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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: 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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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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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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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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```python
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import os
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from functools import partial
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from datasets import DatasetDict, Features, Sequence, Value, concatenate_datasets, load_dataset
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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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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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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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if __name__ == "__main__":
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main()
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```
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