⚡️ Speed up function get_new_h_w by 38%

[codeflash-ai]

📄 38% (0.38x) speedup for get_new_h_w in src/diffusers/pipelines/kandinsky/pipeline_kandinsky.py

⏱️ Runtime : 44.4 microseconds → 32.3 microseconds (best of 486 runs)

📝 Explanation and details

Here is an optimized version of the provided program.
Optimization rationale:

• The expression scale_factor**2 is computed multiple times. Caching this value in a local variable improves performance.
• Conditional increment can be streamlined by using integer division with rounding up, i.e., math.ceil. As math.ceil(x / y) is equivalent to -(-x // y), this avoids an explicit import and is faster.
• The core loop is streamlined and memory accesses minimized.

All output and logic remain unchanged.

Notes:

• The logic for "rounding up" is preserved and fully equivalent to the original, just more efficient.
• No function signature or return values are changed.
• The division and multiplication operations are reduced.
• This will run faster especially for larger and more frequent calls.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 59 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 src.diffusers.pipelines.kandinsky.pipeline_kandinsky import get_new_h_w

# unit tests

# -------------------------
# Basic Test Cases
# -------------------------

def test_basic_exact_multiple():
    # Both h and w are exact multiples of scale_factor**2 (64)
    codeflash_output = get_new_h_w(128, 256, scale_factor=8)
    codeflash_output = get_new_h_w(64, 64, scale_factor=8)
    codeflash_output = get_new_h_w(256, 512, scale_factor=16)

def test_basic_non_multiple():
    # h and w are not multiples of scale_factor**2 (64)
    # h=130, w=130, scale_factor=8
    # new_h = 130//64 = 2, 130%64=2, so +1 = 3, 3*8=24
    # new_w = 3*8=24
    codeflash_output = get_new_h_w(130, 130, scale_factor=8)
    # h=65, w=127, scale_factor=8
    # 65//64=1, 65%64=1, +1=2, 2*8=16
    # 127//64=1, 127%64=63, +1=2, 2*8=16
    codeflash_output = get_new_h_w(65, 127, scale_factor=8)

def test_basic_mixed_multiple_and_non_multiple():
    # h is multiple, w is not
    codeflash_output = get_new_h_w(128, 130, scale_factor=8)
    # h is not multiple, w is
    codeflash_output = get_new_h_w(130, 128, scale_factor=8)

def test_basic_scale_factor_1():
    # scale_factor=1, should return h and w unchanged
    codeflash_output = get_new_h_w(10, 20, scale_factor=1)
    codeflash_output = get_new_h_w(0, 0, scale_factor=1)
    codeflash_output = get_new_h_w(100, 100, scale_factor=1)

def test_basic_scale_factor_2():
    # scale_factor=2, scale_factor**2=4
    # h=5, w=9
    # 5//4=1, 5%4=1, +1=2, 2*2=4
    # 9//4=2, 9%4=1, +1=3, 3*2=6
    codeflash_output = get_new_h_w(5, 9, scale_factor=2)
    # h=8, w=8, both exact multiples
    codeflash_output = get_new_h_w(8, 8, scale_factor=2)

# -------------------------
# Edge Test Cases
# -------------------------

def test_edge_zero_dimensions():
    # h or w is zero
    codeflash_output = get_new_h_w(0, 0, scale_factor=8)
    codeflash_output = get_new_h_w(0, 10, scale_factor=8)
    codeflash_output = get_new_h_w(10, 0, scale_factor=8)

def test_edge_one_dimension():
    # h or w is one
    # scale_factor=8, scale_factor**2=64
    # 1//64=0, 1%64=1, +1=1, 1*8=8
    codeflash_output = get_new_h_w(1, 1, scale_factor=8)
    codeflash_output = get_new_h_w(64, 1, scale_factor=8)
    codeflash_output = get_new_h_w(1, 64, scale_factor=8)

def test_edge_smallest_nonzero():
    # h and w just below scale_factor**2
    # scale_factor=8, scale_factor**2=64
    codeflash_output = get_new_h_w(63, 63, scale_factor=8)
    # h and w just above scale_factor**2
    codeflash_output = get_new_h_w(65, 65, scale_factor=8)

def test_edge_large_scale_factor():
    # Large scale_factor, small h/w
    codeflash_output = get_new_h_w(10, 10, scale_factor=100)
    # Large scale_factor, h/w exactly scale_factor**2
    codeflash_output = get_new_h_w(10000, 10000, scale_factor=100)
    # Large scale_factor, h/w just above scale_factor**2
    codeflash_output = get_new_h_w(10001, 10001, scale_factor=100)

def test_edge_negative_inputs():
    # Negative h or w should still be handled, but the logic will produce negative or zero outputs
    # -1//64 = -1, -1%64=63, so +1=0, 0*8=0
    codeflash_output = get_new_h_w(-1, -1, scale_factor=8)
    # Negative h, positive w
    codeflash_output = get_new_h_w(-1, 64, scale_factor=8)
    # Positive h, negative w
    codeflash_output = get_new_h_w(64, -1, scale_factor=8)

