⚡️ Speed up method HotPotQAEnv.finish by 8,058% in PR #99 (hotpotqa_lookup_fix2)

[codeflash-ai]

⚡️ This pull request contains optimizations for PR #99

If you approve this dependent PR, these changes will be merged into the original PR branch hotpotqa_lookup_fix2.

This PR will be automatically closed if the original PR is merged.

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📄 HotPotQAEnv.finish() in packages/hotpotqa/src/aviary/envs/hotpotqa/env.py

📈 Performance improved by 8,058% (80.58x faster)

⏱️ Runtime went down from 55.3 milliseconds to 677 microseconds (best of 5 runs)

Explanation and details

Here are some performance optimization techniques applied to your code.

Correctness verification

The new optimized code was tested for correctness. The results are listed below.

🔘 (none found) − ⚙️ Existing Unit Tests

✅ 23 Passed − 🌀 Generated Regression Tests

(click to show generated tests)

# imports
import pytest  # used for our unit tests
# function to test
from aviary.env import Environment
from aviary.envs.hotpotqa.env import HotPotQAEnv

# unit tests

class MockState:
    def __init__(self):
        self.done = False
        self.answer = None
        self.reward = 0.0
        self.last_action = None
        # Outputs were verified to be equal to the original implementation

def normalize_answer(answer):
    return answer.strip().lower()
    # Outputs were verified to be equal to the original implementation

def create_tool(func, name):
    return (func, name)
    # Outputs were verified to be equal to the original implementation

@pytest.fixture
def env():
    env = HotPotQAEnv(
        question="What is the capital of France?",
        correct_answer="Paris",
        correct_reward=1.0,
        incorrect_reward=0.0,
        tool_failure_reward=0.0,
        proxy=None
    )
    env.state = MockState()
    return env
    # Outputs were verified to be equal to the original implementation

def test_finish_correct_answer(env):
    # Test with the correct answer
    codeflash_output = env.finish("Paris")
    # Outputs were verified to be equal to the original implementation

def test_finish_incorrect_answer(env):
    # Test with an incorrect answer
    codeflash_output = env.finish("London")
    # Outputs were verified to be equal to the original implementation

def test_finish_no_answer(env):
    # Test with no answer (empty string)
    codeflash_output = env.finish("")
    # Outputs were verified to be equal to the original implementation

def test_finish_whitespace_answer(env):
    # Test with a whitespace answer
    codeflash_output = env.finish("   ")
    # Outputs were verified to be equal to the original implementation

def test_finish_large_answer(env):
    # Test with a very long answer string
    long_answer = "a" * 10000
    codeflash_output = env.finish(long_answer)
    # Outputs were verified to be equal to the original implementation


def test_finish_special_characters(env):
    # Test with special characters in the answer
    codeflash_output = env.finish("Paris!@#$%^&*()")
    # Outputs were verified to be equal to the original implementation

def test_finish_consistency(env):
    # Test consistency of the function
    codeflash_output = env.finish("Paris")
    codeflash_output = env.finish("Paris")
    # Outputs were verified to be equal to the original implementation
# imports
from unittest.mock import MagicMock

import pytest  # used for our unit tests
from aviary.env import Environment
from aviary.envs.hotpotqa.env import HotPotQAEnv


# Mock dependencies
def normalize_answer(answer):
    return answer.strip().lower()
    # Outputs were verified to be equal to the original implementation

def create_tool(func, name):
    return func
    # Outputs were verified to be equal to the original implementation

# Define a mock state class
class HotPotQAEnvState:
    def __init__(self):
        self.done = False
        self.answer = None
        self.reward = 0.0
        self.last_action = None
        # Outputs were verified to be equal to the original implementation

# Unit tests
@pytest.fixture
def env():
    env = HotPotQAEnv(
        question="What is the capital of France?",
        correct_answer="Paris",
        correct_reward=1.0,
        incorrect_reward=0.0,
        tool_failure_reward=0.0,
        proxy=None
    )
    env.state = HotPotQAEnvState()
    return env
    # Outputs were verified to be equal to the original implementation

def test_finish_valid_answer(env):
    # Test with a valid correct answer
    codeflash_output = env.finish("Paris")
    # Outputs were verified to be equal to the original implementation

def test_finish_invalid_answer(env):
    # Test with a valid incorrect answer
    codeflash_output = env.finish("London")
    # Outputs were verified to be equal to the original implementation

def test_finish_no_answer(env):
    # Test with no answer provided
    codeflash_output = env.finish("")
    # Outputs were verified to be equal to the original implementation

def test_finish_whitespace_answer(env):
    # Test with a whitespace answer
    codeflash_output = env.finish(" ")
    # Outputs were verified to be equal to the original implementation

def test_finish_case_insensitivity(env):
    # Test with case insensitivity
    codeflash_output = env.finish("paris")
    # Outputs were verified to be equal to the original implementation

def test_finish_special_characters(env):
    # Test with special characters
    codeflash_output = env.finish("P@ris")
    # Outputs were verified to be equal to the original implementation

def test_finish_long_answer(env):
    # Test with a long answer
    long_answer = "A" * 1000
    codeflash_output = env.finish(long_answer)
    # Outputs were verified to be equal to the original implementation

def test_finish_state_already_done(env):
    # Test when state is already done
    env.state.done = True
    codeflash_output = env.finish("Paris")
    # Outputs were verified to be equal to the original implementation

def test_finish_reward_accumulation(env):
    # Test reward accumulation
    env.state.reward = 5.0
    codeflash_output = env.finish("Paris")
    # Outputs were verified to be equal to the original implementation


def test_finish_unicode_characters(env):
    # Test with unicode characters
    codeflash_output = env.finish("Päris")
    # Outputs were verified to be equal to the original implementation

def test_finish_emoji_characters(env):
    # Test with emoji characters
    codeflash_output = env.finish("Paris😊")
    # Outputs were verified to be equal to the original implementation

def test_finish_extremely_long_input(env):
    # Test with extremely long input
    long_answer = "A" * 10**6
    codeflash_output = env.finish(long_answer)
    # Outputs were verified to be equal to the original implementation

def test_finish_special_floating_point_rewards(env):
    # Test with special floating point values for rewards
    env.correct_reward = float('nan')
    codeflash_output = env.finish("Paris")

    env.correct_reward = float('inf')
    codeflash_output = env.finish("Paris")

    env.incorrect_reward = float('-inf')
    codeflash_output = env.finish("London")
    # Outputs were verified to be equal to the original implementation

🔘 (none found) − ⏪ Replay Tests

[codeflash-ai]

This PR has been automatically closed because the original PR #99 by albertbou92 was closed.