⚡️ Speed up function add_area_dims by 56%

[aseembits93]

📄 56% (0.56x) speedup for add_area_dims in comfy/samplers.py

⏱️ Runtime : 111 milliseconds → 71.2 milliseconds (best of 121 runs)

📝 Explanation and details

To optimize the given function, we can avoid repeated slicing and concatenations within the loop, which can be computationally expensive, especially for large lists. Instead, we can split the list just once and construct the final result using list operations more efficiently.

Here's the optimized version of the program.

Optimizations.

1. Calculate the current number of dimensions (current_dims) once before the loop.
2. Within the loop, use the extend() method to append parts of the area list efficiently rather than using concatenation (+) multiple times.
3. Use a single list construction operation to build the new area list in-place.

This avoids the repeated creation of intermediary lists and makes the loop more efficient.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 24 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests Details

from __future__ import annotations

# imports
import pytest  # used for our unit tests
from comfy.samplers import add_area_dims

# unit tests

# Basic Functionality
def test_basic_functionality():
    codeflash_output = add_area_dims([1, 2, 3, 4], 2)
    codeflash_output = add_area_dims([1, 2, 3, 4], 3)
    codeflash_output = add_area_dims([], 1)
    codeflash_output = add_area_dims([], 3)

# Edge Cases
def test_single_element_list():
    codeflash_output = add_area_dims([1], 1)
    codeflash_output = add_area_dims([1], 2)

def test_odd_number_of_elements():
    codeflash_output = add_area_dims([1, 2, 3], 2)
    codeflash_output = add_area_dims([1, 2, 3, 4, 5], 3)

def test_negative_dimensions():
    codeflash_output = add_area_dims([1, 2, 3, 4], -1)
    codeflash_output = add_area_dims([1, 2, 3, 4], -5)

def test_zero_dimensions():
    codeflash_output = add_area_dims([1, 2, 3, 4], 0)

# Large Scale Test Cases
def test_large_list():
    large_list = list(range(1000))
    codeflash_output = add_area_dims(large_list, 10); result = codeflash_output

def test_very_high_dimensions():
    codeflash_output = add_area_dims([1, 2, 3, 4], 100); result = codeflash_output

def test_large_list_high_dims():
    large_list = list(range(1000))
    codeflash_output = add_area_dims(large_list, 50); result = codeflash_output

# Non-Integer Elements in Area List
def test_mixed_types():
    codeflash_output = add_area_dims([1, 'a', 3.5, True], 2)
    codeflash_output = add_area_dims([None, 2, 'test', 4.5], 3)

# Non-Integer Dimensions

def test_string_dimensions():
    with pytest.raises(TypeError):
        add_area_dims([1, 2, 3, 4], "3")
    with pytest.raises(TypeError):
        add_area_dims([1, 2, 3, 4], "two")

# Special Values in Area List
def test_special_integers():
    codeflash_output = add_area_dims([2147483648, 0, -2147483648], 2)
    codeflash_output = add_area_dims([0, 0, 0, 0], 3)

def test_empty_strings_and_none():
    codeflash_output = add_area_dims(['', '', '', ''], 2)
    codeflash_output = add_area_dims([None, None, None, None], 3)

# Performance and Scalability
def test_very_large_list():
    large_list = list(range(1000))
    codeflash_output = add_area_dims(large_list, 1000); result = codeflash_output

def test_very_large_list_high_dims():
    large_list = list(range(1000))
    codeflash_output = add_area_dims(large_list, 5000); result = codeflash_output
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-add_area_dims-m9rsmkva and push.