Source code for cerebras.modelzoo.data.vision.classification.data.imagenet21k

# Copyright 2022 Cerebras Systems.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import json
import os

from PIL import Image
from torchvision.datasets import VisionDataset
from torchvision.datasets.utils import verify_str_arg

from cerebras.modelzoo.data.vision.classification.dataset_factory import (
    Processor,
)


class ImageNet21K(VisionDataset):
    def __init__(
        self,
        root: str,
        split: str = "train",
        transform=None,
        target_transform=None,
    ):
        super().__init__(
            root,
            transform=transform,
            target_transform=target_transform,
        )
        verify_str_arg(split, "split", ("train", "val"))

        database_path = os.path.join(
            self.root, f"ILSVRC2021winter_whole_map_{split}.txt"
        )
        self.database = json.load(open(database_path))

    def loader(self, path: str):
        return Image.open(path).convert("RGB")

    def __len__(self):
        return len(self.database)

    def __getitem__(self, index: int):
        filename, target = self.database[index]
        image = self.loader(os.path.join(self.root, filename))

        if self.transform is not None:
            image = self.transform(image)

        if self.target_transform is not None:
            target = self.target_transform(target)

        return image, target


class ImageNet21KProcessor(Processor):
    def __init__(self, params):
        super().__init__(params)
        self.allowable_split = ["train", "val"]
        self.num_classes = 19167

    def create_dataset(
        self, use_training_transforms: bool = True, split: str = "train"
    ):
        self.check_split_valid(split)
        transform, target_transform = self.process_transform(
            use_training_transforms
        )

        database_file = f"ILSVRC2021winter_whole_map_{split}.txt"
        if not os.path.isfile(os.path.join(self.data_dir, database_file)):
            raise RuntimeError(
                f"The database file is not present in the root directory. Check "
                "https://github.com/microsoft/Swin-Transformer/blob/main/get_started.md "
                "for more details on preparing the dataset."
            )

        dataset = ImageNet21K(
            root=self.data_dir,
            split=split,
            transform=transform,
            target_transform=target_transform,
        )

        return dataset