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Functions1,065 in github.com/Nota-NetsPresso/netspresso-trainer

⨍ Functions 1,065◇ Types & classes 251

↓ 1 callersMethodget_warp_matrix

Calculate the affine transformation matrix that can warp the bbox area in the input image to the output size.

src/netspresso_trainer/dataloaders/augmentation/custom/image_proc.py:902

↓ 1 callersMethodgrid_anchors

(self, cell_anchors, grid_templates, grid_sizes: List[List[int]], strides: List[List[Tensor]])

src/netspresso_trainer/models/heads/detection/experimental/detection/anchor_generator.py:103

↓ 1 callersFunctionimport_modules_by_task

(conf)

tools/device_runtime/tflite_run.py:30

↓ 1 callersMethodinference

(self)

src/netspresso_trainer/pipelines/inference.py:61

↓ 1 callersFunctioninference_cli

()

src/netspresso_trainer/inferencer_main.py:68

↓ 1 callersFunctioninference_common

( conf: DictConfig, task: str, model_name: str, logging_dir: Path, log_level: Literal['DEB

src/netspresso_trainer/inferencer_common.py:31

↓ 1 callersFunctioninference_with_yaml_impl

(gpus: Optional[Union[List, int]], data: Union[Path, str], augmentation: Union[Path, str],

src/netspresso_trainer/inferencer_main.py:35

↓ 1 callersMethodinitialize_biases

(self, prior_prob)

src/netspresso_trainer/models/heads/detection/experimental/anchor_free_decoupled_head.py:141

↓ 1 callersMethodinitialize_biases

(self, prior_prob)

src/netspresso_trainer/models/heads/detection/experimental/yolo_fastest_head.py:87

↓ 1 callersMethodintersection_and_union

(self, output, target)

src/netspresso_trainer/metrics/segmentation/metric.py:71

↓ 1 callersMethodintersection_and_union

(self, output, target)

src/netspresso_trainer/metrics/segmentation/metric.py:115

↓ 1 callersFunctioninverse_sigmoid

(x: torch.Tensor, eps: float=1e-5)

src/netspresso_trainer/models/op/denoising.py:24

↓ 1 callersMethodkeypoint_pck_accuracy

(self, pred, gt, mask, thr, norm_factor)

src/netspresso_trainer/metrics/pose_estimation/metric.py:65

↓ 1 callersFunctionlaunch_gradio

(args)

demo/app.py:54

↓ 1 callersFunctionload_augmentation_config

(task)

demo/func/main.py:43

↓ 1 callersFunctionload_backbone_and_head_model

( conf_model, task, backbone_name, head_name, num_classes, model_checkpoint, use_pretrained, f

src/netspresso_trainer/models/builder.py:54

↓ 1 callersMethodload_class_map

(self, id_mapping)

src/netspresso_trainer/dataloaders/base.py:148

↓ 1 callersMethodload_class_map

(self, id_mapping)

src/netspresso_trainer/dataloaders/segmentation.py:90

↓ 1 callersFunctionload_classification_class_map

(labels_path: Optional[Union[str, Path]])

src/netspresso_trainer/dataloaders/utils/misc.py:65

↓ 1 callersFunctionload_full_model

(conf_model, model_name, num_classes, model_checkpoint, use_pretrained)

src/netspresso_trainer/models/builder.py:39

↓ 1 callersMethodload_huggingface_samples

(self)

src/netspresso_trainer/dataloaders/base.py:185

↓ 1 callersMethodload_id_mapping

(self)

src/netspresso_trainer/dataloaders/base.py:144

↓ 1 callersFunctionload_model

(model_path)

tools/device_runtime/tflite_run.py:41

↓ 1 callersFunctionload_model_config

(task, model)

demo/func/main.py:38

↓ 1 callersFunctionload_optimizer_checkpoint

(conf, optimizer, scheduler)

src/netspresso_trainer/pipelines/builder.py:40

↓ 1 callersMethodload_samples

(self)

src/netspresso_trainer/dataloaders/base.py:151

↓ 1 callersMethodload_split_samples

(self)

src/netspresso_trainer/dataloaders/base.py:159

↓ 1 callersFunctionloaded_dataset_check

( conf_data: DictConfig, train_dataset: data.Dataset, valid_dataset: data.Dataset, test_datase

src/netspresso_trainer/dataloaders/builder.py:62

↓ 1 callersMethodlog_artifact

(self)

src/netspresso_trainer/loggers/mlflow.py:88

↓ 1 callersMethodlog_end_epoch

( self, epoch: int, time_for_epoch: float, valid_samples: Optional[List] = Non

src/netspresso_trainer/pipelines/train.py:249

↓ 1 callersMethodlog_end_evaluation

( self, time_for_evaluation: float, valid_samples: Optional[List] = None, )

src/netspresso_trainer/pipelines/evaluation.py:92

↓ 1 callersMethodlog_end_inference

( self, time_for_inference: float, valid_samples: Optional[List] = None, )

