DarknetBackbone (class in super_gradients.training.models.yolov5)

YoLoV5DetectionLoss (class in super_gradients.training.losses.yolo_v5_loss) YoLoV5Head (class in super_gradients.training.models.yolov5) YoLoV5L (class in super_gradients.training.models.yolov5) YoLoV5M (class in super_gradients.training.models.yolov5) YoloV5PostPredictionCallback (class in super_gradients.training.models.yolov5) YoLoV5S (class in super_gradients.training.models.yolov5) YoLoV5X (class in super_gradients.training.models.yolov5)