// Test we can retrieve function OpDef from graph
  TF_Buffer* buffer = TF_NewBuffer();
  TF_GraphGetOpDef(host_graph_, func_name_, buffer, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Sanity check returned OpDef
  string data(static_cast<const char*>(buffer->data), buffer->length);
  OpDef op_def;
  op_def.ParseFromString(data);
  EXPECT_EQ(op_def.name(), func_name_);

                                           TF_Status* status) {
  const tensorflow::OpDef* op_def = nullptr;
  status->status =
      tensorflow::OpRegistry::Global()->LookUpOpDef(op_name, &op_def);
  if (!status->status.ok()) return nullptr;

  if (input_index >= op_def->input_arg_size() || input_index < 0) {
    status->status = tensorflow::errors::InvalidArgument(

                      TF_Buffer* output_op_def, TF_Status* status) {
  const OpDef* op_def;
  {
    mutex_lock l(graph->mu);
    status->status = graph->graph.op_registry()->LookUpOpDef(op_name, &op_def);
    if (!status->status.ok()) return;
  }
  status->status = MessageToBuffer(*op_def, output_op_def);
}

void TF_GraphVersions(TF_Graph* graph, TF_Buffer* output_version_def,

    ASSERT_GE(op_list.op_size(), 1);
    typedef tensorflow::protobuf::RepeatedPtrField<tensorflow::OpDef> OpDefs;
    const OpDefs& ops = op_list.op();
    bool found = std::find_if(ops.begin(), ops.end(),
                              [](const tensorflow::OpDef& op_def) {
                                return op_def.name() == "TestCApi";
                              }) != ops.end();
    EXPECT_TRUE(found);

#include "tensorflow/c/c_test_util.h"

#include "tensorflow/c/c_api_experimental.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/framework/op_def.pb.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/public/session_options.h"

//
// This object maps the name of a TensorFlow operation to a description of the
// API to generate for it, as defined by the ApiDef protocol buffer (
// https://www.tensorflow.org/code/tensorflow/core/framework/api_def.proto)
//
// The ApiDef messages are typically used to generate convenience wrapper
// functions for TensorFlow operations in various language bindings.

*   Improve implicit broadcasting lowering.
*   Improving stability of GCS/BigQuery clients by a faster retrying of stale
    transmissions.
*   Remove OpKernelConstruction::op_def() as part of minimizing proto
    dependencies.
*   VectorLaplaceDiag distribution added.
*   Android demo no longer requires libtensorflow_demo.so to run
    (libtensorflow_inference.so still required)

compiler/mlir/tfrt/transforms/lhlo_gpu_to_tfrt_gpu,tensorflow/compiler/mlir/tfrt/transforms/mlrt,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/runtime_fallback/test,tensorflow/core/runtime_fallback/test/gpu,tensorflow/core/runtime_fallback/test/saved_model,tensorflow/core/runtime_fallback/test...