if (ops == nullptr)
    return errors::FailedPrecondition(
        "Trying to register filesystem without operations");

  if (ops->init == nullptr)
    return errors::FailedPrecondition(
        "Trying to register filesystem without `init` operation");

  if (ops->cleanup == nullptr)
    return errors::FailedPrecondition(
        "Trying to register filesystem without `cleanup` operation");

  return OkStatus();
}

)

updater_config_repository(name = "updater_config_repository")

python_register_multi_toolchains(
    name = "python",
    default_version = default_python_version,
    ignore_root_user_error = True,
    python_versions = [
        "3.9",
        "3.10",
        "3.11",
        "3.12",
    ],
    register_coverage_tool = True,
)

py_repositories()

load("@rules_python//python:repositories.bzl", "python_register_toolchains")  # buildifier: disable=same-origin-load
load(
    "//tensorflow/tools/toolchains/python:python_repo.bzl",
    "python_repository",
)

python_repository(name = "python_version_repo")

load("@python_version_repo//:py_version.bzl", "TF_PYTHON_VERSION")

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,

 public:
  bool UseMlir() const { return strcmp(std::get<0>(GetParam()), "mlir") == 0; }
  bool UseFunction() const { return std::get<2>(GetParam()); }
};

TEST_P(CppGradients, TestReluGrad) {
  status_ = registry_.Register("Relu", ReluRegisterer);
  ASSERT_EQ(errors::OK, status_.code()) << status_.message();

  auto ReluGradModel = BuildGradModel(ReluModel, registry_);

  for (int i = 0; i < grad_inputs.size(); i++) {
    grad_inputs[i] = nullptr;
  }
  return OkStatus();
}

Status RegisterNotDifferentiable(GradientRegistry* registry, const string& op) {
  return registry->Register(op, [](const ForwardOperation& op) {
    return new NotDifferentiableGradientFunction;
  });
}
}  // namespace gradients

category names correspond to generated source file names, and should be
consistent with the original source files registering each operator. For example
since `REGISTER_OP("MatMul")` appears in ***core/math_ops.cc***, the "MatMul"
operator in the script should be in the "math" category, and it will be
generated in the output file `c/experimental/ops/math_ops.cc`.

//   // More complex gradient functions can use inputs/attrs etc. from the
//   // forward `op`.
//   return new AddGradientFunction;
// }
//
// Status RegisterGradients(GradientRegistry* registry) {
//   return registry->Register("Add", AddRegisterer);
// }
class GradientFunction {
 public:
  virtual Status Compute(AbstractContext* ctx,
                         absl::Span<AbstractTensorHandle* const> grad_outputs,

#include "tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Register the POSIX filesystems statically.
// Return value will be unused
bool StaticallyRegisterLocalFilesystems() {
  TF_FilesystemPluginInfo info;
  TF_InitPlugin(&info);

      (*optimizer_.destroy_func)(c_optimizer_);
    }
  }

 private:
  TP_Optimizer optimizer_;
  std::string device_type_;
  void* c_optimizer_;
};

// Registration function to register a CGraphOptimizer along with plugin configs
// and device type.
void CGraphOptimizerRegister(
    const PluginGraphOptimizerRegistry::Creator& creator,
    const TP_OptimizerConfigs tp_configs, const char* device_type);

  REGISTER_OP("CApiAttributesTestOpList" #type)               \
      .Attr("v: list(" #type ")")                             \
      .SetShapeFn(tensorflow::shape_inference::UnknownShape)
ATTR_TEST_REGISTER_OP(string);
ATTR_TEST_REGISTER_OP(int);
ATTR_TEST_REGISTER_OP(float);
ATTR_TEST_REGISTER_OP(bool);
ATTR_TEST_REGISTER_OP(type);
ATTR_TEST_REGISTER_OP(shape);
ATTR_TEST_REGISTER_OP(tensor);