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Add 13 new procedural datasets across 7 categories
New dataset categories: combinatorics, statistics, optimization, and formal languages. Extended existing algebra, arithmetic, probability, logic, and graphs packages with complex_advanced, linear_algebra, limits, number_theory, conditional_probability, set_operations, and job_scheduling. Each dataset includes config validation, deterministic seeding, custom scoring, curriculum support, and comprehensive unit tests (92 new tests).
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Ritvik19
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199
reasoning_gym/optimization/dynamic_programming.py
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199
reasoning_gym/optimization/dynamic_programming.py
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import random
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from dataclasses import dataclass, field
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from typing import Any, Optional
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from ..coaching import BaseCurriculum, ScalarAttributeDefinition
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from ..factory import ProceduralDataset, register_dataset
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DATASET_NAME = "dynamic_programming"
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TASK_TYPES = ("lcs", "coin_change", "lis", "edit_distance", "staircase")
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def _lcs_length(s1: str, s2: str) -> tuple[int, str]:
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m, n = len(s1), len(s2)
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dp = [[""] * (n + 1) for _ in range(m + 1)]
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for i in range(1, m + 1):
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for j in range(1, n + 1):
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if s1[i - 1] == s2[j - 1]:
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dp[i][j] = dp[i - 1][j - 1] + s1[i - 1]
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else:
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dp[i][j] = dp[i - 1][j] if len(dp[i - 1][j]) >= len(dp[i][j - 1]) else dp[i][j - 1]
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return len(dp[m][n]), dp[m][n]
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def _coin_change(coins: list[int], amount: int) -> int:
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dp = [float("inf")] * (amount + 1)
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dp[0] = 0
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for c in coins:
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for a in range(c, amount + 1):
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dp[a] = min(dp[a], dp[a - c] + 1)
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return dp[amount] if dp[amount] != float("inf") else -1
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def _lis_length(arr: list[int]) -> int:
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if not arr:
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return 0
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dp = [1] * len(arr)
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for i in range(1, len(arr)):
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for j in range(i):
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if arr[j] < arr[i]:
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dp[i] = max(dp[i], dp[j] + 1)
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return max(dp)
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def _edit_distance(s1: str, s2: str) -> int:
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m, n = len(s1), len(s2)
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dp = [[0] * (n + 1) for _ in range(m + 1)]
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for i in range(m + 1):
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dp[i][0] = i
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for j in range(n + 1):
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dp[0][j] = j
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for i in range(1, m + 1):
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for j in range(1, n + 1):
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if s1[i - 1] == s2[j - 1]:
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dp[i][j] = dp[i - 1][j - 1]
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else:
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dp[i][j] = 1 + min(dp[i - 1][j], dp[i][j - 1], dp[i - 1][j - 1])
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return dp[m][n]
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@dataclass
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class DynamicProgrammingConfig:
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min_str_len: int = 4
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max_str_len: int = 8
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min_arr_len: int = 5
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max_arr_len: int = 10
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max_staircase: int = 15
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task_types: tuple[str, ...] = TASK_TYPES
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task_weights: list[float] = field(default_factory=lambda: [0.2, 0.2, 0.2, 0.2, 0.2])
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seed: Optional[int] = None
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size: int = 500
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def validate(self) -> None:
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assert self.size > 0, "size must be positive"
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assert self.min_str_len >= 2, "min_str_len must be >= 2"
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assert self.max_str_len >= self.min_str_len, "max_str_len must be >= min_str_len"
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assert self.min_arr_len >= 3, "min_arr_len must be >= 3"
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assert self.max_arr_len >= self.min_arr_len, "max_arr_len must be >= min_arr_len"
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assert self.max_staircase >= 2, "max_staircase must be >= 2"
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assert len(self.task_types) > 0, "must have at least one task type"
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assert all(t in TASK_TYPES for t in self.task_types), f"invalid task type"
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assert len(self.task_weights) == len(self.task_types), "weights must match types"
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class DynamicProgrammingDataset(ProceduralDataset):
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def __init__(self, config: DynamicProgrammingConfig):
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super().__init__(config=config, seed=config.seed, size=config.size)
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def _make_lcs(self, rng: random.Random) -> dict:
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l1 = rng.randint(self.config.min_str_len, self.config.max_str_len)
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l2 = rng.randint(self.config.min_str_len, self.config.max_str_len)
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chars = "ABCDEFGH"
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s1 = "".join(rng.choice(chars) for _ in range(l1))
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s2 = "".join(rng.choice(chars) for _ in range(l2))
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length, _ = _lcs_length(s1, s2)
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question = (
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f"Find the length of the longest common subsequence (LCS) of '{s1}' and '{s2}'. "
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f"Give your answer as a single integer."
