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127 lines
2.9 KiB
Markdown
127 lines
2.9 KiB
Markdown
---
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description: RF-DETR Lightning training API reference for RFDETRModelModule, RFDETRDataModule, build_trainer, callbacks, and training primitives.
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---
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# Training API Reference
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This page documents the training primitives that power RF-DETR. For a narrative guide with runnable examples, see [Custom Training API](../learn/train/customization.md).
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## RFDETRModelModule
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::: rfdetr.training.module_model.RFDETRModelModule
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options:
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show_source: false
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members:
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- __init__
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- on_fit_start
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- on_train_batch_start
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- transfer_batch_to_device
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- training_step
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- validation_step
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- test_step
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- predict_step
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- configure_optimizers
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- clip_gradients
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- on_load_checkpoint
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- reinitialize_detection_head
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---
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## RFDETRDataModule
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::: rfdetr.training.module_data.RFDETRDataModule
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options:
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show_source: false
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members:
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- __init__
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- setup
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- train_dataloader
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- val_dataloader
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- test_dataloader
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- class_names
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---
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## build_trainer
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::: rfdetr.training.trainer.build_trainer
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options:
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show_source: false
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---
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## Callbacks
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### RFDETREMACallback
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::: rfdetr.training.callbacks.ema.RFDETREMACallback
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options:
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show_source: false
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members:
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- __init__
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### BestModelCallback
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::: rfdetr.training.callbacks.best_model.BestModelCallback
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options:
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show_source: false
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members:
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- __init__
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### RFDETREarlyStopping
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::: rfdetr.training.callbacks.best_model.RFDETREarlyStopping
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options:
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show_source: false
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members:
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- __init__
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### DropPathCallback
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::: rfdetr.training.callbacks.drop_schedule.DropPathCallback
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options:
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show_source: false
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members:
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- __init__
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### COCOEvalCallback
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::: rfdetr.training.callbacks.coco_eval.COCOEvalCallback
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options:
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show_source: false
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members:
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- __init__
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---
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## RFDETRCli
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!!! info "CLI requires the `train` and `cli` extras"
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```bash
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pip install "rfdetr[train,cli]"
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```
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The `rfdetr` console script and its `--config` / `--print_config` flags are provided by `jsonargparse`, which is included in the `cli` extra.
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`RFDETRCli` is the command-line entry point for RF-DETR. It wraps
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`RFDETRModelModule` and `RFDETRDataModule` under a single `rfdetr` command and
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auto-generates four subcommands from the PyTorch Lightning CLI machinery:
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```bash
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rfdetr fit --config configs/rfdetr_base.yaml
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rfdetr validate --ckpt_path output/best.ckpt
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rfdetr test --ckpt_path output/best.ckpt
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rfdetr predict --ckpt_path output/best.ckpt
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```
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Both `model_config` and `train_config` are specified once; `RFDETRCli`
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automatically links them to the datamodule so you do not need to repeat the
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same arguments under `--data.*`.
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::: rfdetr.training.cli.RFDETRCli
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options:
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show_source: false
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members:
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- __init__
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