};

struct ConcatenationOptionsBuilder {
  typedef ConcatenationOptions Table;
  ::flatbuffers::FlatBufferBuilder &fbb_;
  ::flatbuffers::uoffset_t start_;
  void add_axis(int32_t axis) {
    fbb_.AddElement<int32_t>(ConcatenationOptions::VT_AXIS, axis, 0);
  }
  void add_fused_activation_function(tflite::ActivationFunctionType fused_activation_function) {

	local got
	got=$(mc cat "$2" | sha256sum)

	if [ "${expected}" != "${got}" ]; then
		echo "mismatch - expected ${expected}, got ${got}"
		exit 1
	fi
	echo "matches - ${expected}, got ${got}"
}

add_alias() {
	for i in $(seq 1 4); do
		echo "... attempting to add alias $i"
		until (mc alias set minio http://127.0.0.1:9000 minioadmin minioadmin); do
			echo "...waiting... for 5secs" && sleep 5
		done
	done

        xla_shape.dimensions(), &tensor_shape));
    arg_shapes.emplace_back(tensor_shape);

    DataType dtype;
    TF_RETURN_IF_ERROR(ConvertToDataType(input_type, &dtype));

    auto metadata_arg = metadata_proto.add_args();
    metadata_arg->set_kind(tpu::TPUCompileMetadataProto::Arg::PARAMETER);
    metadata_arg->set_dtype(dtype);
  }

  return absl::OkStatus();
}

absl::Status SetupReturnValues(mlir::ModuleOp module,

  auto client =
      xla::ClientLibrary::GetOrCreateCompileOnlyClient(platform).value();

  std::vector<TensorShape> arg_shapes = {{1}};
  TPUCompileMetadataProto metadata_proto;
  auto arg = metadata_proto.add_args();
  arg->set_dtype(DataType::DT_FLOAT);
  arg->set_kind(TPUCompileMetadataProto::Arg::PARAMETER);
  metadata_proto.add_retvals();
  bool use_tuple_args = true;
  std::vector<ShardingAndIndex> arg_core_mapping;

    tensorflow::tpu::TPUCompileMetadataProto metadata_proto;
    // Set up an arg per arg_shape with the specified type.
    for (int i = 0; i < arg_shapes.size(); ++i) {
      auto metadata_arg = metadata_proto.add_args();
      metadata_arg->set_kind(
          tensorflow::tpu::TPUCompileMetadataProto::Arg::PARAMETER);
      metadata_arg->set_dtype(dtype);
    }
    // Set up one dummy retval.
    metadata_proto.add_retvals();

    Type operand_type = operand_type_and_idx.value();
    int index = operand_type_and_idx.index();
    tensorflow::tpu::TPUCompileMetadataProto::Arg* arg = metadata->add_args();
    tensorflow::DataType dtype;
    tensorflow::Status status =
        tensorflow::ConvertToDataType(operand_type, &dtype);
    if (!status.ok())
      return op.emitOpError(