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@codeflash-ai codeflash-ai bot commented Jan 24, 2025

📄 21% (0.21x) speedup for float_to_255 in pydantic/color.py

⏱️ Runtime : 11.7 microseconds 9.74 microseconds (best of 239 runs)

📝 Explanation and details

Given these considerations, this function is already optimized for speed. Here's the function with minimal but necessary changes.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 52 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 1 Passed
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests Details
import pytest  # used for our unit tests
from pydantic.color import float_to_255

# unit tests

def test_valid_inputs():
    # Test exact boundaries
    codeflash_output = float_to_255(0.0)
    codeflash_output = float_to_255(1.0)
    # Test middle values
    codeflash_output = float_to_255(0.5)
    codeflash_output = float_to_255(0.25)
    codeflash_output = float_to_255(0.75)
    # Test values close to boundaries
    codeflash_output = float_to_255(0.0001)
    codeflash_output = float_to_255(0.9999)


def test_non_float_inputs():
    # Test integer inputs
    codeflash_output = float_to_255(0)
    codeflash_output = float_to_255(1)
    # Test string inputs
    with pytest.raises(TypeError):
        float_to_255("0.5")
    with pytest.raises(TypeError):
        float_to_255("1")
    # Test None input
    with pytest.raises(TypeError):
        float_to_255(None)


def test_boundary_conditions():
    # Test floating-point precision limits
    codeflash_output = float_to_255(1.0 - 1e-10)
    codeflash_output = float_to_255(0.0 + 1e-10)
# 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 pydantic.color import float_to_255

# unit tests

def test_basic_cases():
    # Test exact bounds
    codeflash_output = float_to_255(0.0)
    codeflash_output = float_to_255(1.0)
    
    # Test mid-range values
    codeflash_output = float_to_255(0.5)
    codeflash_output = float_to_255(0.25)
    codeflash_output = float_to_255(0.75)

    # Test small increments
    codeflash_output = float_to_255(0.1)
    codeflash_output = float_to_255(0.9)

    # Test rounding cases
    codeflash_output = float_to_255(0.498)
    codeflash_output = float_to_255(0.502)



def test_deterministic_behavior():
    # Test consistent rounding
    codeflash_output = float_to_255(0.333333)

def test_boundary_precision():
    # Test precision cases
    codeflash_output = float_to_255(1/255)
    codeflash_output = float_to_255(254/255)


def test_zero_and_one_edge_cases():
    # Test exact zero and one
    codeflash_output = float_to_255(0.0)
    codeflash_output = float_to_255(1.0)

def test_minimal_incremental_changes():
    # Test small incremental changes
    codeflash_output = float_to_255(0.00000001)
    codeflash_output = float_to_255(0.99999999)

def test_subnormal_floating_point_numbers():
    # Test very small positive subnormal numbers
    codeflash_output = float_to_255(5e-324)

    # Test very small negative subnormal numbers
    with pytest.raises(ValueError):
        float_to_255(-5e-324)

def test_floating_point_arithmetic_anomalies():
    # Test values resulting from floating-point arithmetic
    codeflash_output = float_to_255(0.1 + 0.2 - 0.3)
    codeflash_output = float_to_255(0.3 - 0.1 - 0.2)

def test_extreme_values_near_limits():
    # Test values just below 1
    codeflash_output = float_to_255(0.9999999999999999)

    # Test values just above 0
    codeflash_output = float_to_255(0.0000000000000001)

def test_floating_point_representations_of_integers():
    # Test exact representation of integers
    codeflash_output = float_to_255(0.5)
    codeflash_output = float_to_255(0.25)
    codeflash_output = float_to_255(0.75)

def test_negative_zero():
    # Test negative zero representation
    codeflash_output = float_to_255(-0.0)

def test_unusual_floating_point_values():
    # Test denormalized numbers
    codeflash_output = float_to_255(1e-308)
    codeflash_output = float_to_255(1e-40)



from pydantic.color import float_to_255

def test_float_to_255():
    assert float_to_255(0.0) == 0

📢 Feedback on this optimization? Discord

Given these considerations, this function is already optimized for speed. Here's the function with minimal but necessary changes.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Jan 24, 2025
@codeflash-ai codeflash-ai bot requested a review from misrasaurabh1 January 24, 2025 08:38
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