in a discouraged way (e.g. running untrusted models or checkpoints, data parsing
outside of the safe formats, etc.) are not treated as vulnerabilities..

### Reporting process

Please use [Google Bug Hunters reporting form](https://g.co/vulnz) to report
security vulnerabilities. Please include the following information along with
your report:

  - A descriptive title

---
name: TensorFlow Lite Converter Issue
about: Use this template for reporting issues during model conversion to TFLite
labels: 'TFLiteConverter'

---

### 1. System information

- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installation (pip package or built from source):
- TensorFlow library (version, if pip package or github SHA, if built from source):

### 2. Code

  virtual Status InputLength(const char* input_name, int* length) = 0;
  virtual Status OutputLength(const char* output_name, int* length) = 0;

  // Set stack trace to be used for potential async error reporting.
  virtual void SetStackTrace(ManagedStackTrace stack_trace) = 0;

  virtual const tensorflow::AbstractOpAttrs* GetOpAttrs() const = 0;
  virtual void AddAttrs(const AbstractOpAttrs* op_attrs) = 0;

> TensorFlow repo. This warning will be removed when the contents of this
> directory are stable and appropriate documentation around its usage is in
> place.

Maintainer: TensorFlow DevInfra

Issue Reporting: File an issue against this repo and tag
[@devinfra](https://github.com/orgs/tensorflow/teams/devinfra)

********************************************************************************

---
name: TensorFlow Lite Op Request
about: Use this template for reporting Lite ops you are using or missing
labels: 'comp:lite'

---

**System information**
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- 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
```

# Official CI Directory

Maintainer: TensorFlow and TensorFlow DevInfra

Issue Reporting: File an issue against this repo and tag
[@devinfra](https://github.com/orgs/tensorflow/teams/devinfra)

********************************************************************************

## TensorFlow's Official CI and Build/Test Scripts

TensorFlow's official CI jobs run the scripts in this folder. Our internal CI

the local wheel file specified in the `requirements_lock_<python_version>.txt`.

Packages are imported one by one in alphabetical order during runtime.

The test doesn't identify package's order-dependent issues; for instance,
importing "tf.foo" followed by "tf.bar" won't reveal that "tf.bar" depends on
"tf.foo" being imported first.

The `_api/v2/api_packages.txt` file is generated during the TensorFlow API v2

# ==============================================================================
"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in

if [[ "$TFCI_DOCKER_PULL_ENABLE" == 1 ]]; then
  # Simple retry logic for docker-pull errors. Sleeps for 15s if a pull fails.
  # Pulling an already-pulled container image will finish instantly, so
  # repeating the command costs nothing.
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 15
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 15
  docker pull "$TFCI_DOCKER_IMAGE"
fi 

if [[ "$TFCI_DOCKER_REBUILD_ENABLE" == 1 ]]; then

*   Added `keras.export.ExportArchive` class for low-level customization of the process of exporting SavedModel artifacts for inference. Both ways of exporting models are based on `tf.function` tracing and produce a TF program composed of TF ops. They are meant primarily for environments where the TF runtime is available, but not the Python interpreter, as is typical for production...