<filename>pl_bolts/models/self_supervised/__init__.py
"""
These models have been pre-trained using self-supervised learning. The models can also be used without pre-training
and overwritten for your own research.

Here's an example for using these as pretrained models.

.. code-block ::

    from pl_bolts.models.self_supervised import CPCV2

    images = get_imagenet_batch()

    # extract unsupervised representations
    pretrained = CPCV2(pretrained=True)
    representations = pretrained(images)

    # use these in classification or any downstream task
    classifications = classifier(representations)

"""
from pl_bolts.models.self_supervised.amdim.amdim_module import AMDIM
from pl_bolts.models.self_supervised.byol.byol_module import BYOL
from pl_bolts.models.self_supervised.cpc.cpc_module import CPCV2
from pl_bolts.models.self_supervised.evaluator import SSLEvaluator
from pl_bolts.models.self_supervised.ssl_finetuner import SSLFineTuner
from pl_bolts.models.self_supervised.moco.moco2_module import MocoV2
from pl_bolts.models.self_supervised.simclr.simclr_module import SimCLR