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)
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return {"question": question, "answer": str(length), "task_type": "lcs"}
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def _make_coin_change(self, rng: random.Random) -> dict:
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num_coins = rng.randint(2, 4)
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coins = sorted(set(rng.randint(1, 10) for _ in range(num_coins + 2)))[:num_coins]
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if 1 not in coins:
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coins = [1] + coins
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amount = rng.randint(5, 25)
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result = _coin_change(coins, amount)
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question = (
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f"What is the minimum number of coins needed to make {amount} "
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f"using coins of denominations {coins}? Each denomination can be used unlimited times. "
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f"Give your answer as a single integer."
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)
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return {"question": question, "answer": str(result), "task_type": "coin_change"}
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def _make_lis(self, rng: random.Random) -> dict:
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n = rng.randint(self.config.min_arr_len, self.config.max_arr_len)
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arr = [rng.randint(1, 50) for _ in range(n)]
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length = _lis_length(arr)
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question = (
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f"Find the length of the longest strictly increasing subsequence in {arr}. "
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f"Give your answer as a single integer."
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)
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return {"question": question, "answer": str(length), "task_type": "lis"}
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def _make_edit_distance(self, rng: random.Random) -> dict:
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l1 = rng.randint(self.config.min_str_len, self.config.max_str_len)
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l2 = rng.randint(self.config.min_str_len, self.config.max_str_len)
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chars = "abcdefgh"
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s1 = "".join(rng.choice(chars) for _ in range(l1))
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s2 = "".join(rng.choice(chars) for _ in range(l2))
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dist = _edit_distance(s1, s2)
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question = (
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f"What is the minimum edit distance (Levenshtein distance) between "
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f"'{s1}' and '{s2}'? Operations: insert, delete, or substitute a character. "
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f"Give your answer as a single integer."
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)
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return {"question": question, "answer": str(dist), "task_type": "edit_distance"}
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def _make_staircase(self, rng: random.Random) -> dict:
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n = rng.randint(3, self.config.max_staircase)
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ways = [0] * (n + 1)
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ways[0] = 1
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ways[1] = 1
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for i in range(2, n + 1):
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ways[i] = ways[i - 1] + ways[i - 2]
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question = (
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f"You are climbing a staircase with {n} steps. Each time you can climb 1 or 2 steps. "
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f"How many distinct ways can you reach the top? Give your answer as a single integer."
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)
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return {"question": question, "answer": str(ways[n]), "task_type": "staircase"}
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def __getitem__(self, idx: int) -> dict:
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rng = random.Random(self.seed + idx)
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task_type = rng.choices(self.config.task_types, weights=self.config.task_weights, k=1)[0]
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generators = {
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"lcs": self._make_lcs,
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"coin_change": self._make_coin_change,
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"lis": self._make_lis,
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"edit_distance": self._make_edit_distance,
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"staircase": self._make_staircase,
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}
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result = generators[task_type](rng)
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return {
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"question": result["question"],
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"answer": result["answer"],
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"metadata": {
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"source_dataset": DATASET_NAME,
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"source_index": idx,
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"task_type": result["task_type"],
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"difficulty": {
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"max_str_len": self.config.max_str_len,
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"max_arr_len": self.config.max_arr_len,
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},
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},
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}
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class DynamicProgrammingCurriculum(BaseCurriculum):
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def __init__(self):
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super().__init__(DynamicProgrammingCurriculum.__name__, DynamicProgrammingConfig)
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self._define_attributes(
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ScalarAttributeDefinition(
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name="max_str_len",
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field_name="max_str_len",
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levels=[5, 8, 12, 15],
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description="Maximum string length",
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),
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ScalarAttributeDefinition(
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name="max_arr_len",
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field_name="max_arr_len",
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levels=[5, 10, 15, 20],
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description="Maximum array length",
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),
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)
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register_dataset(DATASET_NAME, DynamicProgrammingDataset, DynamicProgrammingConfig, DynamicProgrammingCurriculum)
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