node {
  name: "Const"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 2
          }
          dim {
            size: 2
          }
        }
        tensor_content: "\315\314\314=\315\314L>\232\231\231>\315\314\314>"
      }
    }

#include "tensorflow/compiler/mlir/tensorflow/utils/xla_sharding_util.h"
#include "xla/xla.pb.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"

namespace mlir {

#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/test.h"

#include "xla/client/client_library.h"
#include "xla/shape.h"
#include "xla/stream_executor/platform.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/protobuf/config.pb.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"

#include "tensorflow/c/tf_tensor_helper.h"  // IWYU pragma: export
#include "tensorflow/core/framework/allocation_description.pb.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/status.h"

// Internal structures used by the C API. These are likely to change and should
// not be depended on.

#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/logging.h"

namespace tensorflow {

Variable::Variable(ImmediateExecutionContext* ctx, DataType dtype,
                   TensorShape shape, absl::optional<std::string> name,

      const auto& tensor_shape = default_value.shape();
      if (tensor_shape.unknown_rank()) {
        TFE_OpSetAttrShape(op, attr_name, nullptr, -1, status);
      } else {
        const auto num_dims = tensor_shape.dim_size();
        std::unique_ptr<int64_t[]> dims(new int64_t[num_dims]);
        for (int i = 0; i < num_dims; ++i) {
          dims[i] = tensor_shape.dim(i).size();
        }

#include "tensorflow/core/common_runtime/eager/context.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {

#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/mlir_hlo/mhlo/IR/register.h"
#include "xla/shape.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/profile_utils/cpu_utils.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"

//       value: {
//         name : "serving_default_a:0"
//         dtype: DT_FLOAT
//         tensor_shape: {
//         }
//       }
//     }
//     inputs: {
//       key  : "b"
//       value: {
//         name : "serving_default_b:0"
//         dtype: DT_FLOAT
//         tensor_shape: {
//         }
//       }
//     }
//     outputs: {
//       key  : "output_0"
//       value: {