.DS_Store
.ipynb_checkpoints
node_modules
/.bazelrc.user
/.tf_configure.bazelrc
/xla_configure.bazelrc
/bazel-*
/bazel_pip
/tools/python_bin_path.sh
/tensorflow/tools/git/gen
/pip_test
/_python_build
*.pyc
__pycache__
*.swp
.vscode/
cmake_build/
tensorflow/contrib/cmake/_build/
.idea/**
/build/
[Bb]uild/
/build_output/
/tensorflow/core/util/version_info.cc
/tensorflow/python/framework/fast_tensor_util.cpp

      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*enable_xla_compilation=*/false,
          /*gpu_memory_allow_growth=*/true, /*num_cpu_devices=*/2),
      TF_DeleteBuffer);
  TFE_ContextOptionsSetConfig(opts.get(), config->data, config->length,
                              status.get());

      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*xla*/ false,
          /* gpu_memory_allow_growth */ true, /* num_cpu_devices */
          2),
      TF_DeleteBuffer);
  TFE_ContextOptionsSetConfig(opts.get(), config->data, config->length,

    if (lowercased_title.includes('jax')) {
      assignees.push('hawkinsp', 'yashk2810', 'skye');
    }
    if (lowercased_title.includes('xla') || lowercased_title.includes('gpu')) {
      assignees.push('cheshire', 'gcforster', 'reedwm', 'chsigg', 'xla-rotation');
    }
    if (lowercased_title.includes('tf')) {
      assignees.push('rohan100jain', 'bfontain');
    }
  }

**Linux XLA**                 | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.html)         | TBA

        "@com_google_absl//absl/container:flat_hash_map",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/time",
        "@local_xla//xla/tsl/c:tsl_status_internal",
        "@local_xla//xla/tsl/distributed_runtime/coordination:coordination_service_agent",
    ],
    alwayslink = 1,
)

cc_library(
    name = "c_api_experimental_reader",
    testonly = True,

        write_to_bazelrc(
            'build --copt="-DEIGEN_ALTIVEC_ENABLE_MMA_DYNAMIC_DISPATCH=1"')

  with_xla_support = environ_cp.get('TF_ENABLE_XLA', None)
  if with_xla_support is not None:
    write_to_bazelrc('build --define=with_xla_support=%s' %
                     ('true' if int(with_xla_support) else 'false'))

  set_action_env_var(
      environ_cp, 'TF_NEED_ROCM', 'ROCm', False, bazel_config_name='rocm')

#include <cstdint>

#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/kernels.h"
#include "tensorflow/c/kernels_experimental.h"
#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

reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
documentation should be safe, while some of the testing and debugging tools that

  }
  std::sort(names.begin(), names.end());
  return names;
}

CSession::CSession(TF_Graph* graph, TF_Status* s, bool use_XLA) {
  TF_SessionOptions* opts = TF_NewSessionOptions();
  TF_EnableXLACompilation(opts, use_XLA);
  session_ = TF_NewSession(graph, opts, s);
  TF_DeleteSessionOptions(opts);
}

CSession::CSession(TF_Session* session) : session_(session) {}