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README.md
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---
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license: mit
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configs:
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- config_name: complete
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default: true
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path: "calibration/*.zip"
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- split: test
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path: "test/*.zip"
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-
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- config_name: no_airplane
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data_files:
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- split: train
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- "train/airplane.zip"
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- "calibration/airplane.zip"
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- "test/airplane.zip"
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-
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- config_name: no_automobile
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data_files:
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- split: train
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- "train/automobile.zip"
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- "calibration/automobile.zip"
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- "test/automobile.zip"
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-
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- config_name: no_bird
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data_files:
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- split: train
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- "train/bird.zip"
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- "calibration/bird.zip"
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- "test/bird.zip"
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-
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- config_name: no_cat
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data_files:
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- split: train
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- "train/cat.zip"
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- "calibration/cat.zip"
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- "test/cat.zip"
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-
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- config_name: no_deer
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data_files:
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- split: train
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- "train/deer.zip"
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- "calibration/deer.zip"
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- "test/deer.zip"
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-
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- config_name: no_dog
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data_files:
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- split: train
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- "train/dog.zip"
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- "calibration/dog.zip"
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- "test/dog.zip"
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-
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- config_name: no_frog
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data_files:
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- split: train
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- "train/frog.zip"
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- "calibration/frog.zip"
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- "test/frog.zip"
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-
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- config_name: no_horse
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data_files:
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- split: train
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- "train/horse.zip"
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- "calibration/horse.zip"
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- "test/horse.zip"
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-
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- config_name: no_ship
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data_files:
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- split: train
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- "train/ship.zip"
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- "calibration/ship.zip"
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- "test/ship.zip"
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-
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- config_name: no_truck
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data_files:
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- split: train
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- "train/truck.zip"
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- "calibration/truck.zip"
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- "test/truck.zip"
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-
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# From here, STUPID WORKAROUNDS for
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# https://discuss.huggingface.co/t/download-only-requested-split/165968
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- config_name: train
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from torch.utils.data import DataLoader
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dataset = load_dataset("ego-thales/cifar10", name="no_bird_calibration")
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dataset = dataset["unique_split"] # Comment
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dataloader = DataLoader(dataset.with_format("torch"), batch_size=300)
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for batch in dataloader:
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# batch["images"]: tensor with shape `(300, 3, 32, 32)` (`torch.uint8` values between 0 and 255)
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---
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pretty_name: "CIFAR10 with leftover data for calibration"
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license: mit
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language: en
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task_categories: ["image-classification"]
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size_categories: 100K<n<1M
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source_datasets: "https://www.cs.toronto.edu/~kriz/cifar.html"
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dataset_info:
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features:
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- name: image
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dtype: image
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- name: label
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dtype: int64
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- name: classname
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dtype: string
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configs:
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- config_name: complete
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default: true
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path: "calibration/*.zip"
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- split: test
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path: "test/*.zip"
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- config_name: no_airplane
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data_files:
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- split: train
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- "train/airplane.zip"
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- "calibration/airplane.zip"
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- "test/airplane.zip"
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- config_name: no_automobile
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data_files:
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- split: train
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- "train/automobile.zip"
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- "calibration/automobile.zip"
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- "test/automobile.zip"
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- config_name: no_bird
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data_files:
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- split: train
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- "train/bird.zip"
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- "calibration/bird.zip"
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- "test/bird.zip"
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- config_name: no_cat
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data_files:
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- split: train
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- "train/cat.zip"
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- "calibration/cat.zip"
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- "test/cat.zip"
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- config_name: no_deer
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data_files:
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- split: train
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- "train/deer.zip"
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- "calibration/deer.zip"
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- "test/deer.zip"
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- config_name: no_dog
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data_files:
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- split: train
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- "train/dog.zip"
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- "calibration/dog.zip"
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- "test/dog.zip"
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- config_name: no_frog
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data_files:
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- split: train
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- "train/frog.zip"
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- "calibration/frog.zip"
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- "test/frog.zip"
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- config_name: no_horse
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data_files:
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- split: train
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- "train/horse.zip"
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- "calibration/horse.zip"
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- "test/horse.zip"
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- config_name: no_ship
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data_files:
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- split: train
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- "train/ship.zip"
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- "calibration/ship.zip"
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- "test/ship.zip"
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- config_name: no_truck
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data_files:
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- split: train
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- "train/truck.zip"
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- "calibration/truck.zip"
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- "test/truck.zip"
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# From here, STUPID WORKAROUNDS for
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# https://discuss.huggingface.co/t/download-only-requested-split/165968
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- config_name: train
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from torch.utils.data import DataLoader
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dataset = load_dataset("ego-thales/cifar10", name="no_bird_calibration")
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dataset = dataset["unique_split"] # Comment out if you're in case 1. below
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dataloader = DataLoader(dataset.with_format("torch"), batch_size=300)
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for batch in dataloader:
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# batch["images"]: tensor with shape `(300, 3, 32, 32)` (`torch.uint8` values between 0 and 255)
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