"//conditions:default": ["@com_github_grpc_grpc//:grpc++"],
    }),
)
# copybara:comment_end

# A shared object which includes registration mechanisms for ops and
# kernels. Does not include the implementations of any ops or kernels. Instead,
# the library which loads libtensorflow_framework.so
# (e.g. _pywrap_tensorflow_internal.so for Python, libtensorflow.so for the C

# Where component owners are known, add them here.

/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

# Only include debug info for files under tensorflow/, excluding kernels, to
# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g

  # TODO(gunan): Add sanity checks to loaded modules here.

  # Load first party dynamic kernels.
  _tf_dir = _os.path.dirname(_current_file_location)
  _kernel_dir = _os.path.join(_tf_dir, "core", "kernels")
  if _os.path.exists(_kernel_dir):
    _ll.load_library(_kernel_dir)

  # Load third party dynamic kernels.
  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")

        "//tensorflow/core/common_runtime/next_pluggable_device/c:tf_rendezvous_c_api",
        "@local_tsl//tsl/platform",
    ],
)

tf_cuda_library(
    name = "kernels",
    srcs = [
        "kernels.cc",
    ],
    hdrs = [
        "kernels.h",
    ],
    copts = tf_copts(),
    visibility = ["//visibility:public"],
    deps = [
        ":c_api_internal",
        ":c_api_macros_hdrs",

  # TODO(gunan): Add sanity checks to loaded modules here.

  # Load first party dynamic kernels.
  _tf_dir = _os.path.dirname(_current_file_location)
  _kernel_dir = _os.path.join(_tf_dir, "core", "kernels")
  if _os.path.exists(_kernel_dir):
    _ll.load_library(_kernel_dir)

  # Load third party dynamic kernels.
  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")

	}

	// legacy linux indicator for printing warnings
	// about older Linux kernels and Go runtime.
	return currentKernel < kernel.Version(4, 0, 0)
}

func setMaxResources(ctx serverCtxt) (err error) {
	// Set the Go runtime max threads threshold to 90% of kernel setting.
	sysMaxThreads, err := sys.GetMaxThreads()
	if err == nil {
		minioMaxThreads := (sysMaxThreads * 90) / 100

```

TensorFlow kernels and TensorFlow's dependencies are still not built with
debugging information with `--config=dbg`, as issues occur on Linux if
there is too much debug info (see [this GitHub
issue](https://github.com/tensorflow/tensorflow/issues/48919) for context). If
you want to debug a kernel, you can compile specific files with `-g` using the

* Intégration Python facile avec **Jupyter Kernels** pour le développement à distance ou intra-Docker avec des extensions comme Atom Hydrogen ou Visual Studio Code Jupyter.
* Frontend **Vue** :
    * Généré avec Vue CLI.
    * Gestion de l'**Authentification JWT**.

* Простая интеграция Python с **Jupyter Kernels** для разработки удалённо или в Docker с расширениями похожими на Atom Hydrogen или Visual Studio Code Jupyter.
* Фронтенд построен на фреймворке **Vue**:
    * Сгенерирован с помощью Vue CLI.