# Path: selfsup/multi/loaders/loader.py
# class Loader:
#     def __init__(self, batch_size=16, num_threads=5):
#         self._batch_size = batch_size
#         self._num_threads = num_threads
# 
#     def batch(self):
#         raise NotImplemented('Cannot use base class')
# 
#     def start(self, sess):
#         pass


from .loader import Loader
import selfsup.datasets
from __future__ import division, print_function, absolute_import


class UnlabeledImagesLoader(Loader):
    def __init__(self, path, batch_size, num_threads=5, input_size=224, resize_if_small=False,
            root_path=None):
        self._path = path
        self._batch_size = batch_size
        self._num_threads = num_threads
        self._input_size = input_size
        self._resize_if_small = resize_if_small
        self._root_path = root_path

    def batch(self):
        x, imgshape, imgname = selfsup.datasets.unlabeled_batching(
                self._path,
                batch_size=self._batch_size,
                num_threads=self._num_threads,
                input_size=self._input_size,

# Path: selfsup/multi/loaders/loader.py
# class Loader:
#     def __init__(self, batch_size=16, num_threads=5):
#         self._batch_size = batch_size
#         self._num_threads = num_threads
# 
#     def batch(self):
#         raise NotImplemented('Cannot use base class')
# 
#     def start(self, sess):
#         pass


# Path: selfsup/multi/loaders/unlabeled_images.py
from .loader import Loader
import selfsup.datasets

from __future__ import division, print_function, absolute_import


class UnlabeledImagesLoader(Loader):
    def __init__(self, path, batch_size, num_threads=5, input_size=224, resize_if_small=False,
            root_path=None):
        self._path = path
        self._batch_size = batch_size
        self._num_threads = num_threads
        self._input_size = input_size
        self._resize_if_small = resize_if_small
        self._root_path = root_path

    def batch(self):
        x, imgshape, imgname = selfsup.datasets.unlabeled_batching(
                self._path,
                batch_size=self._batch_size,
                num_threads=self._num_threads,
                input_size=self._input_size,

                resize_if_small=self._resize_if_small,