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⚡️ Speed up function gfo2hyper by 15% #105

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📄 15% (0.15x) speedup for gfo2hyper in src/hyperactive/optimizers/constraint.py

⏱️ Runtime : 243 microseconds 211 microseconds (best of 148 runs)

📝 Explanation and details

To optimize the given program for better performance, we will focus on refining the loop inside the gfo2hyper function. One potential optimization is to avoid calling search_space.keys() repeatedly and to directly iterate over search_space.items(). This can help save time, especially for larger dictionaries.

Changes Made.

  1. Changed for _, key in enumerate(search_space.keys()): to for key, values in search_space.items(): to directly access keys and associated values.

Reason for Changes.

  • Accessing both key and value directly in the same loop reduces time complexity and avoids extra dictionary lookups, leading to performance improvements.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 12 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests Details
import pytest  # used for our unit tests
from hyperactive.optimizers.constraint import gfo2hyper

# unit tests

# Basic Functionality Tests
def test_simple_case():
    search_space = {'a': [1, 2, 3], 'b': [4, 5, 6]}
    para = {'a': '1', 'b': '2'}
    expected = {'a': 2, 'b': 6}
    codeflash_output = gfo2hyper(search_space, para)

def test_single_key():
    search_space = {'a': [1, 2, 3]}
    para = {'a': '0'}
    expected = {'a': 1}
    codeflash_output = gfo2hyper(search_space, para)

# Edge Case Tests


def test_non_existent_key_in_search_space():
    search_space = {'a': [1, 2, 3]}
    para = {'b': '0'}
    with pytest.raises(KeyError):
        gfo2hyper(search_space, para)

# Invalid Indices Tests
def test_non_integer_index():
    search_space = {'a': [1, 2, 3]}
    para = {'a': 'x'}
    with pytest.raises(ValueError):
        gfo2hyper(search_space, para)

def test_out_of_bound_index():
    search_space = {'a': [1, 2, 3]}
    para = {'a': '5'}
    with pytest.raises(IndexError):
        gfo2hyper(search_space, para)


def test_multiple_keys_with_mixed_indices():
    search_space = {'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9]}
    para = {'a': '2', 'b': '1', 'c': '0'}
    expected = {'a': 3, 'b': 5, 'c': 7}
    codeflash_output = gfo2hyper(search_space, para)

def test_nested_lists():
    search_space = {'a': [[1, 2], [3, 4]], 'b': [[5, 6], [7, 8]]}
    para = {'a': '1', 'b': '0'}
    expected = {'a': [3, 4], 'b': [5, 6]}
    codeflash_output = gfo2hyper(search_space, para)

# Large Scale Test Cases
def test_large_search_space_and_para():
    search_space = {'key' + str(i): list(range(100)) for i in range(1000)}
    para = {'key' + str(i): str(i % 100) for i in range(1000)}
    expected = {'key' + str(i): i % 100 for i in range(1000)}
    codeflash_output = gfo2hyper(search_space, para)

# Performance and Scalability Tests

def test_high_number_of_keys():
    search_space = {'key' + str(i): [i] for i in range(1000)}
    para = {'key' + str(i): '0' for i in range(1000)}
    expected = {'key' + str(i): i for i in range(1000)}
    codeflash_output = gfo2hyper(search_space, para)

# Special Cases Tests


import pytest  # used for our unit tests
from hyperactive.optimizers.constraint import gfo2hyper

# unit tests

# Basic Functionality

To edit these changes git checkout codeflash/optimize-gfo2hyper-m8ft3mp4 and push.

Codeflash

To optimize the given program for better performance, we will focus on refining the loop inside the `gfo2hyper` function. One potential optimization is to avoid calling `search_space.keys()` repeatedly and to directly iterate over `search_space.items()`. This can help save time, especially for larger dictionaries.



### Changes Made.
1. Changed `for _, key in enumerate(search_space.keys()):` to `for key, values in search_space.items():` to directly access keys and associated values.

### Reason for Changes.
- Accessing both key and value directly in the same loop reduces time complexity and avoids extra dictionary lookups, leading to performance improvements.
@misrasaurabh1
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@23pointsNorth what code formatting settings does this repo use? I could not find one so just defaulted to black but that sometimes causes some differences.

@SimonBlanke
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@23pointsNorth what code formatting settings does this repo use? I could not find one so just defaulted to black but that sometimes causes some differences.

I always autoformat my files to 'black' on save. But there might be some differences in older files.

@@ -5,9 +5,9 @@

def gfo2hyper(search_space, para):
values_dict = {}
for _, key in enumerate(search_space.keys()):
for key, values in search_space.items():
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This requires the items-method in this dict base-class to work.

@fkiraly
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fkiraly commented Mar 25, 2025

@misrasaurabh1, how did you measure the speed-up if the function actually breaks?

Is this PR completely AI generated and you did not even check whether it runs, or how should I understand this?

@misrasaurabh1
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Hi @fkiraly , the speed up is measured by codeflash using the generated test cases that are attached in the PR description. Looking at the code it was hard to know what input type it was going to get so it made an assumption that it would get a dictionary, and did the correctness and performance checks.
I manually reviewed the optimization and since it looked good, i opened the PR here. But its true that the benchmark hasn't been run again with the modified code, but i believe that the performance gains should still hold

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3 participants