⚡️ Speed up function _compute_shear_matrix by 14%

[codeflash-ai]

📄 14% (0.14x) speedup for _compute_shear_matrix in kornia/geometry/transform/affwarp.py

⏱️ Runtime : 495 microseconds → 435 microseconds (best of 168 runs)

📝 Explanation and details

Optimization Explanation.

1. Condition Checking: The function eye_like now adheres to a clearer conditional structure which aims for fast execution and reduces the number of conditional checks.

2. Tensor Operations: Enhanced tensor operations in _compute_shear_matrix. The code directly uses squeeze(-1) in place of indexing with 0:1 or 1:2 to remove unnecessary dimension adjustments, which optimizes the runtime by minimizing unnecessary tensor operations.

3. Memory Usage: The optimized code utilizes expand and repeat correctly based on the condition of shared_memory, minimizing extra memory allocation when unnecessary.

These small yet crucial improvements in the code not only optimise the runtime performance but also maintain clarity and readability.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 6 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
import torch
from kornia.core import Tensor, eye
from kornia.geometry.transform.affwarp import _compute_shear_matrix
from kornia.utils.misc import eye_like
from torch.testing import assert_allclose

# LICENSE HEADER MANAGED BY add-license-header
#
# Copyright 2018 Kornia Team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

__all__ = [
    "Affine",
    "Rescale",
    "Resize",
    "Rotate",
    "Scale",
    "Shear",
    "Translate",
    "affine",
    "affine3d",
    "rescale",
    "resize",
    "resize_to_be_divisible",
    "rotate",
    "rotate3d",
    "scale",
    "shear",
    "translate",
]
from kornia.geometry.transform.affwarp import _compute_shear_matrix

# unit tests




def test_large_batch_size():
    # Test with a large batch size
    shear = torch.rand(1000, 2)
    codeflash_output = _compute_shear_matrix(shear)


def test_inf_values():
    # Test with infinity shear values
    shear = torch.tensor([[float('inf'), 0.0]])
    codeflash_output = _compute_shear_matrix(shear)

def test_nan_values():
    # Test with NaN shear values
    shear = torch.tensor([[float('nan'), 0.0]])
    codeflash_output = _compute_shear_matrix(shear)

def test_requires_grad():
    # Test with requires_grad=True
    shear = torch.tensor([[1.0, 0.0]], requires_grad=True)
    codeflash_output = _compute_shear_matrix(shear)



import pytest  # used for our unit tests
import torch
from kornia.core import Tensor, eye
from kornia.geometry.transform.affwarp import _compute_shear_matrix
from kornia.utils.misc import eye_like
from torch.testing import assert_allclose

# LICENSE HEADER MANAGED BY add-license-header
#
# Copyright 2018 Kornia Team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#


__all__ = [
    "Affine",
    "Rescale",
    "Resize",
    "Rotate",
    "Scale",
    "Shear",
    "Translate",
    "affine",
    "affine3d",
    "rescale",
    "resize",
    "resize_to_be_divisible",
    "rotate",
    "rotate3d",
    "scale",
    "shear",
    "translate",
]
from kornia.geometry.transform.affwarp import _compute_shear_matrix

# unit tests







def test_large_batch_size():
    # Test with a large batch size
    shear = torch.rand(1000, 2)  # Ensure the tensor size is under 100MB
    codeflash_output = _compute_shear_matrix(shear)



def test_invalid_shape():
    # Test with invalid shape
    shear = torch.tensor([0.5, 0.3, 0.1])
    with pytest.raises(RuntimeError):
        _compute_shear_matrix(shear)

To edit these changes git checkout codeflash/optimize-_compute_shear_matrix-m8o93pf4 and push.

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