# 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

        "//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

  # 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",
        "@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",

```

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

	}

	// 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

TF_ImportGraphDefOptionsSetValidateColocationConstraints(
    TF_ImportGraphDefOptions* opts, unsigned char enable);

// Load the library specified by library_filename and register the pluggable
// device and related kernels present in that library. This function is not
// supported on embedded on mobile and embedded platforms and will fail if
// called.
//
// Pass "library_filename" to a platform-specific mechanism for dynamically

// Kernel definition information.

// Returns a serialized KernelList protocol buffer containing KernelDefs for all
// registered kernels.
TF_CAPI_EXPORT extern TF_Buffer* TF_GetAllRegisteredKernels(TF_Status* status);

// Returns a serialized KernelList protocol buffer containing KernelDefs for all
// kernels registered for the operation named `name`.

//tensorflow/cc/saved_model:saved_model_half_plus_two
//tensorflow:no_tensorflow_py_deps
//tensorflow/tools/pip_package:win_pip_package_marker
//tensorflow/core:image_testdata
//tensorflow/core/kernels/cloud:bigquery_reader_ops
//tensorflow/python:extra_py_tests_deps
//tensorflow/python:mixed_precision
//tensorflow/python:tf_optimizer
//tensorflow/python:compare_test_proto_py

        mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],