# Do not remove this line; See https://github.com/tensorflow/tensorflow/issues/42596
from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow  # pylint: disable=unused-import
from tensorflow.python.tools import module_util as _module_util
from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader

# Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.

/tensorflow/c/eager @qqfish
/tensorflow/core/common_runtime/eager @qqfish
/tenosrflow/core/debug @caisq
/tensorflow/core/kernels/mkl/ @penpornk
/tensorflow/core/kernels/sparse/ @penpornk
/tensorflow/core/nccl/ @azaks2 @chsigg
/tensorflow/python/autograph/ @mdanatg
/tensorflow/python/debug @caisq
/tensorflow/python/eager @rohan100jain
/tensorflow/tools/docs/ @markdaoust
/tensorflow/compiler/mlir/ @aminim

#include "tensorflow/core/platform/init_main.h"
#include "tensorflow/core/platform/mutex.h"
#include "tensorflow/core/platform/net.h"
#include "tensorflow/core/platform/platform.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/protobuf/config.pb.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

using tensorflow::FunctionDef;
using tensorflow::Node;
using tensorflow::NodeBuilder;
using tensorflow::Status;

    tensorflow/c/tf_buffer.h  \
    tensorflow/c/tf_datatype.h \
    tensorflow/c/tf_status.h \
    tensorflow/c/tf_tensor.h \
    tensorflow/c/tf_tensor_helper.h \
    tensorflow/c/tf_tstring.h \
    tensorflow/c/tf_file_statistics.h \
    tensorflow/c/tensor_interface.h \
    tensorflow/c/c_api_macros.h \
    tensorflow/c/c_api_experimental.h \
    ${LIB_PKG}/include/tensorflow/c
  cp tensorflow/c/eager/c_api.h \

        "//tensorflow/compiler/mlir/quantization/tensorflow/python:quantize_model_cc_impl",
        "//tensorflow/compiler/mlir/quantization/tensorflow:passes",
        "//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/compiler/mlir/tensorflow/c:mlir_c_api_registration",
        "//tensorflow/compiler/mlir/tensorflow:error_util",
        "//tensorflow/compiler/mlir/tensorflow:mlir_import_options",

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

# requiring conditional path adjustments throughout the CI scripts.
# Note: This does not work for `docker cp` commands.
# For a little more detail, see:
# https://github.com/tensorflow/tensorflow/blob/cc3006af6fea8d2a1360b3b5e65f9d14bbdb7094/ci/devinfra/docker/windows2022/Dockerfile#L196
TFCI_OUTPUT_WIN_DOCKER_DIR='C:/drive_t'

# Docker on Windows doesn't support the `host` networking mode, and so

# Release 2.11.1

**Note**: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin.

_current_module.__path__ = [_module_dir] + _current_module.__path__

_CONTRIB_WARNING = """
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.
"""

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML