|
|
| import ast |
| import itertools |
| import numpy as np |
| from typing import List |
|
|
| def solve(solve_function: str,input: List[str], expected_output: str) -> str: |
| """function used to run the solve function on input *kwargs and return the the predicted output |
| |
| :param solve_function: the function to run (the solve function below as a string) |
| :type solve_function: str |
| :param kwargs: the inputs to the solve function |
| :type kwargs: List[str] |
| """ |
| local_namespace = {} |
| exec(solve_function,local_namespace) |
| found_name, program_name = get_function_name_from_code(solve_function) |
| |
| if not found_name: |
| raise ValueError(f"Function name not found in program: {solve_function}") |
| |
| solve_fn = local_namespace.get(program_name) |
| |
| prediction = solve_fn(input) |
| |
| prediction = prediction.split() |
| expected_output = expected_output.split() |
| |
| if len(prediction) != len(expected_output): |
| raise ValueError(f"Invalid Format of prediction") |
| |
| for i in range(len(prediction)): |
| if prediction[i] != expected_output[i]: |
| return False |
| |
| return True |
|
|
| def evaluate(solve_function: str, tests_inputs: List[str], expected_outputs: str) -> float: |
| """Returns the score of the solve function we're evolving based on the tests_inputs and expected_outputs. |
| Scores are between 0 and 1, unless the program fails to run, in which case the score is -1. |
| """ |
| if solve(solve_function,tests_inputs,expected_outputs) == True: |
| return 1.0 |
| return 0.0 |
|
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|
|
| def get_function_name_from_code(code): |
| tree = ast.parse(code) |
| for node in ast.walk(tree): |
| if isinstance(node, ast.FunctionDef): |
| return True, node.name |
|
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| |
| return False, None |
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