using tensorflow::Status;
using tensorflow::unwrap;
using tensorflow::wrap;
using tensorflow::tracing::CreateTracingExecutionContext;
using tensorflow::tracing::SetDefaultTracingEngine;
using tensorflow::tracing::TracingContext;
using tensorflow::tracing::TracingOperation;
using tensorflow::tracing::TracingTensorHandle;

void TF_SetTracingImplementation(const char* name, TF_Status* s) {

#define TENSORFLOW_C_EAGER_GRAPH_FUNCTION_H_

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/refcount.h"
namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);

                    absl::Span<AbstractTensorHandle*> outputs) {
  if (!isa<ImmediateExecutionContext>(ctx)) {
    // TODO(b/168850692): Fix this.
    return errors::Unimplemented(
        "BroadcastMul is not supported in tracing mode yet.");
  }
  auto imm_ctx = dyn_cast<ImmediateExecutionContext>(ctx);
  AbstractTensorPtr minus_1(imm_ctx->CreateInt32Scalar(-1));
  ImmediateTensorHandlePtr dim(imm_ctx->CreateLocalHandle(minus_1.get()));

#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Abstract interface to an operation.
// This interface allows building and executing an operation in either
// tracing or immediate execution mode.
class AbstractOperation {
 protected:
  enum AbstractOperationKind {
    kGraph,
    kMlir,
    kEager,
    kTfrt,
    kTape,
    kOpHandler
  };

build --copt=-Wno-gnu-offsetof-extensions

# Store performance profiling log in the mounted artifact directory.
# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling
build --profile=/tf/pkg/profile.json.gz

# Use the rebuilt gcc toolchain to compile for manylinux2014

TF_CAPI_EXPORT unsigned char TFE_ContextHasFunction(TFE_Context* ctx,
                                                    const char* name);

// Enables tracing of RunMetadata on the ops executed from this context.
TF_CAPI_EXPORT extern void TFE_ContextEnableRunMetadata(TFE_Context* ctx);

// Disables tracing of RunMetadata on the ops executed from this context.
TF_CAPI_EXPORT extern void TFE_ContextDisableRunMetadata(TFE_Context* ctx);

        "//tensorflow/c/eager:abstract_operation",
        "//tensorflow/c/eager:abstract_tensor_handle",
        "//tensorflow/c/eager:c_api_unified_internal",
        "//tensorflow/c/eager:tracing_utils",
        "//tensorflow/core:framework",
        "//tensorflow/core/platform:errors",
        "@com_google_absl//absl/types:span",
    ],
)

cc_library(
    name = "io_ops",
    srcs = [

#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Builds and returns a `TracingContext` using the default tracing impl.
AbstractContext* BuildFunction(const char* fn_name);

// Creates parameters (placeholders) in the tracing `ctx` using the shape and
// dtype of `inputs`.
Status CreateParamsForInputs(AbstractContext* ctx,

TEST_P(CppGradients, TestSparseSoftmaxCrossEntropyWithLogitsGrad) {
  if (UseFunction()) {
    // TODO(b/168850692): Enable this.
    GTEST_SKIP() << "Can't take gradient of "
                    "SparseSoftmaxCrossEntropyWithLogits in tracing mode.";
  }

  // Score
  float X_vals[] = {1.0f, 2.0f, 3.0f, -5.0f, -4.0f, -3.0f, 2.0f, 0.0f, -1.0f};
  int64_t X_dims[] = {3, 3};
  AbstractTensorHandlePtr X;
  {
    AbstractTensorHandle* X_raw;

  ASSERT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(status.get()));

  TF_DeleteExecutionContext(graph_ctx);
}

// The above tests are run for a combination of:
// - graphdef and MLIR tracing engine
INSTANTIATE_TEST_SUITE_P(Tracing, UnifiedCAPI,
                         ::testing::Combine(::testing::Values("graphdef",
                                                              "mlir"),