benchmark/supervised/generate_datasets.py [41:53]:
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        x = []
        y = []
        for split in splits:
            ds, ds_info = tfds.load(dataset_name, split=split, with_info=True)

            if x_key not in ds_info.features:
                raise ValueError("x_key not found - available features are:",
                                 str(ds_info.features.keys()))
            if y_key not in ds_info.features:
                raise ValueError("y_key not found - available features are:",
                                 str(ds_info.features.keys()))

            pb = tqdm(total=ds_info.splits[split].num_examples,
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tensorflow_similarity/samplers/tfdataset_samplers.py [116:128]:
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        x = []
        y = []
        for split in splits:
            ds, ds_info = tfds.load(dataset_name, split=split, with_info=True)

            if x_key not in ds_info.features:
                raise ValueError("x_key not found - available features are:",
                                 str(ds_info.features.keys()))
            if y_key not in ds_info.features:
                raise ValueError("y_key not found - available features are:",
                                 str(ds_info.features.keys()))

            pb = tqdm(total=ds_info.splits[split].num_examples,
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