fsds_cleaning_env / tests /test_reward.py
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v2: curriculum scheduling, SFT pipeline, reward redesign, agent guide
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from __future__ import annotations
from fsds_cleaning_env.reward import (
FinalRewardInput,
StepRewardInput,
TOOL_ERROR_REWARD,
compute_final_reward,
compute_quality_gate_bonus,
compute_step_reward,
)
def test_step_reward_positive_improvement() -> None:
inp = StepRewardInput(quality_before=0.5, quality_after=0.7)
reward = compute_step_reward(inp)
# Delta = 0.2, minus margin 0.02 => 0.18
assert abs(reward - 0.18) < 1e-6
def test_step_reward_negative_clipped() -> None:
inp = StepRewardInput(quality_before=0.5, quality_after=0.2)
reward = compute_step_reward(inp)
# Delta = -0.3, minus margin 0.02 => -0.32, clipped to -0.15
assert abs(reward - (-0.15)) < 1e-6
def test_quality_gate_bonus() -> None:
assert compute_quality_gate_bonus(True) == 0.15
assert compute_quality_gate_bonus(False) == -0.1
def test_final_reward_combination() -> None:
inp = FinalRewardInput(
quality_score=1.0,
gate_passed=True,
required_operation_coverage=1.0,
)
reward = compute_final_reward(inp)
# 0.45 * 1.0 + 0.30 * 1.0 + 0.25 * 1.0 = 1.0
assert abs(reward - 1.0) < 1e-6
def test_tool_error_reward_constant() -> None:
assert TOOL_ERROR_REWARD < 0.0