chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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import json
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import sys
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from datasets import load_dataset
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from general_util.logger import get_child_logger
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logger = get_child_logger(__name__)
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sys.set_int_max_str_digits(0)
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class APPsReader:
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def __init__(self, split: str = "train", train_sub_split: str = ""):
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self.train_sub_val_ids = set(json.load(open("apps_train_sub_val_ids.json")))
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self.split = split
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self.train_sub_split = train_sub_split
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def __call__(self, file_path):
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data = load_dataset(file_path, split=self.split, trust_remote_code=True).to_list()
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logger.info(len(data))
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if self.split == "train" and self.train_sub_split:
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if self.train_sub_split == "train":
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data = [item for item in data if item["problem_id"] not in self.train_sub_val_ids]
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elif self.train_sub_split == "val":
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data = [item for item in data if item["problem_id"] in self.train_sub_val_ids]
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else:
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raise ValueError(f"Invalid train_sub_split: {self.train_sub_split} [train, val]")
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logger.info(f"Using {self.train_sub_split} split for training data")
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logger.info(len(data))
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missing_solutions = 0
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missing_test_cases = 0
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for item in data:
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if item["solutions"]:
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item["solutions"] = json.loads(item["solutions"])
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else:
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missing_solutions += 1
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if item["input_output"]:
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item["input_output"] = json.loads(item["input_output"])
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else:
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missing_test_cases += 1
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print(f"Missing solutions: {missing_solutions}")
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print(f"Missing test cases: {missing_test_cases}")
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return data
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class APPsWithFunctionName:
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def __init__(self, split: str = "train", train_sub_split: str = "", use_starter_code: bool = False):
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self.train_sub_val_ids = set(json.load(open("apps_train_sub_val_ids.json")))
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self.split = split
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self.train_sub_split = train_sub_split
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self.use_starter_code = use_starter_code
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def __call__(self, file_path):
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data = load_dataset(file_path, split=self.split, trust_remote_code=True).to_list()
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logger.info(len(data))
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if self.split == "train" and self.train_sub_split:
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if self.train_sub_split == "train":
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data = [item for item in data if item["problem_id"] not in self.train_sub_val_ids]
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elif self.train_sub_split == "val":
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data = [item for item in data if item["problem_id"] in self.train_sub_val_ids]
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else:
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raise ValueError(f"Invalid train_sub_split: {self.train_sub_split} [train, val]")
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logger.info(f"Using {self.train_sub_split} split for training data")
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logger.info(len(data))
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missing_solutions = 0
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missing_test_cases = 0
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for item in data:
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if item["solutions"]:
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item["solutions"] = json.loads(item["solutions"])
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else:
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missing_solutions += 1
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if item["input_output"]:
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item["input_output"] = json.loads(item["input_output"])
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if "fn_name" in item["input_output"]:
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item["fn_name"] = item["input_output"]["fn_name"]
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if self.use_starter_code:
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assert item["starter_code"]
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item["question"] += f"\n\n{item['starter_code']}"
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else:
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item["question"] += f"\n\nYou should name the function as `{item['fn_name']}`."
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else:
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missing_test_cases += 1
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print(f"Missing solutions: {missing_solutions}")
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print(f"Missing test cases: {missing_test_cases}")
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return data
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class APPsFlatTestCasesReader(APPsWithFunctionName):
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def __call__(self, file_path):
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data = super().__call__(file_path)
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outputs = []
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for item in data:
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if item["input_output"]:
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inputs = item["input_output"]["inputs"]
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inputs = [str(_input) for _input in inputs]
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item["test_inputs"] = inputs
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outputs.append(item)
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return outputs
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class PseudoInputsWithFunctionName:
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def __init__(self, use_starter_code: bool = False, train_sub_split: str = "train"):
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self.use_starter_code = use_starter_code
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self.train_sub_val_ids = set([f"apps-train-{x}" for x in json.load(open("apps_train_sub_val_ids.json"))])
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self.train_sub_split = train_sub_split
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def __call__(self, file_path):
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data = json.load(open(file_path, encoding="utf-8"))
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logger.info(len(data))
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if self.train_sub_split == "train":
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data = [item for item in data if item["problem_id"] not in self.train_sub_val_ids]
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elif self.train_sub_split == "val":
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data = [item for item in data if item["problem_id"] in self.train_sub_val_ids]
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else:
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raise ValueError(f"Invalid train_sub_split: {self.train_sub_split} [train, val]")
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logger.info(f"Using {self.train_sub_split} split for training data")
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logger.info(len(data))
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missing_solutions = 0
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missing_test_cases = 0
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for item in data:
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if item["input_output"]:
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if not isinstance(item["input_output"], dict):
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item["input_output"] = json.loads(item["input_output"])
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if "fn_name" in item["input_output"]:
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item["fn_name"] = item["input_output"]["fn_name"]
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if self.use_starter_code:
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# FIXME: This is a bug for synthesized data, since we didn't generate starter code.
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# We should use `fn_name` to compose simple starter_code instead.
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# See PseudoInputsWithFunctionNameFixStarterCode for the fix.
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if "starter_code" in item and item["starter_code"]:
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item["question"] += f"\n\n{item['starter_code']}"
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else:
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item["question"] += f"\n\nYou should name the function as `{item['fn_name']}`."
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else:
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missing_test_cases += 1
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print(f"Missing solutions: {missing_solutions}")
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print(f"Missing test cases: {missing_test_cases}")
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return data
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class PseudoInputsWithFunctionNameFixStarterCode:
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def __init__(self, use_starter_code: bool = False, train_sub_split: str = "train"):
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self.use_starter_code = use_starter_code
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self.train_sub_val_ids = set([f"apps-train-{x}" for x in json.load(open("apps_train_sub_val_ids.json"))])
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self.train_sub_split = train_sub_split
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def __call__(self, file_path):
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data = json.load(open(file_path, encoding="utf-8"))
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logger.info(len(data))
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if self.train_sub_split == "train":
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data = [item for item in data if item["problem_id"] not in self.train_sub_val_ids]
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elif self.train_sub_split == "val":
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data = [item for item in data if item["problem_id"] in self.train_sub_val_ids]
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else:
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raise ValueError(f"Invalid train_sub_split: {self.train_sub_split} [train, val]")
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logger.info(f"Using {self.train_sub_split} split for training data")
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logger.info(len(data))
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missing_solutions = 0
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missing_test_cases = 0
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for item in data:
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if item["input_output"]:
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if not isinstance(item["input_output"], dict):
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item["input_output"] = json.loads(item["input_output"])
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if "fn_name" in item["input_output"]:
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item["fn_name"] = item["input_output"]["fn_name"]
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if self.use_starter_code and "starter_code" in item and item["starter_code"]:
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item["question"] += f"\n\n{item['starter_code']}"
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else:
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item["question"] += f"\n\nYou should name the function as `{item['fn_name']}`."
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else:
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missing_test_cases += 1
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print(f"Missing solutions: {missing_solutions}")
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print(f"Missing test cases: {missing_test_cases}")
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return data
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