#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/platform/base64.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/util/debug_data_dumper.h"

using tensorflow::errors::InvalidArgument;

namespace tensorflow {
namespace {

Status ValidateNonRefOutput(const Node* node, int idx) {
  const DataType& dt = node->output_type(idx);

                                                     TF_Status* status);

// Get a comma-separated list of op names executed in graph functions dispatched
// to `ctx`. This feature is currently only enabled for TFRT debug builds, for
// performance and simplicity reasons.
TF_CAPI_EXPORT extern void TFE_GetExecutedOpNames(TFE_Context* ctx,
                                                  TF_Buffer* buf,

    visibility = ["//visibility:public"],
)

config_setting(
    name = "linux_riscv64",
    values = {"cpu": "riscv64"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "debug",
    values = {
        "compilation_mode": "dbg",
    },
    visibility = ["//visibility:public"],
)

config_setting(
    name = "optimized",
    values = {
        "compilation_mode": "opt",

          *node_def = node->def();
        }
      }
      *graph_def.mutable_library() = graph.flib_def().ToProto();
      if (flags::Global().more_stack_traces.value()) {
        *graph_def.mutable_debug_info() = graph.BuildDebugInfo();
      }
      session->graph->mu.unlock();
      status->status = session->session->Extend(std::move(graph_def));
      if (!status->status.ok()) {

    *   tf.data input pipelines can now be executed in debug mode, which
        disables any asynchrony, parallelism, or non-determinism and forces
        Python execution (as opposed to trace-compiled graph execution) of
        user-defined functions passed into transformations such as `map`. The
        debug mode can be enabled through
        `tf.data.experimental.enable_debug_mode()`.
*   `tf.lite`

  void AsyncWait(TFE_Context* context, TF_Status* status) const;

  // Device strings for component devices that only include a
  // worker/task/replica if any of those differ across components. Useful for
  // printing debug messages.
  std::vector<std::string> SummarizeDeviceNames() const;

 private:
  // A sequence of device names, indicating which devices replicated operations
  // are forwarded to.

// explicitly by running a TPUReplicatedOutput operation on the parallel device.
//
// TODO(allenl): There are some use-cases that are only supported by copying to
// host at the moment (e.g. debug print on a tensor, .numpy(), etc.). We either
// need to return something here or address these use-cases one by one.
TFE_TensorHandle* CopyTensorFromParallelDevice(TFE_Context* context,