Weekly GitHub Report for Tensorflow: June 09, 2025 - June 16, 2025 (12:08:21)

Weekly GitHub Report for Tensorflow

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Table of Contents

• I. News
  • 1.1. Recent Version Releases
  • 1.2. Other Noteworthy Updates
• II. Issues
  • 2.1. Top 5 Active Issues
  • 2.2. Top 5 Stale Issues
  • 2.3. Open Issues
  • 2.4. Closed Issues
  • 2.5. Issue Discussion Insights

• III. Pull Requests
  • 3.1. Open Pull Requests
  • 3.2. Closed Pull Requests
  • 3.3. Pull Request Discussion Insights

• IV. Contributors
  • 4.1. Contributors

I. News

1.1 Recent Version Releases:

The current version of this repository is v2.19.0

1.2 Version Information:

The TensorFlow 2.19.0 release, created on March 5, 2025, introduces breaking changes to the LiteRT C++ and Python APIs, including the transition of tf.lite.Interpreter to a new location, with a deprecation warning ahead of its removal in version 2.20. Additionally, the update enhances tfl.Cast op to support bfloat16 in the runtime kernel and discontinues publishing libtensorflow packages, though they remain accessible via PyPI.

II. Issues

2.1 Top 5 Active Issues:

We consider active issues to be issues that that have been commented on most frequently within the last week. Bot comments are omitted.

1. Some sorting related ops produce results inconsistent with NumPy when tensor contains NaN: This issue highlights a bug in TensorFlow version 2.17 where several sorting and indexing operations produce results that are inconsistent with NumPy when the tensor contains NaN values. The problem is exacerbated in the nightly version, where CPU and GPU implementations often yield different results, leading to discrepancies in operations like tf.sort, tf.argsort, tf.math.top_k, and tf.searchsorted.

   • A contributor expressed interest in working on the issue as their first contribution, aiming to reproduce the bug and propose a fix. Another contributor analyzed the issue, implemented a fix to ensure consistent NaN handling across CPU and GPU, and created tests to verify the solution, requesting to submit a pull request for review.
   • Number of comments this week: 2

2. TensorFlow disables SwiftUI Previews: This issue reports a bug where integrating the TensorFlowLiteSwift library into an iOS app causes SwiftUI Previews to stop functioning, although the app runs correctly on a device or simulator. The problem persists despite using the specified version of TensorFlowLiteSwift, and the issue can be reproduced by adding the TensorFlowLite framework to a simple SwiftUI app.

   • A team member acknowledged the issue and expressed gratitude for reporting it, stating they would attempt to reproduce the behavior and provide updates.
   • Number of comments this week: 1

3. how to build libtensorflowlite_c.so with Address Sanitizer: This issue is about a user seeking guidance on how to build the libtensorflowlite_c.so library with Address Sanitizer enabled, using the latest or version 2.13 of TensorFlow. The user has confirmed that the issue is reproducible with TensorFlow Nightly and is looking for specific build instructions or configurations to achieve this.

   • A responder thanked the user for raising the issue and provided detailed instructions, including specific Bazel build commands and links to relevant documentation, to help build the library with Address Sanitizer. They requested feedback on whether the provided solution worked and offered further assistance if needed.
   • Number of comments this week: 1

4. Deeplabcut issue: This issue involves a problem with building or installing Deeplabcut, where the user encounters an ImportError related to TensorFlow's native runtime on a Windows 11 system with TensorFlow version 2.19 and CUDA version 12.9. The error occurs when attempting to load a TensorFlow-based project using PyTorch version 3.0, resulting in a failure to import a necessary dynamic link library (DLL).

   • A user experiencing the same issue resolved it by creating a new conda environment with Python 3.10, installing TensorFlow version 2.14, and using CUDA version 11.8, which suggests a potential compatibility issue with the newer versions of TensorFlow and CUDA.
   • Number of comments this week: 1

Since there were fewer than 5 open issues, all of the open issues have been listed above.

