bazel query --keep_going 'kind(py_test, //tensorflow/python/...) - attr("tags", "no_pip|manual", //tensorflow/python/...)' | grep -v -f $BATS_TEST_TMPDIR/ignore_deps_for_these_packages | paste -sd "+" - > $BATS_TEST_TMPDIR/deps
  # Find all one-step dependencies of those tests which are from //tensorflow
  # (since external deps will come from Python-level pip dependencies),

    see! value: render: shell validations: required: true

-   type: textarea id: logs attributes: label: Relevant log output description:
    Please copy and paste any relevant log output. This will be automatically

    git config --system --add safe.directory '*'
    git config --system protocol.file.allow always

    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files
    if [[ "$(git rev-parse --abbrev-ref HEAD)" == "pull_branch" ]]; then

  bazel cquery --keep_going 'kind(py_test, //tensorflow/python/...) - attr("tags", "no_pip|manual", //tensorflow/python/...)' | grep -v -f $BATS_TEST_TMPDIR/ignore_deps_for_these_packages | paste -sd "+" - > $BATS_TEST_TMPDIR/deps
  # Find all one-step dependencies of those tests which are from //tensorflow
  # (since external deps will come from Python-level pip dependencies),

  // `backward_function_deleter`) to compute jvps for this operation. If
  // `forward_function` is null, a GradientTape is used on the backward function
  // to compute the jvp, which will waste computation when executing eagerly.
  //
  // Unlike GradientTape::RecordOperation, Accumulate runs gradient computation
  // immediately. It stores the results, which feed into Accumulate for future

```
(You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

#### Option B: Paste your code here or provide a link to a custom end-to-end colab

```
(You can paste links or attach files by dragging & dropping them below)

# Usage: Go to
# https://github.com/tensorflow/tensorflow/actions/workflows/release-branch-cherrypick.yml
# and click "Run Workflow." Leave "Use Workflow From" set to "master", then
# input the branch name and paste the cherry-pick commit and click Run. A PR
# will be created.

name: Release Branch Cherrypick
on:
  workflow_dispatch:
    inputs:
      # We use this instead of the "run on branch" argument because GitHub looks

HuiyangFei, Jacker, Jan HüNnemeyer, Jason Taylor, Jason Zaman, Jesse,
Jiang,Zhoulong, Jiawei Zhang, Jie, Joe Yearsley, Johannes Schmitz, Jon Perl, Jon
Triebenbach, Jonathan, Jonathan Hseu, Jongmin Park, Justin Shenk, ******@****.***,
Kate Hodesdon, Kb Sriram, Keishi Hattori, Kenneth Blomqvist, Koan-Sin Tan, Li
Liangbin, Li, Yiqiang, Loo Rong Jie, Madiyar, Mahmoud Abuzaina, Mark Ryan, Matt
Dodge, mbhuiyan, melvinljy96, Miguel Mota, Nafis Sadat, Nathan Luehr, naurril,

- TensorFlow installed from (source or binary):
- TensorFlow version (or github SHA if from source):


**Provide the text output from tflite_convert**

```
# Copy and paste here
```

**Standalone code to reproduce the issue** 
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/Jupyter/any notebook.

      value:
      render: shell
    validations:
      required: true
  - type: textarea
    id: logs
    attributes:
      label: Relevant log output
      description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.