def test_edge_scale_factor_zero():
    # scale_factor=0 should raise ZeroDivisionError
    with pytest.raises(ZeroDivisionError):
        get_new_h_w(10, 10, scale_factor=0)

def test_edge_scale_factor_negative():
    # Negative scale_factor, test that the function does not crash and returns correct result
    # scale_factor=-2, scale_factor**2=4
    # 5//4=1, 5%4=1, +1=2, 2*-2=-4
    # 9//4=2, 9%4=1, +1=3, 3*-2=-6
    codeflash_output = get_new_h_w(5, 9, scale_factor=-2)


def test_large_basic():
    # Large h and w, exact multiples
    # scale_factor=8, scale_factor**2=64
    # h=64000, w=64000, 64000//64=1000, 1000*8=8000
    codeflash_output = get_new_h_w(64000, 64000, scale_factor=8)

def test_large_non_multiple():
    # Large h and w, not exact multiples
    # h=64001, w=63999
    # 64001//64=1000, 64001%64=1, +1=1001, 1001*8=8008
    # 63999//64=999, 63999%64=63, +1=1000, 1000*8=8000
    codeflash_output = get_new_h_w(64001, 63999, scale_factor=8)

def test_large_scale_factor():
    # Large scale_factor, large h/w
    # scale_factor=32, scale_factor**2=1024
    # h=102400, w=204800
    # 102400//1024=100, 102400%1024=0, so 100*32=3200
    # 204800//1024=200, 204800%1024=0, so 200*32=6400
    codeflash_output = get_new_h_w(102400, 204800, scale_factor=32)

def test_large_mixed():
    # Large h, small w
    codeflash_output = get_new_h_w(999999, 17, scale_factor=8)
    # Small h, large w
    codeflash_output = get_new_h_w(17, 999999, scale_factor=8)

def test_large_varied_scale_factors():
    # Varying scale_factor with large h/w
    for sf in [2, 4, 8, 16]:
        h = 800 * sf * sf + 13
        w = 600 * sf * sf + 7
        # new_h = (h//sf**2 + (1 if h%sf**2!=0 else 0)) * sf
        expected_h = ((h // (sf**2)) + (1 if h % (sf**2) != 0 else 0)) * sf
        expected_w = ((w // (sf**2)) + (1 if w % (sf**2) != 0 else 0)) * sf
        codeflash_output = get_new_h_w(h, w, scale_factor=sf)

# -------------------------
# Mutation-resistance / regression
# -------------------------

def test_mutation_resistance_off_by_one():
    # If the "+1" logic is omitted, the result will be wrong
    # h=65, w=65, scale_factor=8, scale_factor**2=64
    # 65//64=1, 65%64=1, so +1=2, 2*8=16
    # If +1 is omitted, it would be 1*8=8 (wrong)
    codeflash_output = get_new_h_w(65, 65, scale_factor=8)

def test_mutation_resistance_wrong_power():
    # If scale_factor is not squared, result will be wrong
    # h=256, w=256, scale_factor=8, scale_factor**2=64
    # 256//64=4, 256%64=0, 4*8=32
    codeflash_output = get_new_h_w(256, 256, scale_factor=8)
    # If scale_factor is not squared, it would be 256//8=32, 32*8=256 (wrong)

def test_mutation_resistance_wrong_return():
    # If the function returned (new_h, new_w) instead of (new_h*scale_factor, new_w*scale_factor)
    # The results would be off
    # h=130, w=130, scale_factor=8, scale_factor**2=64
    # 130//64=2, 130%64=2, +1=3, 3*8=24
    codeflash_output = get_new_h_w(130, 130, scale_factor=8)
    # If (3,3) is returned, it's wrong
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import pytest  # used for our unit tests
from src.diffusers.pipelines.kandinsky.pipeline_kandinsky import get_new_h_w

# unit tests

# -------------------
# Basic Test Cases
# -------------------

def test_exact_divisible():
    # Both h and w are exactly divisible by scale_factor**2
    h, w, scale = 64, 64, 8
    # scale_factor**2 = 64, so new_h = 1, new_w = 1, output = (8, 8)
    codeflash_output = get_new_h_w(h, w, scale)

def test_not_divisible():
    # h and w not exactly divisible by scale_factor**2
    h, w, scale = 65, 66, 8
    # h//64=1, h%64=1, so new_h=2, output_h=16
    # w//64=1, w%64=2, so new_w=2, output_w=16
    codeflash_output = get_new_h_w(h, w, scale)

def test_one_dimension_divisible():
    # Only h is divisible, w is not
    h, w, scale = 128, 130, 8
    # h//64=2, h%64=0, new_h=2, output_h=16
    # w//64=2, w%64=2, new_w=3, output_w=24
    codeflash_output = get_new_h_w(h, w, scale)

def test_both_zero():
    # Both h and w are zero
    h, w, scale = 0, 0, 8
    # 0//64=0, 0%64=0, so new_h=0, new_w=0, output=(0,0)
    codeflash_output = get_new_h_w(h, w, scale)

def test_scale_factor_default():
    # Use default scale_factor=8
    h, w = 100, 200
    # scale_factor**2=64
    # h//64=1, h%64=36, new_h=2, output_h=16
    # w//64=3, w%64=8, new_w=4, output_w=32
    codeflash_output = get_new_h_w(h, w)

