Weekly GitHub Report for Tensorflow: June 16, 2025 - June 23, 2025 (12:07:07)

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 in the LiteRT C++ and Python APIs, including the transition of tf.lite.Interpreter to a new location, with a deprecation warning for its future removal in version 2.20. Notable improvements include support for bfloat16 in the tfl.Cast operation, and the discontinuation of publishing libtensorflow packages, which can still be accessed 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. building //tensorflow/lite/ios:TensorFlowLiteC_xcframework results in broken header files: This issue involves a problem with building the TensorFlowLiteC_xcframework for iOS, where the header file c_api.h attempts to include a non-existent types.h file, resulting in a build error. The user reports that this issue occurs when trying to compile a Swift iOS app project that includes the TensorFlowLiteC framework, leading to a failure in building the module due to the missing header file.

   • The comments discuss the issue's reproducibility and confirm the missing types.h file, with a temporary workaround suggested to manually copy the file from a specific location. However, this workaround is not ideal as it leads to further compilation issues with other missing headers, and a proper fix is needed to automate the inclusion of all necessary files.
   • Number of comments this week: 3

2. tf.nn.conv2d with invalid input dims crashes in TF ≤2.19 — now raises InvalidArgumentError in nightly: This issue describes a bug in TensorFlow 2.19 where using tf.nn.conv2d with an invalid input dimension causes a crash with an abort/core dump, while in the nightly version, it raises a catchable InvalidArgumentError. The problem arises because tf.nn.conv2d expects a 4D tensor as input, but the provided input is only 2D, leading to the error.

   • A user tested the code on both TensorFlow 2.19 and a nightly version, confirming that the code raises an error due to an input rank mismatch rather than crashing. They suggested reshaping the input tensor to 4D to resolve the issue and provided a reference link for further guidance, recommending using stable releases for consistent behavior.
   • Number of comments this week: 1

3. YoloX different Model Output for Python and Android: This issue involves a bug where the YoloX model produces different outputs when run on Python compared to Android, despite using the same model and test image. The user has ruled out common issues such as endianness and has provided code for both platforms, suggesting that the problem may be specific to the Android implementation of the model.

   • A commenter expressed interest in contributing to the project, offering their experience with TensorFlow and mobile deployment to help investigate and resolve the discrepancy in the YoloX model's output on Android. They requested guidance on how to contribute and which parts of the codebase to focus on.
   • 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 installation attempts. The user, a graduate student, is struggling with driver compatibility for their NVIDIA RTX 3050 TI GPU, as the system automatically installs an incompatible driver version, leading to significant time spent on debugging rather than on their machine learning coursework.
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 describes 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 set to a large value, such as tf.constant([18446743219011059112, 1], dtype=tf.uint64), causing these APIs to fail 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 integration aims to provide native tools for complex audio data augmentation, enhancing the capabilities for researchers and developers working on audio-related projects by streamlining workflows and reducing reliance 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 indicates that the Round operation does not support complex numbers directly on the available devices.
5. tf.raw_ops.Unbatch aborts with "Check failed: d < dims()": This issue reports a bug in TensorFlow version 2.17 where the tf.raw_ops.Unbatch operation aborts unexpectedly with an error message "Check failed: d < dims()". The problem occurs on a Linux Ubuntu 20.04.3 LTS system using Python 3.11.8, and the error can be reproduced with TensorFlow Nightly, indicating a persistent issue in the codebase.