2.2 Top 5 Stale Issues:

We consider stale issues to be issues that has had no activity within the last 30 days. The team should work together to get these issues resolved and closed as soon as possible.

1. TF-TRT Warning: Could not find TensorRT: This issue involves a user experiencing difficulties with TensorFlow on an Ubuntu 22.04 system, specifically encountering a warning that TensorRT could not be found despite multiple attempts to install and configure the software within an Anaconda environment. The user suspects that the problem may be related to the NVIDIA driver compatibility with their RTX 3050 TI GPU, as they are forced to use an older driver version (535) instead of the automatically installed 550 version, which does not work on their multi-monitor setup.
2. SystemError in tf.ensure_shape and tf.compat.v1.ensure_shape when dtype of shape is tf.uint64 and its value is too large.: This issue involves a bug in TensorFlow where using tf.ensure_shape or tf.compat.v1.ensure_shape with a shape of dtype tf.uint64 and a value close to 2^64 results in a SystemError and OverflowError. The problem occurs specifically when the shape is defined with large values, such as tf.constant([18446743219011059112, 1], dtype=tf.uint64), causing these errors to be triggered in eager execution mode.
3. Feature Request: Integrate different Digital Signal Processing into tf.signal: This issue is a feature request to integrate advanced Digital Signal Processing (DSP) functionalities into TensorFlow's tf.signal module, similar to those available in the PyTorch ecosystem, particularly from the julius library. The request highlights the need for native tools within TensorFlow to perform complex audio data augmentation, which would enhance the development of robust audio recognition and processing models by providing seamless data preprocessing and augmentation capabilities without relying on external libraries.
4. [DOCS] Missing complex input for Round op: This issue highlights a documentation bug in TensorFlow's Round operation, where the official documentation incorrectly states that a complex tensor can be used as input, but in practice, this results in an error unless the operation is applied separately to the real and imaginary parts. The user has reproduced this inconsistency using TensorFlow version 2.15.0 on MacOS Sonoma, and the error log indicates that the operation is not supported for complex data types on the available devices.
5. tf.raw_ops.Unbatch aborts with "Check failed: d < dims()": This issue pertains to a bug in TensorFlow version 2.17, where the tf.raw_ops.Unbatch operation aborts unexpectedly with an error message indicating a failed check on tensor dimensions, specifically "Check failed: d < dims()". The problem has been reproduced using TensorFlow Nightly on a Linux Ubuntu 20.04.3 LTS system with custom code, and the error occurs when executing a standalone script that involves random tensor operations.

2.3 Open Issues

This section lists, groups, and then summarizes issues that were created within the last week in the repository.

Issues Opened This Week: 4

Summarized Issues:

• TensorFlow Version Compatibility Issues: Several issues have been reported regarding compatibility problems with different versions of TensorFlow. One issue involves a bug in TensorFlow version 2.17 where sorting and indexing operations produce inconsistent results with NumPy when handling NaN values, with differences noted between CPU and GPU implementations. Another issue describes a problem with loading a TensorFlow-based project in Deeplabcut on Windows 11, where an ImportError occurs due to a failed DLL initialization routine when using TensorFlow version 2.19 and CUDA version 12.9.
  • issues/95235, issues/95274

• TensorFlowLiteSwift Integration Bug: A bug has been identified where integrating the TensorFlowLiteSwift library version 2.17.0 into an iOS app causes SwiftUI Previews to stop functioning. Despite this issue, the app continues to run correctly on a device or simulator, indicating a specific problem with the preview functionality.
  • issues/95106

• Building TensorFlow with Address Sanitizer: Guidance is sought on building the libtensorflowlite_c.so library with Address Sanitizer enabled using TensorFlow's latest version or version 2.13. The issue includes a response with specific Bazel build commands and documentation links to assist in addressing the query.
  • issues/95222

2.4 Closed Issues

This section lists, groups, and then summarizes issues that were closed within the last week in the repository. This section also links the associated pull requests if applicable.

Issues Closed This Week: 0

Summarized Issues:

As of our latest update, there were no issues closed in the project this week.

