# All required CUDA packages
cuda-compat-12-8
cuda-command-line-tools-12-8
cuda-cudart-dev-12-8
cuda-nvcc-12-8
cuda-cupti-12-8
cuda-nvprune-12-8
cuda-libraries-12-8
cuda-libraries-dev-12-8
cuda-nvml-dev-12-8
libcufft-12-8
libcurand-12-8
libcusolver-dev-12-8
libcusparse-dev-12-8
libcublas-12-8
libcublas-dev-12-8
libnccl-dev=2.25.1-1+cuda12.8
libnccl2=2.25.1-1+cuda12.8

# All required CUDA packages
cuda-compat-13-0
cuda-command-line-tools-13-0
cuda-cudart-dev-13-0
cuda-nvcc-13-0
cuda-cupti-13-0
cuda-nvprune-13-0
cuda-libraries-13-0
cuda-libraries-dev-13-0
cuda-nvml-dev-13-0
libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0

# All required CUDA packages
cuda-compat-12-1
cuda-command-line-tools-12-1
cuda-cudart-dev-12-1
cuda-nvcc-12-1
cuda-cupti-12-1
cuda-nvprune-12-1
cuda-libraries-12-1
cuda-libraries-dev-12-1
cuda-nvml-dev-12-1
libcufft-12-1
libcurand-12-1
libcusolver-dev-12-1
libcusparse-dev-12-1
libcublas-12-1
libcublas-dev-12-1
libnccl-dev=2.18.3-1+cuda12.1
libnccl2=2.18.3-1+cuda12.1

# packages only provide the "0.10-2build1" version. We use patchelf to manipulate
# certain shared libraries during the wheel building process (https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/build_pip_package.sh#L255-L262).
# When we use Patchelf versions <0.12, those shared libraries end up with a

# All required CUDA packages
cuda-compat-12-1
cuda-command-line-tools-12-1
cuda-cudart-dev-12-1
cuda-nvcc-12-1
cuda-cupti-12-1
cuda-nvprune-12-1
cuda-libraries-12-1
cuda-libraries-dev-12-1
cuda-nvml-dev-12-1
libcufft-12-1
libcurand-12-1
libcusolver-dev-12-1
libcusparse-dev-12-1
libcublas-12-1
libcublas-dev-12-1
libnccl-dev=2.18.3-1+cuda12.1
libnccl2=2.18.3-1+cuda12.1

# All required CUDA packages
cuda-compat-12-3
cuda-command-line-tools-12-3
cuda-cudart-dev-12-3
cuda-nvcc-12-3
cuda-cupti-12-3
cuda-nvprune-12-3
cuda-libraries-12-3
cuda-libraries-dev-12-3
cuda-nvml-dev-12-3
libcufft-12-3
libcurand-12-3
libcusolver-dev-12-3
libcusparse-dev-12-3
libcublas-12-3
libcublas-dev-12-3
libnccl-dev=2.19.3-1+cuda12.3
libnccl2=2.19.3-1+cuda12.3

_current_module.__path__ = [_module_dir] + _current_module.__path__


# Enable TF2 behaviors
from tensorflow.python.compat import v2_compat as _compat
_compat.enable_v2_behavior()
_major_api_version = 2


# Load all plugin libraries from site-packages/tensorflow-plugins if we are
# running under pip.
# TODO(gunan): Find a better location for this code snippet.
from tensorflow.python.framework import load_library as _ll

formats that can be processed by TensorFlow.

These modifications and conversions are handled by a variety of libraries that
have different security properties and provide different levels of confidence
when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,

	Dynlink    = flag.Bool("dynlink", false, "support references to Go symbols defined in other shared libraries")
	Linkshared = flag.Bool("linkshared", false, "generate code that will be linked against Go shared libraries")
	AllErrors  = flag.Bool("e", false, "no limit on number of errors reported")

      "keras.api._v1.keras.__internal__.legacy.rnn_cell")
_current_module.nn.__path__ = [_module_dir] + _current_module.nn.__path__

del importlib

# Load all plugin libraries from site-packages/tensorflow-plugins if we are
# running under pip.
# TODO(gunan): Find a better location for this code snippet.
from tensorflow.python.framework import load_library as _ll