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on
CPU Upgrade
import json | |
import os | |
import string | |
from src.logger import get_logger | |
WARMUP_DATASET_SIZE = 100 | |
DATASET_SIZE = 120 | |
MIN_INPUT_LENGTH = 2 | |
MAX_INPUT_LENGTH = 20 | |
MIN_SUBMISSION_SIZE = 1 | |
MAX_SUBMISSION_SIZE = 1024 * 1024 * 120 # 120 MB. | |
MAX_SINGLE_SUBMISSION_SIZE = 1024 * 1024 # 1MB. | |
MAX_SUBMISSION_LINES = DATASET_SIZE + 1 # Allow empty line. | |
logger = get_logger(__name__) | |
def is_valid( | |
s: str, | |
min_length: int = MIN_INPUT_LENGTH, | |
max_length: int = MAX_INPUT_LENGTH, | |
) -> bool: | |
""" | |
@brief Checks whether the given string is valid. | |
@param s The string to validate. | |
@return True iff all characters are in [a-zA-Z0-9], spaces, or '.' and '-', and the length if between | |
min length and max length. | |
""" | |
characters = [c for c in s] # Not using the length from len(.) as that includes unicode characters. | |
if len(characters) < min_length or len(characters) > max_length: | |
return False | |
# Very important: We delimit using underscores. So these _CANNOT_ be allowed in sanitised strings. | |
ALLOWED = ( | |
[c for c in string.ascii_lowercase] | |
+ [c for c in string.ascii_uppercase] | |
+ [c for c in string.digits] | |
+ [" ", ".", "-"] | |
) | |
for c in s: | |
if c not in ALLOWED: | |
return False | |
return True | |
def is_submission_file_valid( | |
submission_path: str, | |
is_warmup_dataset: bool, | |
) -> bool: | |
""" | |
@brief Checks whether the given submission file is valid. | |
@param submission_path The path to the submission file. | |
@param is_warmup_dataset Whether we are working on the regular or the warmup dataset. | |
@return True iff the file is within the size constraints, a JSONL, and every line is no longer than | |
the fixed maximum bound. | |
""" | |
if not os.path.exists(submission_path): | |
logger.warning(f"Could not find submission file {submission_path=}") | |
return False | |
submission_size = os.stat(submission_path).st_size | |
if submission_size < MIN_SUBMISSION_SIZE or submission_size > MAX_SUBMISSION_SIZE: | |
logger.warning(f"Submission size was {submission_size}, exceeding [{MIN_SUBMISSION_SIZE, MAX_SUBMISSION_SIZE}]") | |
return False | |
with open(submission_path, "r") as f: | |
# Not using readlines() to avoid consuming a large buffer at once. | |
n_lines = 0 | |
seen_ids = set() | |
while len(line := f.readline(MAX_SINGLE_SUBMISSION_SIZE)) > 0: | |
n_lines += 1 | |
if n_lines > MAX_SUBMISSION_LINES: | |
logger.warning(f"Got submission with more than {MAX_SUBMISSION_LINES} lines") | |
return False | |
if not (line.startswith("{") and (line.endswith("}") or line.endswith("}\n"))): | |
logger.warning("Submission has line that does not appear to be a JSONL") | |
return False | |
d = json.loads(line) | |
if set(d.keys()) != set(["problem_id", "solution"]): | |
logger.warning("Found unexpected keys") | |
return False | |
if not ((type(d["problem_id"]) is str or type(d["problem_id"]) is int) and type(d["solution"] is str)): | |
logger.warning("Found unexpected types") | |
return False | |
try: | |
problem_id = int(d["problem_id"]) | |
except Exception: | |
logger.warning("Could not convert problem ID to int") | |
return False | |
if is_warmup_dataset: | |
if problem_id < DATASET_SIZE or problem_id >= DATASET_SIZE + WARMUP_DATASET_SIZE: | |
logger.warning(f"Problem ID {problem_id} is beyond allowed bounds") | |
return False | |
else: | |
if problem_id < 0 or problem_id >= DATASET_SIZE: | |
logger.warning(f"Problem ID {problem_id} is beyond allowed bounds") | |
return False | |
if problem_id in seen_ids: | |
logger.warning(f"Got duplicate submission -- ID {problem_id} appears twice") | |
return False # Duplicate submission. | |
seen_ids.add(problem_id) | |
return True | |