#define TENSORFLOW_C_EXPERIMENTAL_SAVED_MODEL_PUBLIC_TENSOR_SPEC_H_

#include <stddef.h>

#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_shape.h"

#ifdef __cplusplus
extern "C" {
#endif  // __cplusplus

// An opaque type corresponding to TensorSpec
typedef struct TF_TensorSpec TF_TensorSpec;

// Returns the dtype associated with the TensorSpec.

// Represents a (partially-defined) shape.
typedef struct TF_Shape {
  int num_dims;  // Must be >= -1; -1 represents unknown rank.
  int64_t* dim_sizes;
} TF_Shape;

// Add a new parameter to a TensorFlow Function.
TF_AbstractTensor* TF_AddFunctionParameter(TF_ExecutionContext* func,
                                           TF_DataType dtype, TF_Shape shape,
                                           TF_Status* s);

#include "tensorflow/c/tf_shape_internal.h"

extern "C" {

TF_DataType TF_TensorSpecDataType(const TF_TensorSpec* spec) {
  return static_cast<TF_DataType>(tensorflow::unwrap(spec)->dtype());
}

const TF_Shape* TF_TensorSpecShape(const TF_TensorSpec* spec) {
  return tensorflow::wrap(&tensorflow::unwrap(spec)->shape());
}

#include "tensorflow/c/experimental/saved_model/public/signature_def_param_list.h"
#include "tensorflow/c/experimental/saved_model/public/tensor_spec.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_shape.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/lib/io/path.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/stringpiece.h"

    value {
      type: DT_INT32
    }
  }
}
node {
  name  : "y_reshape"
  op    : "Reshape"
  input : "y_const"
  input : "y_shape"
  attr { key: "T" value { type: DT_INT32 } }
  # Attribute TShape not specified; needs to be set to its default
  # by tfcompile.
}
node {
  name  : "x_y_sum"
  op    : "Add"
  input : "x_const"
  input : "y_reshape"
  attr {
    key  : "T"
    value {

  for (const std::optional<llvm::ArrayRef<int64_t>>& shape : shapes) {
    TensorShapeProto& tshape = *shape_list.add_shape();
    if (shape.has_value()) {
      for (int64_t dim : *shape) {
        tshape.add_dim()->set_size(mlir::ShapedType::isDynamic(dim) ? -1 : dim);
      }
    } else {
      tshape.set_unknown_rank(true);
    }
  }

  // If shape is already set, override it. This can happen if we import

        "@local_xla//xla/tsl/c:tsl_status_internal_headers",
    ],
    visibility = [
        "//tensorflow/python:__subpackages__",
    ],
)

cc_library(
    name = "tf_shape",
    srcs = ["tf_shape.cc"],
    hdrs = ["tf_shape.h"],
    copts = tf_copts(),
    visibility = ["//visibility:public"],
    deps = [
        ":c_api_macros",
        ":tf_shape_internal",
        "//tensorflow/core:framework",

    value {
      type: DT_STRING
    }
  }
  attr {
    key: "row_partition_types"
    value {
      list {
        s: ["ROW_SPLITS"]
      }
    }
  }
  attr {
    key: "Tshape"
    value {
      type: DT_INT64
    }
  }
  attr {
    key: "Tindex"
    value {
      type: DT_INT64
    }
  }
  attr {
    key: "T"
    value {
      type: DT_STRING

  TFE_Op* reshape_op = TFE_NewOp(tfe_context_, "Reshape", status_);
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);
  TFE_OpSetAttrType(reshape_op, "T", TF_FLOAT);
  TFE_OpSetAttrType(reshape_op, "Tshape", TF_INT32);
  CheckOutputShapes(reshape_op,
                    /* input_shapes*/ {unknown_shape(), unknown_shape()},
                    /* input_tensors*/ {nullptr, tensor_1X6},

  TF_DeleteExecutionContext(ctx);
  return wrap(func);
}

TF_AbstractTensor* TF_AddFunctionParameter(TF_ExecutionContext* func,
                                           TF_DataType dtype, TF_Shape shape,
                                           TF_Status* s) {
  DCHECK_GE(shape.num_dims, -1);
  TracingTensorHandle* t;
  TracingContext* tracing_ctx = dyn_cast<TracingContext>(unwrap(func));
  if (!tracing_ctx) {