| """ |
| We use this script to create the huggingface format dataset files for the sciworld dataset. |
| NOTE: You need to install the ScienceWorld dataset first: https://github.com/allenai/ScienceWorld |
| """ |
| import json |
| import os |
| import random |
|
|
| random.seed(42) |
|
|
| task_variations = { |
| "boil": 30, |
| "melt": 30, |
| "freeze": 30, |
| "change-the-state-of-matter-of": 30, |
| "use-thermometer": 540, |
| "measure-melting-point-known-substance": 436, |
| "measure-melting-point-unknown-substance": 300, |
| "power-component": 20, |
| "power-component-renewable-vs-nonrenewable-energy": 20, |
| "test-conductivity": 900, |
| "test-conductivity-of-unknown-substances": 600, |
| "find-living-thing": 300, |
| "find-non-living-thing": 300, |
| "find-plant": 300, |
| "find-animal": 300, |
| "grow-plant": 126, |
| "grow-fruit": 126, |
| "chemistry-mix": 32, |
| "chemistry-mix-paint-secondary-color": 36, |
| "chemistry-mix-paint-tertiary-color": 36, |
| "lifespan-longest-lived": 125, |
| "lifespan-shortest-lived": 125, |
| "lifespan-longest-lived-then-shortest-lived": 125, |
| "identify-life-stages-1": 14, |
| "identify-life-stages-2": 10, |
| "inclined-plane-determine-angle": 168, |
| "inclined-plane-friction-named-surfaces": 1386, |
| "inclined-plane-friction-unnamed-surfaces": 162, |
| "mendelian-genetics-known-plant": 120, |
| "mendelian-genetics-unknown-plant": 480, |
| } |
|
|
|
|
| def create_dataset_files(output_dir, train_task_names, test_task_names, jar_path, percentage=0.6): |
| |
| os.makedirs(output_dir, exist_ok=True) |
|
|
| train_data = [] |
| test_data = [] |
|
|
| for task_name in train_task_names: |
| total_var = task_variations[task_name] |
| for i in range(int(total_var * percentage)): |
| task_config = { |
| "task_name": task_name, |
| "var_num": i, |
| "jar_path": jar_path, |
| } |
| task_desc = json.dumps(task_config) |
| train_data.append({"task_desc": task_desc, "targe": ""}) |
|
|
| random.shuffle(train_data) |
|
|
| for task_name in test_task_names: |
| total_var = task_variations[task_name] |
| for i in range(int(total_var * percentage)): |
| task_config = { |
| "task_name": task_name, |
| "var_num": i, |
| "jar_path": jar_path, |
| } |
| task_desc = json.dumps(task_config) |
| test_data.append({"task_desc": task_desc, "targe": ""}) |
|
|
| random.shuffle(test_data) |
|
|
| |
| dataset_dict = {"train": train_data, "test": test_data} |
|
|
| for split, data in dataset_dict.items(): |
| output_file = os.path.join(output_dir, f"{split}.jsonl") |
| with open(output_file, "w") as f: |
| for item in data: |
| f.write(json.dumps(item) + "\n") |
|
|
| |
| dataset_info = { |
| "citation": "", |
| "description": "Custom dataset", |
| "splits": { |
| "train": {"name": "train", "num_examples": len(train_data)}, |
| "test": {"name": "test", "num_examples": len(test_data)}, |
| }, |
| } |
|
|
| with open(os.path.join(output_dir, "dataset_dict.json"), "w") as f: |
| json.dump(dataset_info, f, indent=2) |
|
|
|
|
| if __name__ == "__main__": |
| |
| jar_path = "/your/path/ScienceWorld/scienceworld/scienceworld.jar" |
| |
| if not os.path.exists(jar_path): |
| raise FileNotFoundError( |
| f"JAR file not found at {jar_path}, please set the jar path mannually." |
| ) |
|
|
| current_file_dir = os.path.dirname(os.path.abspath(__file__)) |
| output_dir = f"{current_file_dir}/sciworld_data" |
| train_task_names = [ |
| "boil", |
| "melt", |
| "change-the-state-of-matter-of", |
| "use-thermometer", |
| "measure-melting-point-known-substance", |
| "power-component", |
| "test-conductivity", |
| "find-living-thing", |
| "find-plant", |
| "grow-plant", |
| "chemistry-mix", |
| "chemistry-mix-paint-secondary-color", |
| "lifespan-shortest-lived", |
| "identify-life-stages-2", |
| "inclined-plane-determine-angle", |
| "inclined-plane-friction-named-surfaces", |
| "mendelian-genetics-known-plant", |
| ] |
| test_task_names = list(task_variations.keys() - set(train_task_names)) |
| create_dataset_files(output_dir, train_task_names, test_task_names, jar_path, percentage=0.5) |
|
|