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: 5

Summarized Issues:

• TensorFlowLiteC_xcframework Build Issue for iOS: The TensorFlowLiteC_xcframework for iOS has a problem when built using Bazel, where the c_api.h header file incorrectly includes a non-existent types.h file. This results in compilation errors when attempting to integrate the framework into an iOS project.
  • issues/95417

• Model Output Discrepancy on Android: The YoloX model produces different outputs for the same input image when run on Python compared to Android, despite using the same model and input data. This discrepancy seems to be specific to Android, as similar code works for other models like RT-detr and Yolov11/v8.
  • issues/95489

• Guidance on TensorFlow C API and GPU Delegate: There is a request for guidance on the correct usage of the libtensorflowlite_c.so C API and the GPU OpenCL delegate in TensorFlow. Users are seeking clarity on how to effectively implement these components in their projects.
  • issues/95634

• Runtime Error with Reduce Operator: A runtime error occurs when using empty axes for a reduce operator in TensorFlow's nightly build (version 2.20.0.dev20250619), which does not happen in the stable release (version 2.19.0). This issue is linked to a specific pull request that introduced the problem.
  • issues/95663

• Support Request for RTX 50xx Series GPUs: There is a request for TensorFlow to support the RTX 50xx series GPUs, as a user encountered a bug while using the latest TensorFlow version on Ubuntu 22.04 with custom code. This highlights the need for compatibility with newer GPU models.
  • issues/95705

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: 4

Summarized Issues:

• ImportError and DLL Load Failures in TensorFlow: Users have reported ImportErrors related to DLL load failures when using TensorFlow, particularly in environments where TensorFlow is installed on a different disk than the Jupyter notebook or on Microsoft platforms. These issues often stem from missing dependencies or compatibility problems with the system configuration, affecting the loading of native TensorFlow runtime modules like _pywrap_tensorflow_internal.
  • issues/95413, issues/95468

• Issues with TensorFlow's @tf.function Decorator: A bug has been identified when using TensorFlow's @tf.function decorator with nested functions that accept tf.Variable objects, resulting in an AssertionError. This problem arises due to limitations in TensorFlow's graph tracing and variable mutation tracking, especially when dynamic input transformations necessitate retracing of inner functions.
  • issues/95578

• Spam Reports on TensorFlow GitHub: The TensorFlow GitHub project has encountered spam reports where users submit personal contact information and irrelevant content instead of valid bug reports. Such submissions are promptly closed as spam to maintain the integrity of the issue tracking system.
  • issues/95644

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: 2

Key Open Pull Requests

1. io_utils: prevent input() crash in non-interactive mode: This pull request addresses an issue in the TensorFlow project by modifying the ask_to_proceed_with_overwrite() function in io_utils.py to detect when stdin is not a TTY, thereby preventing crashes in non-interactive environments such as CI/cron jobs by skipping the prompt and returning False instead of raising an EOFError.

• URL: pull/95525

• Merged: No

• Associated Commits: bcf49, 82699

2. [mlir][tosa] Support negative axis in gather lowering: This pull request introduces support for negative axis values in the lowering process of TensorFlow Lite's gather operation within the MLIR TOSA framework, as detailed in the commit by Tai Ly.

• URL: pull/95608

• Merged: No

• Associated Commits: 7e45e

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: 5

Key Closed Pull Requests

1. Ci fix rng test gpu by limiting threads in threadpool to 20: This pull request addresses a CI issue in the TensorFlow project by fixing the rng_test for GPU by limiting the number of threads in the thread pool to 20, as a workaround for a context that is not being destroyed, although it was not merged into the main codebase.

