Train
=====


.. autoclass:: netspresso.trainer.trainer::Trainer
   :members:
   :show-inheritance:
   :inherited-members:


Example
-------

Train
~~~~~

.. code-block:: python

   from netspresso import NetsPresso
   from netspresso.enums import Task
   from netspresso.trainer.augmentations import Resize
   from netspresso.trainer.optimizers import AdamW
   from netspresso.trainer.schedulers import CosineAnnealingWarmRestartsWithCustomWarmUp


   netspresso = NetsPresso(email="YOUR_EMAIL", password="YOUR_PASSWORD")

   # 1. Declare trainer
   trainer = netspresso.trainer(task=Task.OBJECT_DETECTION)

   # 2. Set config for training
   # 2-1. Data
   trainer.set_dataset_config(
      name="traffic_sign_config_example",
      root_path="/root/traffic-sign",
      train_image="images/train",
      train_label="labels/train",
      valid_image="images/valid",
      valid_label="labels/valid",
      id_mapping=["prohibitory", "danger", "mandatory", "other"],
   )

   # 2-2. Model
   print(trainer.available_models)  # ['EfficientFormer', 'YOLOX-S', ...]
   trainer.set_model_config(model_name="YOLOX-S", img_size=512)

   # 2-3. Augmentation
   trainer.set_augmentation_config(
      train_transforms=[Resize()],
      inference_transforms=[Resize()],
   )

   # 2-4. Training
   optimizer = AdamW(lr=6e-3)
   scheduler = CosineAnnealingWarmRestartsWithCustomWarmUp(warmup_epochs=10)
   trainer.set_training_config(
      epochs=40,
      batch_size=16,
      optimizer=optimizer,
      scheduler=scheduler,
   )

   # 3. Train
   training_result = trainer.train(gpus="0, 1", project_name="project_sample")


Retrain
~~~~~~~

.. code-block:: python

   from netspresso import NetsPresso
   from netspresso.trainer.optimizers import AdamW


   netspresso = NetsPresso(email="YOUR_EMAIL", password="YOUR_PASSWORD")

   # 1. Declare trainer
   trainer = netspresso.trainer(yaml_path="./temp/hparams.yaml")

   # 2. Set config for retraining
   # 2-1. FX Model
   trainer.set_fx_model(fx_model_path="./temp/FX_MODEL_PATH.pt")

   # 2-2. Training
   trainer.set_training_config(
      epochs=30,
      batch_size=16,
      optimizer=AdamW(lr=6e-3),
   )

   # 3. Train
   trainer.train(gpus="0, 1", project_name="project_retrain_sample")