// named job. The server can communicate with any other server in the same
// cluster.

// In-process TensorFlow server.
typedef struct TF_Server TF_Server;

// Creates a new in-process TensorFlow server configured using a serialized
// ServerDef protocol buffer provided via `proto` and `proto_len`.
//
// The server will not serve any requests until TF_ServerStart is invoked.

  # At most 1 GPU platform can be configured.
  gpu_platform_count = 0
  if environ_cp.get('TF_NEED_ROCM') == '1':
    gpu_platform_count += 1
  if environ_cp.get('TF_NEED_CUDA') == '1':
    gpu_platform_count += 1
  if gpu_platform_count >= 2:
    raise UserInputError('CUDA / ROCm are mututally exclusive. '
                         'At most 1 GPU platform can be configured.')

  set_cc_opt_flags(environ_cp)

#     nogcp:        Disable GCS support.
#     nohdfs:       Disable hadoop hdfs support.
#     nonccl:       Disable nccl support.
#
#
# Remote build execution options (only configured to work with TF team projects for now.)
#     rbe_base:  General RBE options shared by all flavors.
#     rbe_linux: General RBE options used on all linux builds.

  EXPECT_FALSE(executed);
  ASSERT_FALSE(TF_GetCode(status.get()) == TF_OK);

  // Custom devices can refuse to do type-based dispatch (as hcustom1 is
  // configured to do)
  matmul.reset(MatMulOp(context.get(), hcustom1.get(), hcpu.get()));
  num_retvals = 1;
  executed = false;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());
  EXPECT_FALSE(executed);

                                                  TF_Status* status);

// Set logical devices to the context's device manager.
// If logical devices are already configured at context initialization
// through TFE_ContextOptions, this method should not be called.
TF_CAPI_EXPORT extern void TFE_SetLogicalCpuDevices(TFE_Context* ctx,
                                                    int num_cpus,

*   Adds a family= attribute in `tf.summary` ops to allow controlling the tab
    name used in Tensorboard for organizing summaries.
*   When GPU is configured, do not require --config=cuda, instead, automatically
    build for GPU if this is requested in the configure script.
*   Fix incorrect sampling of small probabilities in CPU/GPU multinomial.