# -------------------
# Edge Test Cases
# -------------------

def test_minimum_positive():
    # Minimum positive h and w, scale_factor=1
    h, w, scale = 1, 1, 1
    # scale_factor**2=1
    # h//1=1, h%1=0, new_h=1, output_h=1
    # w//1=1, w%1=0, new_w=1, output_w=1
    codeflash_output = get_new_h_w(h, w, scale)

def test_zero_one_dimension():
    # h=0, w>0
    h, w, scale = 0, 10, 2
    # scale_factor**2=4
    # h//4=0, h%4=0, new_h=0, output_h=0
    # w//4=2, w%4=2, new_w=3, output_w=6
    codeflash_output = get_new_h_w(h, w, scale)

def test_large_scale_factor():
    # scale_factor much larger than h and w
    h, w, scale = 10, 10, 100
    # scale_factor**2=10000
    # h//10000=0, h%10000=10, new_h=1, output_h=100
    # w//10000=0, w%10000=10, new_w=1, output_w=100
    codeflash_output = get_new_h_w(h, w, scale)

def test_negative_dimensions():
    # Negative h and w should still work with integer division
    h, w, scale = -10, -20, 2
    # scale_factor**2=4
    # h//4=-3, h%4=2, so new_h=-2, output_h=-4
    # w//4=-5, w%4=0, so new_w=-5, output_w=-10
    codeflash_output = get_new_h_w(h, w, scale)

def test_scale_factor_one():
    # scale_factor=1, should return (h, w)
    h, w, scale = 123, 456, 1
    # scale_factor**2=1
    # h//1=123, h%1=0, new_h=123, output_h=123
    # w//1=456, w%1=0, new_w=456, output_w=456
    codeflash_output = get_new_h_w(h, w, scale)

def test_large_prime_numbers():
    # Large prime numbers for h, w, scale_factor=7
    h, w, scale = 101, 103, 7
    # scale_factor**2=49
    # h//49=2, h%49=3, new_h=3, output_h=21
    # w//49=2, w%49=5, new_w=3, output_w=21
    codeflash_output = get_new_h_w(h, w, scale)

def test_scale_factor_zero():
    # scale_factor=0 should raise ZeroDivisionError
    with pytest.raises(ZeroDivisionError):
        get_new_h_w(10, 10, 0)


def test_large_inputs_divisible():
    # Large h and w, both divisible by scale_factor**2
    h, w, scale = 1024, 2048, 16
    # scale_factor**2=256
    # h//256=4, h%256=0, new_h=4, output_h=64
    # w//256=8, w%256=0, new_w=8, output_w=128
    codeflash_output = get_new_h_w(h, w, scale)

def test_large_inputs_not_divisible():
    # Large h and w, not divisible by scale_factor**2
    h, w, scale = 999, 888, 10
    # scale_factor**2=100
    # h//100=9, h%100=99, new_h=10, output_h=100
    # w//100=8, w%100=88, new_w=9, output_w=90
    codeflash_output = get_new_h_w(h, w, scale)

def test_maximum_allowed_size():
    # Test with maximum allowed size under 1000 elements
    h, w, scale = 999, 999, 3
    # scale_factor**2=9
    # h//9=111, h%9=0, new_h=111, output_h=333
    # w//9=111, w%9=0, new_w=111, output_w=333
    codeflash_output = get_new_h_w(h, w, scale)

def test_large_scale_factor_and_large_inputs():
    # Large scale_factor and large h, w
    h, w, scale = 900, 800, 30
    # scale_factor**2=900
    # h//900=1, h%900=0, new_h=1, output_h=30
    # w//900=0, w%900=800, new_w=1, output_w=30
    codeflash_output = get_new_h_w(h, w, scale)

def test_large_inputs_one_dimension():
    # Large h, small w
    h, w, scale = 999, 2, 10
    # scale_factor**2=100
    # h//100=9, h%100=99, new_h=10, output_h=100
    # w//100=0, w%100=2, new_w=1, output_w=10
    codeflash_output = get_new_h_w(h, w, scale)

# -------------------
# Determinism Test
# -------------------

def test_determinism():
    # Call the function multiple times with the same input and check for same output
    h, w, scale = 123, 456, 7
    codeflash_output = get_new_h_w(h, w, scale); result1 = codeflash_output
    codeflash_output = get_new_h_w(h, w, scale); result2 = 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-get_new_h_w-mbdffli9 and push.