Weekly GitHub Report for Tensorflow: November 10, 2025 - November 17, 2025 (12:05:50)

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:

Released on March 5, 2025, TensorFlow version 2.19.0 introduces breaking changes to the tf.lite API, including the deprecation of tf.lite.Interpreter in favor of ai_edge_litert.interpreter and changes to certain C++ constants for improved API compatibility. Key updates also include runtime support for the bfloat16 data type in the tfl.Cast operation and the discontinuation of standalone libtensorflow package publishing, while still allowing unpacking from 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. build tersonflow-lite error: This issue reports a build error encountered when compiling TensorFlow Lite with XNNPACK enabled on an Ubuntu system, specifically related to undefined or mismatched declarations in the file_util.cc source file. The user has reproduced the bug using the TensorFlow nightly build and provided detailed build logs showing multiple compilation errors involving the FileDescriptor and FileDescriptorView classes.

   • The comments discuss a referenced pull request that was supposed to fix the issue, but the bug persists for the user. There is a question about whether the user is building from the latest commit or the same one as the fix, and the issue is reopened for further investigation.
   • Number of comments this week: 3

2. failed: undeclared inclusion(s) in rule '//tensorflow/core/grappler:devices': This issue reports a build failure in TensorFlow version 2.21.0 on Void Linux, caused by undeclared inclusion(s) in the Bazel build rule for '//tensorflow/core/grappler:devices'. The user provides detailed environment information and a reproducible build script, highlighting missing dependency declarations for several protobuf header files during the build process.

   • The single comment in the thread is a brief mention of another user without any further discussion or troubleshooting, leaving the issue unresolved and without additional input.
   • Number of comments this week: 1

3. [CUDA] illegal memory read on Where: This issue reports a bug in TensorFlow 2.20 where the GPU kernel PropagateWhereIndicesKernel performs an illegal memory read when executing the tf.raw_ops.Where operation on extremely large tensors, causing an out-of-bounds access detected by Compute-Sanitizer. The problem appears related to incorrect bounds calculation or index overflow during the handling of tensors with around 2 billion elements on CUDA 12.5.1 and cuDNN 9.2.1 under Ubuntu 22.04.

   • A commenter analyzing the bug explains that the error likely stems from the GPU kernel accessing memory beyond its allocation due to index overflow or miscalculated bounds when processing very large tensors. They express interest in contributing to the project, asking if the issue is being addressed and offering to start with documentation or smaller GPU-related tasks.
   • 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 describes a problem where TensorFlow on Ubuntu 22.04 cannot detect TensorRT despite having the appropriate NVIDIA drivers and CUDA version installed, specifically with an RTX 3050 Ti GPU and CUDA 12.4. The user reports difficulties with driver compatibility, having to downgrade from the default NVIDIA 550 driver to version 535, and is seeking help to resolve the persistent "Could not find TensorRT" warning that hinders their machine learning development.
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 reports a bug in TensorFlow where using tf.ensure_shape or tf.compat.v1.ensure_shape with a shape tensor of type tf.uint64 containing very large values close to 2^64 causes a SystemError and OverflowError. Specifically, when such large values are passed in eager execution mode, the functions fail with an error related to the built-in isinstance function, indicating improper handling of large unsigned 64-bit integers in shape validation.
3. Feature Request: Integrate different Digital Signal Processing into tf.signal: This issue is a feature request proposing the integration of advanced digital signal processing (DSP) functionalities, similar to those found in the julius library, into TensorFlow's tf.signal module. The requester highlights the current lack of comprehensive audio data augmentation tools within TensorFlow compared to PyTorch and suggests that adding these capabilities would enhance audio model training by enabling native, efficient preprocessing and augmentation workflows.
4. [DOCS] Missing complex input for Round op: This issue reports a documentation bug in TensorFlow where the Round operation is described as supporting complex tensor inputs, but in practice, attempting to use a complex tensor with this operation results in an error, requiring users to manually round the real and imaginary parts separately. The user provides a reproducible example on MacOS with TensorFlow 2.15.0 and Python 3.9, demonstrating that the operation fails with a device not found error for complex inputs, indicating a discrepancy between the documentation and actual functionality.
5. tf.raw_ops.Unbatch aborts with "Check failed: d < dims()": This issue reports a bug in TensorFlow version 2.17 where the operation tf.raw_ops.Unbatch aborts with a fatal check failure error "Check failed: d < dims()" when executed. The problem occurs on Linux Ubuntu 20.04.3 LTS with Python 3.11.8, and the user has provided a minimal reproducible example demonstrating that the error arises due to an invalid dimension check within the unbatch operation.