src/netspresso_trainer/pipelines/inference.py:77

↓ 1 callersMethodlog_end_of_traning

(self, final_metrics=None)

src/netspresso_trainer/loggers/base.py:172

↓ 1 callersMethodlog_images_with_dict

(self, image_dict, mode='train')

src/netspresso_trainer/loggers/tensorboard.py:80

↓ 1 callersMethodlog_metrics_with_dict

(self, scalar_dict, mode="train")

src/netspresso_trainer/loggers/mlflow.py:77

↓ 1 callersMethodlog_onnx_model

Log an ONNX model to MLflow. Args: model_path: Path to the ONNX model file input_example: Optional input ten

src/netspresso_trainer/loggers/mlflow.py:115

↓ 1 callersMethodlog_scalars_with_dict

(self, scalar_dict, mode='train')

src/netspresso_trainer/loggers/tensorboard.py:73

↓ 1 callersMethodlog_start_of_training

(self, hparams=None)

src/netspresso_trainer/loggers/base.py:180

↓ 1 callersMethodlogin

(self, email: str, password: str)

demo/func/pynetspresso.py:23

↓ 1 callersFunctionmagic_image_handler

(img)

src/netspresso_trainer/loggers/visualizer.py:208

↓ 1 callersFunctionmain

()

tools/open_dataset_tool/objects365.py:169

↓ 1 callersFunctionmatch_detection_batch

Match predictions with target labels based on IoU levels. Args: predictions (np.ndarray): Batch prediction. Describes a single image

src/netspresso_trainer/metrics/detection/metric.py:62

↓ 1 callersMethodmeta_blocks

(num_blocks, module_idx, hidden_size, num_attention_heads, attention_hidden_size, attentio

src/netspresso_trainer/models/backbones/experimental/efficientformer.py:285

↓ 1 callersMethodmixup

(self, origin_img, origin_labels, input_dim, dataset)

src/netspresso_trainer/dataloaders/augmentation/custom/mosaic.py:270

↓ 1 callersFunctionnms_fast_rcnn

dets is a numpy array : num_dets, 4 scores ia nump array : num_dets,

tools/device_runtime/postprocessors/detection_postprocessor.py:73

↓ 1 callersFunctionnormalize

(img)

tools/device_runtime/preprocessors/preprocessor.py:49

↓ 1 callersMethodnormalize_bboxes

Normalize bounding boxes to [0, 1] range

src/netspresso_trainer/models/heads/detection/experimental/rtdetr_head.py:654

↓ 1 callersMethodnormalize_bboxes

Normalize bounding boxes to [0, 1] range

src/netspresso_trainer/losses/detection/rtdetr.py:381

↓ 1 callersMethodnum_anchors_per_location

(self)

src/netspresso_trainer/models/heads/detection/experimental/detection/anchor_generator.py:98

↓ 1 callersFunctionparse_args

()

tools/onnx_convert.py:32

↓ 1 callersFunctionparse_args

()

tools/scheduler_test.py:31

↓ 1 callersFunctionparse_args

()

tools/exir_convert.py:34

↓ 1 callersFunctionparse_args

()

tools/fx_convert.py:30

↓ 1 callersFunctionparse_args

()

tools/device_runtime/tflite_run.py:24

↓ 1 callersFunctionparse_args

()

demo/app.py:24

↓ 1 callersFunctionprecisions_per_class

( matches: np.ndarray, prediction_confidence: np.ndarray, prediction_class_ids: np.ndarray, tr

src/netspresso_trainer/metrics/detection/metric.py:191

↓ 1 callersFunctionprocess_annotations

(annotation_path, label_dir)

tools/open_dataset_tool/objects365.py:114

↓ 1 callersFunctionprocess_split

(split, patches, base_url, objects365_path, num_process)

tools/open_dataset_tool/objects365.py:136

↓ 1 callersFunctionrandom_affine

( img, targets, target_size, degrees, translate, scales, shear, fill, )

src/netspresso_trainer/dataloaders/augmentation/custom/mosaic.py:135

↓ 1 callersMethodrandom_set

(self)

src/netspresso_trainer/dataloaders/augmentation/custom/image_proc.py:772

↓ 1 callersMethodrandom_set

(self, image)

src/netspresso_trainer/dataloaders/augmentation/custom/image_proc.py:810

↓ 1 callersFunctionread_json

(json_path)

demo/func/experiments.py:23

↓ 1 callersFunctionrecall_per_class

( matches: np.ndarray, prediction_confidence: np.ndarray, prediction_class_ids: np.ndarray, tr

src/netspresso_trainer/metrics/detection/metric.py:226

↓ 1 callersMethodreset

(self)

src/netspresso_trainer/utils/record.py:32

↓ 1 callersMethodreset

(self)

