typedef struct TF_FilesystemPluginOps {
  char* scheme;
  int filesystem_ops_abi;
  int filesystem_ops_api;
  size_t filesystem_ops_size;
  TF_FilesystemOps* filesystem_ops;
  int random_access_file_ops_abi;
  int random_access_file_ops_api;
  size_t random_access_file_ops_size;
  TF_RandomAccessFileOps* random_access_file_ops;
  int writable_file_ops_abi;
  int writable_file_ops_api;
  size_t writable_file_ops_size;

  tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
fi
source ci/official/utilities/get_versions.sh

# Note on gsutil commands:
# "gsutil cp" always "copies into". It cannot act on the contents of a directory
# and it does not seem possible to e.g. copy "gs://foo/bar" as anything other than
# "/path/bar". This script uses "gsutil rsync" instead, which acts on directory

    for (int i = 0; i < expected.size(); ++i) {
      ASSERT_EQ(expected[i], data[i]) << "Different data at index " << i;
    }
  }

  std::vector<TF_Output> ToOutput(const std::vector<TF_Operation*> ops) {
    std::vector<TF_Output> out;
    for (auto op : ops) {
      out.push_back({op, 0});
    }
    return out;
  }

  void Define(int num_opers, const std::vector<TF_Operation*>& opers,

)

config_setting(
    name = "with_xla_support",
    define_values = {"with_xla_support": "true"},
    visibility = ["//visibility:public"],
)

# By default, XLA GPU is compiled into tensorflow when building with
# --config=cuda even when `with_xla_support` is false. The config setting
# here allows us to override the behavior if needed.
config_setting(
    name = "no_xla_deps_in_cuda",

    TF_Status* status) {
  TFE_CustomDevice device;
  void* device_info;
  tensorflow::parallel_device::AllocateParallelDevice(
      device_name, underlying_devices.data(), underlying_devices.size(),
      &device, &device_info);
  TFE_RegisterCustomDevice(context, device, device_name, device_info, status);
}

}  // namespace parallel_device
}  // namespace tensorflow

    [Environment]::SetEnvironmentVariable(\"PATH\", $old_path + \";${zulu_root}\bin\", \"Machine\"); \
    [Environment]::SetEnvironmentVariable(\"JAVA_HOME\", $zulu_root, \"Machine\")

# Install gcloud (install.bat installs directly into bin folder of extracted zip contents)
# Install needed gcloud components
RUN Add-Type -AssemblyName "System.IO.Compression.FileSystem"; \

      # Get the linker version
      ld_version = run_shell([gcc_env, '-Wl,-version']).split()

      ld_version_int = convert_version_to_int(ld_version[3])
      if ld_version_int is None:
        ld_version_int = convert_version_to_int(ld_version[4])

      # Enable if 'ld' version >= 2.35
      if ld_version_int >= 2035000:
        write_to_bazelrc(
            'build --copt="-DEIGEN_ALTIVEC_ENABLE_MMA_DYNAMIC_DISPATCH=1"')

//
TF_CAPI_EXPORT extern TF_ShapeAndTypeList* TF_NewShapeAndTypeList(
    int num_shapes);
TF_CAPI_EXPORT extern void TF_ShapeAndTypeListSetShape(
    TF_ShapeAndTypeList* shape_list, int index, const int64_t* dims,
    int num_dims);
TF_CAPI_EXPORT extern void TF_ShapeAndTypeListSetUnknownShape(
    TF_ShapeAndTypeList* shape_list, int index);
TF_CAPI_EXPORT extern void TF_ShapeAndTypeListSetDtype(

#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

namespace {

using ::tensorflow::string;

void ReplaceTaskInServerDef(tensorflow::ServerDef* server_def, int task_index) {
  tensorflow::JobDef* job_def = server_def->mutable_cluster()->mutable_job(0);
  int port = tensorflow::testing::PickUnusedPortOrDie();
  job_def->mutable_tasks()->at(task_index) =
      tensorflow::strings::StrCat("localhost:", port);
}

fi

# Create and expand to the full path of TFCI_OUTPUT_DIR
export TFCI_OUTPUT_DIR=$(realpath "$TFCI_OUTPUT_DIR")
mkdir -p "$TFCI_OUTPUT_DIR"

# In addition to dumping all script output to the terminal, place it into
# $TFCI_OUTPUT_DIR/script.log
exec > >(tee "$TFCI_OUTPUT_DIR/script.log") 2>&1

# Setup tfrun, a helper function for executing steps that can either be run