"//tensorflow/c/experimental/ops:nn_ops",
    ],
)

cc_library(
    name = "nn_grad",
    srcs = ["nn_grad.cc"],
    hdrs = [
        "nn_grad.h",
    ],
    visibility = ["//visibility:private"],
    deps = [
        "//tensorflow/c/eager:abstract_tensor_handle",
        "//tensorflow/c/eager:gradients_internal",
        "//tensorflow/c/eager:immediate_execution_context",

  fstat(fd, &st);
  if (S_ISDIR(st.st_mode)) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION, "path is a directory");
  } else {
    const void* address =
        mmap(nullptr, st.st_size, PROT_READ, MAP_PRIVATE, fd, 0);
    if (address == MAP_FAILED) {
      TF_SetStatusFromIOError(status, errno, path);
    } else {
      region->plugin_memory_region =
          new tf_read_only_memory_region::PosixMemoryRegion{

      bool build_default_zeros_grads = true);

  // Whether the tape is persistent. See ctor for detailed description.
  bool IsPersistent() const { return persistent_; }

 private:
  TensorTape tensor_tape_;
  OpTape<BackwardFunction, TapeTensor> op_tape_;
  int64_t next_op_id_{0};

  // Map from tensor id to number of remaining usages (i.e. how many entries in

build --incompatible_enforce_config_setting_visibility
# TODO: also enable this flag after fixing the visibility violations
# build --incompatible_config_setting_private_default_visibility

# Default options should come above this line.

# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
# target CPU to build transient dependencies correctly. See

  // Remove a function. 'func' argument is the name of a previously added
  // FunctionDef. The name is in fdef.signature.name.
  virtual Status RemoveFunction(const string& func) = 0;

 private:
  const AbstractContextKind kind_;
};

namespace internal {
struct AbstractContextDeleter {
  void operator()(AbstractContext* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};

  // worker/task/replica if any of those differ across components. Useful for
  // printing debug messages.
  std::vector<std::string> SummarizeDeviceNames() const;

 private:
  // A sequence of device names, indicating which devices replicated operations
  // are forwarded to.
  const std::vector<std::string> underlying_devices_;

  // Adds `value` to the existing value of the variable.
  void AssignAdd(TFE_Context* context, TFE_TensorHandle* value,
                 TF_Status* status);

 private:
  // Helper for running any single-argument assignment ops (Assign, AssignAdd,
  // AssignSub, ...).
  void GeneralAssignment(const char* op_name, TFE_Context* context,

    }
    if (first_call_) {
      first_call_ = false;
      return absl::OkStatus();
    }
    return tensorflow::errors::Internal("Graph pass runs for more than once!");
  }

 private:
  bool first_call_ = true;
};

// After the graph pass is registered, it takes effect globally and can affect
// other test cases. Define a static variable to switch it on and off.

      : device_name_(name), parallel_device_(std::move(parallel_device)) {}
  const std::string& name() const { return device_name_; }
  const ParallelDevice& device() const { return *parallel_device_; }

 private:
  std::string device_name_;
  std::unique_ptr<ParallelDevice> parallel_device_;
};

absl::optional<std::vector<MaybeParallelTensorOwned>> ExecuteWithSpecialOps(
    const ParallelDevice& parallel_device,

  std::vector<TensorHandlePtr> Join(TF_Status* status);

  // Block until all Ops finished running on the thread.
  void AsyncWait(TF_Status* status);

 private:
  void Run();

  void Execute(TFE_Context* context, const char* operation_name,
               std::vector<TFE_TensorHandle*> inputs,
               const TFE_OpAttrs* attributes, int expected_max_outputs,