src/netspresso_trainer/utils/record.py:61

↓ 1 callersFunctionround_up

Round up `x` to the biggest-nearest multiple of `div`

src/netspresso_trainer/models/heads/detection/experimental/yolo_head.py:32

↓ 1 callersFunctionrun_distributed_evaluation_script

(gpu_ids, data, augmentation, model, logging, environment, log_level, ta

src/netspresso_trainer/evaluator_main.py:35

↓ 1 callersFunctionrun_distributed_training_script

(gpu_ids, data, augmentation, model, training, logging, environment, log_level,

src/netspresso_trainer/trainer_main.py:36

↓ 1 callersFunctionsave_checkpoint

(obj_dict, f: Union[str, Path])

src/netspresso_trainer/utils/checkpoint.py:50

↓ 1 callersFunctionsave_graphmodule

(model: nn.Module, f)

src/netspresso_trainer/utils/fx.py:36

↓ 1 callersMethodsave_result

(self, image_dict: Dict, prefix, epoch)

src/netspresso_trainer/loggers/image.py:42

↓ 1 callersMethodsave_summary

(self, losses, metrics, predictions, time_for_evaluation)

src/netspresso_trainer/pipelines/evaluation.py:122

↓ 1 callersMethodsave_summary

(self, time_for_inference, predictions)

src/netspresso_trainer/pipelines/inference.py:90

↓ 1 callersMethodseparate_anchor

separate anchor and bbouding box

src/netspresso_trainer/losses/detection/yolov9.py:429

↓ 1 callersMethodsequence_reduce

SegFormer

src/netspresso_trainer/models/op/base_metaformer.py:147

↓ 1 callersMethodset_cell_anchors

(self, dtype: torch.dtype, device: torch.device)

src/netspresso_trainer/models/heads/detection/experimental/detection/anchor_generator.py:95

↓ 1 callersMethodset_epoch

r""" Sets the epoch for this sampler. When :attr:`shuffle=True`, this ensures all replicas use a different random ordering for each ep

src/netspresso_trainer/dataloaders/utils/sampler.py:122

↓ 1 callersMethodset_provider

(self, device)

src/netspresso_trainer/models/base.py:167

↓ 1 callersMethodsimota_matching

(self, cost, pair_wise_ious, gt_classes, num_gt, fg_mask)

src/netspresso_trainer/losses/detection/yolox.py:405

↓ 1 callersFunctionsplit_param_groups

(model, overwrited_config_dict)

src/netspresso_trainer/optimizers/builder.py:67

↓ 1 callersFunctiontab_augmentation

(args, task_choices, model_choices)

demo/tab/home/augmentation.py:14

↓ 1 callersFunctiontab_compressor

(args)

demo/tab/compressor.py:14

↓ 1 callersFunctiontab_dataset

(args, task_choices, model_choices)

demo/tab/home/dataset.py:3

↓ 1 callersFunctiontab_experiments

(args)

demo/tab/experiments.py:9

↓ 1 callersFunctiontab_home

(args)

demo/tab/home/main.py:48

↓ 1 callersFunctiontab_scheduler

(args, task_choices, model_choices)

demo/tab/home/scheduler.py:13

↓ 1 callersFunctiontab_train

(args, task_choices, model_choices)

demo/tab/home/train.py:17

↓ 1 callersMethodtest_step

(self, test_model, batch)

src/netspresso_trainer/pipelines/task_processors/base.py:58

↓ 1 callersFunctiontrain_cli

()

src/netspresso_trainer/trainer_main.py:134

↓ 1 callersFunctiontrain_cli_without_additional_gpu_check

()

src/netspresso_trainer/trainer_main.py:151

↓ 1 callersMethodtrain_one_epoch

(self, epoch)

src/netspresso_trainer/pipelines/train.py:222

↓ 1 callersFunctiontrain_with_yaml

( data: Union[Path, str], augmentation: Union[Path, str], model: Union[Path, str], training: Union

src/netspresso_trainer/trainer_main.py:110

↓ 1 callersFunctiontxtywh2cxcywh

(top_left_x, top_left_y, width, height)

tools/open_dataset_tool/objects365.py:71

↓ 1 callersMethodunfolding

(self, feature_map: Tensor)

src/netspresso_trainer/models/backbones/experimental/mobilevit.py:117

↓ 1 callersMethoduse_l1_update

(self)

src/netspresso_trainer/losses/detection/yolo.py:36

↓ 1 callersMethoduse_l1_update

(self)

src/netspresso_trainer/losses/detection/yolox.py:38

↓ 1 callersMethodvalidate

(self)

src/netspresso_trainer/pipelines/train.py:236

↓ 1 callersFunctionvalidate_evaluation_config

(conf: DictConfig, gpus: Union[List, int])

src/netspresso_trainer/utils/engine_utils.py:222

↓ 1 callersFunctionvalidate_inference_config

(conf: DictConfig, gpus: Union[List, int])

src/netspresso_trainer/utils/engine_utils.py:241

↓ 1 callersFunctionvalidate_train_config

(conf: DictConfig)

src/netspresso_trainer/utils/engine_utils.py:200

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