• URL: pull/95501

• Merged: No

• Associated Commits: 40e3e, f65e5, 5a71c, 83713, 70b4d, abb24, 642ae, b6821, 15640, c4958, b6b66, 6d19b, 4c853, d1038, 54e1f, d8198, d860d, c0b36, 18d5c, 7946a, 24c78, 0c992, 2bab5, 89810, 4cc12, 6aa74, 63752, 57188, dc9fb, a91e4, 75ee5, 1e3c6, d40d9, 31d9c, ec39e, 94d31, f42a7, 94f61, 71a8f, d2e43, 1e3ef, ef2d4, 5bad4, 8f1cb, 37d76, e8844, 4556d, cf094, a2036, 33542, 4717f, b9bf3, 3ed87, cd4b0, f40da, a26fb, 038a6, 52994, 79309, 84c13, 4396a, 3c61e, 06702, 6e9f2, da5df, ff760, de1e4, b4e5e, ce1b2, 874c4, 451d1, 8fc12, c1526, 5dbad, 5c1aa, f7991, d377c, 7c927, f5f98, b5400, 1537a, cece9, 7ae16, e624e, 09335, 2211b, 2a929, 6c915, 07cab, 4d444, 575fd, 67b5d, a2bad, 468cf, 7ccb1, 58fc0, db5ae, 9e21f, da24c, 3515d, 8cf48, 09b52, ccced, a382c, 532df, b854f, 58d80, f4770, 3c370, e5dd7, 9f051, 1afb6, f854d, 554f8, 68c43, 2baac, 33a41, e554c, 1c5d7, 4d453, d7f29, 4ca78, 3ac1e, ed3e4, 5788e, 75503, 04c3e, e2acb, 188d1, 1d388, 87930, c1375, 66ca7, b0d33, 713b6, 09053, b6971, d9163, 76f24, 252a9, 7ec4c, 2464a, 8aedd, 071ee, 3a90e, 67d8f, ac4cb, 02686, 25619, e60b7, 70057, fd54d, b74d5, 72a9f, d71ec, f22b6, 8df41, 22772, b1e81, 34e1c, b45da, f8452, 03daf, 68e1e, e1d97, b3932, a5407, 28861, 79765, 467f7, cf3c4, 0e049, aeabf, 4c21b, 03b3d, 62c0d, b664f, 9019a, 496f7, d5f0c, 16c82, ae453, 9de27, eec13, 15ab9, 4bc26, a3f8d, 34a99, 89a93, 7b820, a80fd, 656ad, 5063b, 21b23, 409ac, 74fa1, 6fd39, 94825, b1cde, cc5a9, e5b0d, a3a2f, 390b7, c1e07, 716b3, 3f49a, 7a0fc, 99339, 9124f, a09bd, 428ff, 1eb0b, 3136d, 749be, 38c69, 5da5e, 30c7c, c2522, 21309, be774, b80f1, 592bb, 5f752, b6235, dede7, 1b17a, 2470a, 06234, b0cf7, 33ce7, 7c809, 3a816, 49a8e, 43a62, 71bf8, 773d0, 47dc3, 0909c, 6ba21, 5013f, 830c2, 03248, 6e173, c5291, 6523a, 45cb8, 68a01, 5bfb3, fa591, c0771

2. Potential Negative Number Used as Index small fix: This pull request addresses a potential issue in the TensorFlow codebase where the return value of snprintf, which can be negative upon failure, is used as an array index without validation, potentially leading to out-of-bounds writes and undefined behavior, and includes updates such as modifying gpu_compatibility.cc, leveraging sprintf's null-terminating behavior, and removing an unused variable.

• URL: pull/95512

• Merged: Yes

• Associated Commits: 39d46, 28ecd, 3f910

3. Fixed the issue when accessing paddings_data in VisitPadNode: This pull request addresses and resolves an issue related to accessing paddings_data in the VisitPadNode function, which was identified through a specific test failure in the WebNN conformance tests, and has been successfully merged into the TensorFlow project.

• URL: pull/95506

• Merged: Yes

• Associated Commits: a3ed1

Other Closed Pull Requests

• Typographical Errors in Documentation: This pull request addresses and corrects typographical errors in the documentation strings of the TensorFlow project. The changes were successfully merged, improving the clarity and accuracy of the documentation.
  • pull/95627

• Addition of New Workflow File: This pull request involves adding a new workflow file named "test.txt" to the TensorFlow project. However, it was not merged into the main codebase, indicating it might have been a test or draft.
  • pull/95667

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
SilentTester73	0	0	11	1
mihaimaruseac	2	0	0	4
KAVYANSHTYAGI	3	2	0	0
Venkat6871	1	1	0	3
mohiuddin-khan-shiam	2	1	0	0
wangw-1991	1	1	1	0
salim-nibouche	0	0	1	2
gaikwadrahul8	0	0	0	3
nikhilshinde63	1	1	0	0
vamsimanchala	1	1	0	0