| """Example of a custom task with automatic discovery.""" |
|
|
| from ..base_task import BaseTask, TaskConfig |
| import re |
| from typing import List, Dict |
|
|
|
|
| class MathTask(BaseTask): |
| """A task for simple math problems.""" |
| |
| TASK_NAME = "math" |
| |
| def __init__(self, config: TaskConfig): |
| super().__init__(config) |
| |
| def _load_data(self): |
| """Generate synthetic math problems for testing.""" |
| import pandas as pd |
| import random |
| |
| random.seed(42) |
| problems = [] |
| |
| |
| for _ in range(20): |
| a, b = random.randint(1, 20), random.randint(1, 20) |
| op = random.choice(['+', '-', '*']) |
| |
| if op == '+': |
| answer = a + b |
| elif op == '-': |
| answer = a - b |
| else: |
| answer = a * b |
| |
| problems.append({ |
| self.config.input_column: f"{a} {op} {b}", |
| self.config.output_column: str(answer) |
| }) |
| |
| self.data = pd.DataFrame(problems) |
|
|
| |
| def get_icl_examples(self, num_examples: int = 10, shuffle: bool = True, seed: int = None, fresh: bool = True) -> List[Dict[str, str]]: |
| """Generate simple arithmetic examples for ICL. |
| |
| Note: `fresh` is ignored for synthetic/generated tasks (there's no stable dataset indices to track). |
| """ |
| import random |
| if seed is not None: |
| random.seed(seed) |
|
|
| examples = [] |
| for _ in range(num_examples): |
| a, b = random.randint(1, 10), random.randint(1, 10) |
| examples.append({"input": f"{a} + {b}", "output": str(a + b)}) |
|
|
| if shuffle: |
| |
| random.shuffle(examples) |
|
|
| return examples[:num_examples] |
| |
| def evaluate(self, predictions: List[str], split: str = "test", **kwargs) -> Dict[str, float]: |
| """Evaluate math predictions.""" |
| correct = 0 |
| total = len(predictions) |
| |
| if total == 0: |
| return {"accuracy": 0.0} |
| |
| |
| data_split = self.data if split == "test" else self.data |
| targets = data_split[self.config.output_column].tolist() |
| |
| if len(predictions) != len(targets): |
| raise ValueError(f"Number of predictions ({len(predictions)}) doesn't match targets ({len(targets)})") |
| |
| detailed_results = [] |
| for pred, target in zip(predictions, targets): |
| result = self.evaluate_response(pred, str(target)) |
| if result["correct"]: |
| correct += 1 |
| detailed_results.append(result) |
| |
| accuracy = correct / total |
| return { |
| "accuracy": accuracy, |
| "correct_count": correct, |
| "total_count": total, |
| "detailed_results": detailed_results |
| } |
| |
| def evaluate_response(self, response: str, target: str) -> dict: |
| """Evaluate a math response with number extraction.""" |
| |
| def extract_number(text: str) -> float: |
| """Extract the first number from text.""" |
| |
| match = re.search(r'-?\d+\.?\d*', text.strip()) |
| if match: |
| return float(match.group()) |
| return None |
| |
| response_num = extract_number(response) |
| target_num = extract_number(target) |
| |
| if response_num is None or target_num is None: |
| return { |
| "correct": False, |
| "error": "Could not extract numbers", |
| "response_extracted": response_num, |
| "target_extracted": target_num |
| } |
| |
| |
| correct = abs(response_num - target_num) < 0.001 |
| |
| return { |
| "correct": correct, |
| "response_extracted": response_num, |
| "target_extracted": target_num, |
| "original_response": response, |
| "original_target": target |
| } |
| |
| def generate_prompt(self, row: dict, demonstrations: list = None) -> str: |
| """Generate a prompt for math problems.""" |
| prompt = "Solve the following math problem:\n\n" |
| |
| if demonstrations: |
| prompt += "Here are some examples:\n" |
| for demo in demonstrations: |
| prompt += f"Problem: {demo['input']}\nAnswer: {demo['target']}\n\n" |
| prompt += "Now solve this problem:\n" |
| |
| prompt += f"Problem: {row[self.config.input_column]}\nAnswer:" |
| return prompt |
|
|