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: 20

Summarized Issues:

• CUDA Kernel Illegal Memory Accesses: Multiple CUDA kernels in TensorFlow 2.20 on Ubuntu 22.04 with CUDA 12.5.1 exhibit illegal out-of-bounds memory reads or writes during execution, causing crashes or undefined behavior. These issues affect various operations including ParameterizedTruncatedNormal, PopulationCount, ResourceApplyAdadelta, ResourceScatterNdUpdate, ResourceScatterUpdate, ReverseSequence, segment_sum, SpaceToDepth, SparseConcat, SparseSegmentSum, Svd, Transpose, UnsortedSegmentSum, MatrixDiagPart, SplitOpKernel, and PropagateWhereIndicesKernel.
• issues/104076, issues/104077, issues/104078, issues/104079, issues/104080, issues/104257, issues/104258, issues/104259, issues/104260, issues/104261, issues/104359, issues/104360, issues/104361, issues/104363, issues/104364, issues/104365

• Build Errors with TensorFlow Lite and XNNPACK: A build error occurs when compiling TensorFlow Lite with the XNNPACK delegate enabled on Ubuntu, caused by mismatches and missing declarations related to FileDescriptor and FileDescriptorView classes in the file_util.cc source file. This prevents successful compilation and integration of the delegate.
• issues/104155

• TensorFlow to TOSA Conversion Type Mismatch: The --tfl-to-tosa-pipeline conversion fails to handle the tfl.fully_connected operation correctly, resulting in a type mismatch error where tosa.reshape expects a tosa-conformant tensor but receives an incompatible quantized tensor. This blocks proper model conversion workflows.
• issues/104313

• TensorFlow Java Repository Unarchive Request: The TensorFlow SIG JVM team requests unarchiving the tensorflow/java-ndarray repository, which is archived but still actively used by the Java client. They seek contact with TensorFlow maintainers to address ongoing usage and maintenance concerns.
• issues/104395

• KerasTensor Incompatibility with tape.watch: Using tape.watch on the output of a DenseNet121 layer, which is a KerasTensor, raises a ValueError because tape.watch expects a tf.Tensor, tf.Variable, or ExtensionType, not a KerasTensor. This causes issues in gradient tracking workflows involving Keras models.
• issues/104521

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: 2

Summarized Issues:

• Bug Reports and User Feedback: This topic covers issues where users report bugs or provide feedback about TensorFlow behavior. One issue involves a user reproducing a bug with TensorFlow Nightly and minimal code, leading to a request to stop spamming.
• issues/104238

• Build Failures and Compatibility Issues: This topic includes problems related to building TensorFlow on specific platforms and toolchains. One issue describes build failures on RockyLinux 9.6 with GCC toolsets 13-15 and Bazel 8.4.2, which were resolved by downgrading Bazel and switching to Clang.
• issues/104297

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. Tflite: Fix QuantizedMeanOrSum template type in refkernel: This pull request addresses a bug in TensorFlow Lite by fixing the template type used in the QuantizedMeanOrSum function within the reference kernel to prevent ReduceSum overflow for non-uint8 tensors by correctly passing the template type to GetTensorData.

• URL: pull/104108

• Merged: No

• Associated Commits: a66a7

2. Corrected padding in softmax. In FP16 without this the softmax for pa…: This pull request addresses a correction in the padding implementation of the softmax function for FP16 precision, preventing the softmax output from becoming infinite for padded zero values in the original image by properly handling cases where the padded values have zero numerator but a non-zero denominator.

• URL: pull/104247

• Merged: No

• Associated Commits: 0ca71

3. Update tfe_wrapper_monitoring_reader.cc: This pull request proposes an update to the file tfe_wrapper_monitoring_reader.cc by removing an extra semicolon after the string ("License"); to improve code correctness.

• URL: pull/104548

• Merged: No

• Associated Commits: 0df4b

Other Open Pull Requests

• Codebase linting and error fixing: This topic covers pull requests that address and fix line errors in the codebase using the ruff tool. These changes improve code quality and maintain consistency across the project by automating error detection and correction.
• pull/104553

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. My spam is commited: This pull request, titled "My spam is commited," contains a single commit with the message "my work is commited," but it was not merged into the main branch.

• URL: pull/104072

• Merged: No

• Associated Commits: 62890

2. Update README.md: This pull request proposes updates to the README.md file by adding alt text to the logo, fixing the PyPI badge link, and improving code comments, but it was not merged.

• URL: pull/104073

• Merged: No

• Associated Commits: c4152

3. [tosa] Fix tosa compile error: This pull request fixes a compile error in the TOSA component by changing the default assignment of ArrayRef from std::nullopt to an empty initializer, ensuring all related tests pass successfully.

• URL: pull/104129

• Merged: Yes

• Associated Commits: c8c90

Other Closed Pull Requests

• Documentation improvements: These pull requests focus on enhancing the project's documentation and code quality. One PR proposes adding a comprehensive guide for setting up and installing TensorFlow, while another aims to reformat the code and apply various fixes to improve readability and maintainability.
• [pull/104295, pull/104403]

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
ashvinashivin0-sketch	0	0	38	0
kokol16	0	0	24	0
Venkat6871	0	0	0	21
ILCSFNO	4	4	7	4
khteh	0	0	6	3
infiWang	6	1	0	1
shank87414	0	0	8	0
souhil25	4	2	0	1
tamama-plb	0	0	1	5
jameslovespancakes	4	1	0	0