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- ---
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- license: mit
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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- - split: test
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- path: data/test-*
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- dataset_info:
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- features:
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- - name: images
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- sequence: string
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- - name: problem
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- dtype: string
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- - name: answer
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 477238
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- num_examples: 3000
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- - name: test
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- num_bytes: 93920
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- num_examples: 600
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- download_size: 287256
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- dataset_size: 571158
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: mit
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: test
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+ path: data/test-*
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+ dataset_info:
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+ features:
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+ - name: images
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+ sequence: string
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+ - name: problem
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+ dtype: string
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+ - name: answer
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+ dtype: string
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+ splits:
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+ - name: train
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+ num_bytes: 477238
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+ num_examples: 3000
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+ - name: test
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+ num_bytes: 93920
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+ num_examples: 600
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+ download_size: 287256
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+ dataset_size: 571158
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+ language:
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+ - en
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+ size_categories:
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+ - 1K<n<10K
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+ ---
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+
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+ Please download [images.tar](images.tar) to your local disk and use `tar -xvf images.tar` to unarchive the image files.
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+
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+ This dataset was mixed with [hiyouga/geometry3k](https://huggingface.co/datasets/hiyouga/geometry3k) and [hiyouga/math12k](https://huggingface.co/datasets/hiyouga/math12k) using the following script.
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+
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+ ```python
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+ import os
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+ from functools import partial
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+
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+ from datasets import DatasetDict, Features, Sequence, Value, concatenate_datasets, load_dataset
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+
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+
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+ def process_sample(example: dict, index: int, split: str):
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+ if "images" in example:
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+ image = example["images"][0]
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+ image_path = os.path.join("images", split, f"{index}.png")
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+ image.save(image_path)
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+ images = [image_path]
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+ else:
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+ images = []
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+
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+ return {
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+ "images": images,
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+ "problem": example["problem"],
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+ "answer": example["answer"],
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+ }
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+
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+
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+ def main():
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+ geo3k = load_dataset("hiyouga/geometry3k")
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+ math12k = load_dataset("hiyouga/math12k")
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+ os.makedirs(os.path.join("images", "train"), exist_ok=True)
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+ os.makedirs(os.path.join("images", "test"), exist_ok=True)
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+ map_kwargs = {
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+ "with_indices": True,
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+ "num_proc": 64,
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+ "features": Features(
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+ {"images": Sequence(Value("string")), "problem": Value("string"), "answer": Value("string")}
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+ ),
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+ }
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+ geo3k_train = geo3k["train"].select(range(1500)).map(partial(process_sample, split="train"), **map_kwargs)
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+ geo3k_test = geo3k["test"].select(range(300)).map(partial(process_sample, split="test"), **map_kwargs)
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+ math12k_train = math12k["train"].select(range(1500)).map(partial(process_sample, split="train"), **map_kwargs)
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+ math12k_test = math12k["test"].select(range(300)).map(partial(process_sample, split="test"), **map_kwargs)
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+ trainset = concatenate_datasets([geo3k_train, math12k_train])
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+ testset = concatenate_datasets([geo3k_test, math12k_test])
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+ dataset = DatasetDict({"train": trainset, "test": testset})
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+ dataset.push_to_hub("hiyouga/rl-mixed-dataset")
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+
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+
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+ if __name__ == "__main__":
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+ main()
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+ ```