discussion, and please direct specific questions to
[Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow).**

The TensorFlow project strives to abide by generally accepted best practices in
open-source software development.

## Patching guidelines

Follow these steps to patch a specific version of TensorFlow, for example, to
apply fixes to bugs or security vulnerabilities:

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/tf_status.h"

// --------------------------------------------------------------------------
// C API for Graph. The API is under active development and eventually
// should allow registering a plugin graph optimizer with TensorFlow.
//
// Conventions:
//   * Struct prefix indicates whether struct fields should be filled by the
//     plugin or core implementation:

    [tensorflow/build Docker images](https://hub.docker.com/r/tensorflow/build)
    (`tensorflow/tensorflow:devel` and `tensorflow/tensorflow:devel-gpu` are no
    longer supported for) development. Use TF SIG Build Dockerfiles in
    development to avoid installing the packages directly on your system (in
    which case remember to change the directory from `/root` to `/tensorflow`

// TODO(jeff,sanjay):
// - export functions to set Config fields

// --------------------------------------------------------------------------
// The new graph construction API, still under development.

// Represents a computation graph.  Graphs may be shared between sessions.
// Graphs are thread-safe when used as directed below.
typedef struct TF_Graph TF_Graph;

// Return a new graph object.

ln -s "/usr/include/linux" "${TARGET}/usr/include/linux"
ln -s "/usr/include/asm-generic" "${TARGET}/usr/include/asm-generic"
ln -s "/usr/include/aarch64-linux-gnu/asm" "${TARGET}/usr/include/asm"

# Download glibc's shared and development libraries based on the value of the
# `VERSION` parameter.
# Note: 'Templatizing' this and the other conditional branches would require
# defining several variables (version, os, path) making it difficult to maintain

#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_status.h"
#include "xla/pjrt/c/pjrt_c_api.h"

// --------------------------------------------------------------------------
// C API for device. The API is under active development and eventually
// should allow registering a plugin device with TensorFlow.

#ifdef __cplusplus
extern "C" {
#endif

// TF_Device is a C wrapper to the C++ TF Device class. This is to be passed

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference
functions](https://www.tensorflow.org/guide/create_op#define_the_op_interface)

    visibility = ["//visibility:public"],
)

# This flag specifies whether TensorFlow 2.0 API should be built instead
# of 1.* API. Note that TensorFlow 2.0 API is currently under development.
config_setting(
    name = "api_version_2",
    define_values = {"tf_api_version": "2"},
    visibility = ["//visibility:public"],
)

# This flag enables experimental MLIR support.
config_setting(

and
[issues tagged with `2.0`](https://github.com/tensorflow/tensorflow/issues?q=is%3Aopen+is%3Aissue+label%3A2.0)
on GitHub for insight into recent issues and development progress.

If you experience any snags when using TF 2.0, please let us know at the
[TF 2.0 Testing User Group](https://groups.google.com/a/tensorflow.org/forum/?utm_medium=email&utm_source=footer#!forum/testing).