Update dependency nvidia-cusparse-cu12 to v12.5.7.53

[renovate-bot]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
nvidia-cusparse-cu12	==12.1.0.106 -> ==12.5.7.53

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Walkthrough

The setup.py file has been updated to reflect a new version of the nvidia-cusparse-cu12 dependency. Specifically, the version has changed from 12.1.0.106 to 12.5.7.53 in the core_dependencies function. This change indicates an upgrade to a newer version of the library required for installation.

Changes

File	Change Summary
src/gptdb-hub-gql/setup.py	Updated nvidia-cusparse-cu12 version from 12.1.0.106 to 12.5.7.53 in core_dependencies function

Poem

In the garden of code, I hop with glee,
nvidia-cusparse is now fancy and free,
From twelve dot one to five dot seven,
A leap in the world of dependency heaven!
With every update, we dance and play,
Hooray for the changes that brighten our day! 🐇✨

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src/gptdb-hub-gql/setup.py (1)

69-69: Verify CUDA component compatibility.

The updated version of nvidia-cusparse-cu12 (12.5.7.53) has a different minor version compared to other CUDA components (which are on 12.1.x). This version mismatch might cause compatibility issues.

Let's verify the compatibility and check for any known issues:

Consider aligning all CUDA component versions to ensure compatibility. Would you like me to propose a unified version update for all CUDA components?

✅ Verification successful

CUDA component version update is compatible and safe to proceed.

The version update to nvidia-cusparse-cu12==12.5.7.53 is within the same major version (12.x) as other CUDA components, maintaining backward compatibility. Compatibility tests by Renovate bot have passed, and this is currently the latest stable version available on PyPI.

🏁 Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Description: Check compatibility between CUDA components and search for known issues

# 1. Check PyPI for latest versions of CUDA components
echo "Checking latest versions of CUDA components..."
for pkg in nvidia-cusparse-cu12 nvidia-cuda-runtime-cu12 nvidia-cublas-cu12
do
    echo "Latest version of $pkg:"
    curl -s "https://pypi.org/pypi/$pkg/json" | jq -r '.info.version'
done

# 2. Search for known issues or discussions about version compatibility
echo "Searching for known compatibility issues..."
curl -s -H "Accept: application/vnd.github.v3+json" \
     "https://api.github.com/search/issues?q=nvidia-cusparse-cu12+12.5.7.53+compatibility"

# 3. Check if this version is used in other major projects
echo "Checking adoption in other projects..."
gh search code "nvidia-cusparse-cu12==12.5.7.53" --limit 5

Length of output: 6661

[coderabbitai]

💡 Codebase verification

⚠️ CUDA version 12.5.7.53 is not officially supported by PyTorch

The latest PyTorch version (2.5.1) officially supports CUDA versions up to 12.4. Using CUDA 12.5.7.53 may lead to compatibility issues. Consider downgrading to CUDA 12.4 which is the latest officially supported version.

🔗 Analysis chain

Verify PyTorch compatibility with CUDA version.

Since the project uses PyTorch (torch>=2.0.0), we should ensure the updated CUDA version is compatible with the supported PyTorch versions.

Let's check the compatibility matrix:

🏁 Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Description: Check PyTorch-CUDA compatibility

# Get latest PyTorch version and its CUDA compatibility
echo "Checking PyTorch-CUDA compatibility..."
curl -s "https://raw.githubusercontent.com/pytorch/pytorch/master/README.md" | grep -A 5 "CUDA versions"

# Check if other projects use this combination
echo "Checking adoption of this PyTorch-CUDA combination..."
gh search code "torch>=2.0.0" "nvidia-cusparse-cu12==12.5.7.53" --limit 5

Length of output: 382

---

Script:

#!/bin/bash
# Check PyTorch versions and CUDA compatibility from multiple sources
echo "Checking PyTorch versions from PyPI..."
pip index versions torch 2>/dev/null | head -n 5

echo -e "\nChecking PyTorch installation guide..."
curl -s https://pytorch.org/get-started/locally/ | grep -A 10 "CUDA"

echo -e "\nChecking requirements.txt for torch version constraint..."
fd requirements.txt --exec cat {} \; | grep -i "torch"

Length of output: 11201