2.5 Issue Discussion Insights

This section will analyze the tone and sentiment of discussions within this project's open and closed issues that occurred within the past week. It aims to identify potentially heated exchanges and to maintain a constructive project environment.

Based on our analysis, there are no instances of toxic discussions in the project's open or closed issues from the past week.

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III. Pull Requests

3.1 Open Pull Requests

This section provides a summary of pull requests that were opened in the repository over the past week. The top three pull requests with the highest number of commits are highlighted as 'key' pull requests. Other pull requests are grouped based on similar characteristics for easier analysis. Up to 25 pull requests are displayed in this section, while any remaining pull requests beyond this limit are omitted for brevity.

Pull Requests Opened This Week: 4

Key Open Pull Requests

1. Allow TFL to TOSA pipeline to load TFL dialect: This pull request addresses the issue of the TFL dialect no longer being part of the common dialects by enabling the TFL to TOSA pipeline to load the TFL dialect, ensuring that the tf-tosa-opt --tofl-to-tosa-pipeline command can continue to convert from TFL.

• URL: pull/95205

• Merged: No

• Associated Commits: b39b0

2. [PROTOTYPE] Cleanup TFL dependencies in tosa: This pull request aims to streamline the TensorFlow Lite (TFLite) dependencies within the TensorFlow Open Source Architecture (TOSA) by removing unnecessary components, as indicated by the commit titled "Cleanup TFL dependencies in tosa" and is currently open for review.

• URL: pull/95262

• Merged: No

• Associated Commits: 2e4f0

3. Fix compilation error in tensorflow/python/tfcompile_wrapper.cc on s390x: This pull request addresses a compilation error in the TensorFlow project on the s390x architecture by explicitly including the necessary header file llvm/ADT/StringRef.h in tensorflow/python/tfcompile_wrapper.cc to resolve an issue with the llvm::sys::getHostCPUName().str() function, which was previously causing a build failure due to a missing definition of StringRef.

• URL: pull/95322

• Merged: No

• Associated Commits: d5261

Other Open Pull Requests

• Decoding Issue in pip_smoke_test.py: This pull request addresses a decoding issue in the pip_smoke_test.py script of the TensorFlow project. It adds a safeguard to handle byte outputs from subprocess.check_output() safely, ensuring the output is properly decoded to a string to prevent errors during test parsing and improve the script's robustness and portability across different Python environments.
  • pull/95335

3.2 Closed Pull Requests

This section provides a summary of pull requests that were closed in the repository over the past week. The top three pull requests with the highest number of commits are highlighted as 'key' pull requests. Other pull requests are grouped based on similar characteristics for easier analysis. Up to 25 pull requests are displayed in this section, while any remaining pull requests beyond this limit are omitted for brevity.

Pull Requests Closed This Week: 0

As of our latest update, there are no closed pull requests for the project this week.

3.3 Pull Request Discussion Insights

This section will analyze the tone and sentiment of discussions within this project's open and closed pull requests that occurred within the past week. It aims to identify potentially heated exchanges and to maintain a constructive project environment.

Based on our analysis, there are no instances of toxic discussions in the project's open or closed pull requests from the past week.

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IV. Contributors

4.1 Contributors

Active Contributors:

We consider an active contributor in this project to be any contributor who has made at least 1 commit, opened at least 1 issue, created at least 1 pull request, or made more than 2 comments in the last month.

If there are more than 10 active contributors, the list is truncated to the top 10 based on contribution metrics for better clarity.

Contributor	Commits	Pull Requests	Issues	Comments
ShengDong207	0	0	19	0
mihaimaruseac	0	0	0	18
SilentTester73	0	0	12	1
Venkat6871	0	0	0	13
KAVYANSHTYAGI	3	2	0	0
harshithn31	2	1	1	0
cx104906	0	0	3	1
gaikwadrahul8	0	0	0	4
rakshithgb-fujitsu	2	1	0	0
Redempt1onzzZZ	0	0	1	2