}

void TFE_OpAddInputList(TFE_Op* op, TFE_TensorHandle** inputs, int num_inputs,
                        TF_Status* status) {
  status->status = tensorflow::unwrap(op)->AddInputList(
      {reinterpret_cast<tensorflow::AbstractTensorHandle**>(
           tensorflow::unwrap(inputs)),
       static_cast<size_t>(num_inputs)});
}

extern int TFE_OpGetFlatInputCount(const TFE_Op* op, TF_Status* status) {

    ExecutableType** out_executable) {
  DCHECK_NE(out_executable, nullptr);
  VLOG(2) << "DeviceCompiler::Compile " << DebugString();

  if (VLOG_IS_ON(2)) {
    VLOG(2) << "num_inputs=" << args.size();
    for (int i = 0, end = args.size(); i < end; i++) {
      VLOG(3) << i << ": " << args[i].HumanString();
    }
  }
  TF_ASSIGN_OR_RETURN(auto signature,

// TODO(ycao): Support computation with compile-time constant, which requires
// non-trivial input mapping as implemented now.
void GetInputMappingForMlir(int num_inputs, std::vector<int>* input_mapping) {
  input_mapping->resize(num_inputs, 0);
  std::iota(input_mapping->begin(), input_mapping->end(), 0);
}

static void RegisterDialects(mlir::DialectRegistry& registry) {

  }
}

bool TF_IsRefInput(TF_OpKernelContext* ctx, int i, TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelContext*>(ctx);
  if (i < 0 || i >= cc_ctx->num_inputs()) {
    TF_SetStatus(status, TF_OUT_OF_RANGE, "input index out of range");
    return false;
  }
  TF_SetStatus(status, TF_OK, "");
  return cc_ctx->input_is_ref(i);
}

#ifndef IS_MOBILE_PLATFORM

      send_recv_nodes.push_back(n);
    }
  }
  EXPECT_EQ(num_send_from_host, 1);
  EXPECT_EQ(num_recv_at_host, 1);
  for (Node *n : send_recv_nodes) {
    Node *input_node;
    TF_CHECK_OK(n->input_node(n->num_inputs() - 1, &input_node));
    EXPECT_EQ(input_node, key_placeholder);

    bool has_control_edge_to_sequencer = false;
    for (const Edge *e : n->out_edges()) {
      if (e->IsControlEdge() && e->dst() == sequencer) {

    : OpKernel(ctx), platform_info_(XlaPlatformInfoFromDevice(ctx->device())) {}

void XlaRunOp::Compute(OpKernelContext* ctx) {
  VLOG(3) << "XlaRunOp " << def().name();
  Tensor key_tensor = ctx->input(ctx->num_inputs() - 1);

  bool use_pjrt =
      GetXlaOpsCommonFlags()
          ->tf_xla_use_device_api.IsEnabledInXlaCompileAndRunForDevice(
              platform_info_.device_type());

  if (use_pjrt) {

	// do not block indefinitely (e.g. apply a timeout).
	Close() error

	// NumInput returns the number of placeholder parameters.
	//
	// If NumInput returns >= 0, the sql package will sanity check
	// argument counts from callers and return errors to the caller
	// before the statement's Exec or Query methods are called.
	//
	// NumInput may also return -1, if the driver doesn't know

      IsSingleCallRegion(while_region.getBody()), while_arg_matcher);

  // All existing inputs to while region are inputs to the functional while.
  auto new_inputs = llvm::to_vector<4>(while_region.getOperands());

  // All existing results will also be generated by the functional while.
  auto new_result_types = llvm::to_vector<4>(while_region.getResultTypes());

					return err
				}
				covervarsoutfile = outputfiles[0]
				outputfiles = outputfiles[1:]
				numInputs := len(flag.Args())
				numOutputs := len(outputfiles)
				if numOutputs != numInputs {
					return fmt.Errorf("number of output files (%d) not equal to number of input files (%d)", numOutputs, numInputs)
				}
				if err := readPackageConfig(*pkgcfg); err != nil {
					return err
				}
				return nil

/**
 * Tests for SimpleGenericBloomFilter and derived BloomFilter views.
 *
 * @author Dimitris Andreou
 */
public class BloomFilterTest extends TestCase {
  private static final int NUM_PUTS = 100_000;
  private static final ThreadLocal<Random> random =
      new ThreadLocal<Random>() {
        @Override
        protected Random initialValue() {
          return new Random();
        }
      };