// The internal gradient implementation needs the shape of the input image.
  // x_shape = shape(x)[1:3]
  //         = slice(shape(x), {1}, {3 - 1})
  auto x_shape = Slice(scope, Shape(scope, op.input(0)), {1}, {2});
  grad_outputs->push_back(internal::ResizeNearestNeighborGrad(
      scope, grad_inputs[0], x_shape,
      internal::ResizeNearestNeighborGrad::AlignCorners(align_corners)

#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.

  ManipGradTest() : scope_(Scope::NewRootScope()) {}

  void RunTest(const Output& x, const TensorShape& x_shape, const Output& y,
               const TensorShape& y_shape) {
    TF_ASSERT_OK(scope_.status());
    float max_error;
    TF_ASSERT_OK((ComputeGradientError<float, float, float>(
        scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error)));
    EXPECT_LT(max_error, 1e-4);
  }

  Scope scope_;
};

#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());
}

// 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);

  FunctionGradTest() : scope_(Scope::NewRootScope()) {}

  void RunTest(const Output& x, const TensorShape& x_shape, const Output& y,
               const TensorShape& y_shape) {
    TF_ASSERT_OK(scope_.status());
    float max_error;
    auto result = (ComputeGradientError<float, float, float>(
        scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error));
    TF_CHECK_OK(result);
    TF_ASSERT_OK(result);
    EXPECT_LT(max_error, 1e-3);
  }

    }
  }
  attr {
    key: "dtype"
    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"

#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"

        "@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",

template <typename X_T, typename Y_T, typename JAC_T>
Status ComputeGradientError(const Scope& scope, const Output& x,
                            const Tensor& x_init_value, const Output& y,
                            const TensorShape& y_shape, JAC_T* max_error);

}  // namespace tensorflow