// graph_def.library().gradient()
std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def);

// Returns a sorted vector of names contained in `grad_def`
std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def);

class CSession {
 public:
  CSession(TF_Graph* graph, TF_Status* s, bool use_XLA = false);

fi

# "TFCI_MACOS_INSTALL_BAZELISK_ENABLE" is used to decide if we need to install
# Bazelisk manually. We enable this for macOS x86 builds as those VMs do not
# have Bazelisk pre-installed. "TFCI_MACOS_INSTALL_BAZELISK_URL" contains the
# link to the Bazelisk binary which needs to be downloaded.
if [[ "${TFCI_MACOS_INSTALL_BAZELISK_ENABLE}" == 1 ]]; then
  sudo wget --no-verbose -O "/usr/local/bin/bazel" "${TFCI_MACOS_INSTALL_BAZELISK_URL}"

  if (TF_GetCode(status) != TF_OK) return nullptr;
  TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
  TFE_OpSetAttrShape(op, "shape", {}, 0, status);
  TFE_OpSetAttrString(op, "container", "localhost", 0);
  TFE_OpSetAttrString(op, "shared_name", "", 0);
  if (!device_name.empty()) {
    TFE_OpSetDevice(op, device_name.c_str(), status);
  }
  if (TF_GetCode(status) != TF_OK) return nullptr;

  }

  FunctionDef fdef() {
    tensorflow::FunctionDef fdef;
    EXPECT_TRUE(GetFunctionDef(func_, &fdef));
    return fdef;
  }

  // logging utility
  template <class Container>
  string ToString(const Container& v) {
    std::stringstream ss;
    ss << "{";
    size_t i = 0;
    for (const auto& e : v) {
      if (i != 0) {
        ss << ", ";
      }
      ss << e.ToString();
      ++i;

      (d) If the Work includes a "NOTICE" text file as part of its
          distribution, then any Derivative Works that You distribute must
          include a readable copy of the attribution notices contained
          within such NOTICE file, excluding those notices that do not
          pertain to any part of the Derivative Works, in at least one
          of the following places: within a NOTICE text file distributed

  ///    filesystem failed.
  /// 2) `TF_FAILED_PRECONDITION` if the read from the remote filesystem
  /// succeeded,
  ///    but the read returned a partial block, and the LRU cache contained a
  ///    block at a higher offset (indicating that the partial block should have
  ///    been a full block).
  /// 3) `TF_OUT_OF_RANGE` if the read from the remote filesystem succeeded, but

==============================================================================*/

#include "tensorflow/c/eager/c_api_experimental.h"

#include <cstdint>
#include <memory>
#include <utility>
#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/strings/match.h"
#include "absl/time/time.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/tfe_context_internal.h"

#include "tensorflow/c/eager/c_api.h"

#include <algorithm>
#include <cstddef>
#include <cstdint>
#include <memory>
#include <string>
#include <utility>
#include <vector>

#include "absl/algorithm/container.h"
#include "absl/memory/memory.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_internal.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_experimental.h"

    ]),
)

# ** Targets for Windows build (start) **

# Build a shared library (DLL) by cc_binary from tf_custom_op_library_additional_deps_impl,
# it contains all object code from its dependencies.
# This target is only used for parsing the symbols to be exported in tensorflow.dll.
# Do NOT depend on it.
tf_native_cc_binary(

                                                      TF_Status* status);
TF_CAPI_EXPORT extern void TF_Reset(const TF_SessionOptions* opt,
                                    const char** containers, int ncontainers,
                                    TF_Status* status);
// Treat the bytes proto[0,proto_len-1] as a serialized GraphDef and
// add the nodes in that GraphDef to the graph for the session.
//