],
    visibility = ["//tensorflow/python:__pkg__"],
)

cc_library(
    name = "parallel_device",
    srcs = [":device_sources"],
    hdrs = [":device_headers"],
    visibility = ["//visibility:private"],
    deps = [
        ":parallel_device_lib",
        "//tensorflow/c:c_api",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",

    return absl::OkStatus();
  }
  ~ReluGradientFunction() override {
    for (auto output : forward_outputs_) {
      if (output) {
        output->Unref();
      }
    }
  }

 private:
  // TODO(b/174778737): Only hold needed outputs.
  vector<AbstractTensorHandle*> forward_outputs_;
};

Status BroadcastMul(AbstractContext* ctx, AbstractTensorHandle* vec,
                    AbstractTensorHandle* mat,

      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing
}  // namespace tensorflow

load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:private"],
    licenses = ["notice"],
)

# Filesystem implementation for POSIX environments: Linux, MacOS, Android, etc.
tf_cc_shared_object(
    name = "libposix_filesystem.so",
    framework_so = [],

  virtual Status GetFunctionDef(const FunctionDef**) = 0;

  // Returns a shared reference to the wrapped function.
  virtual absl::StatusOr<core::RefCountPtr<FunctionRecord>>
  GetFunctionRecord() = 0;

 private:
  const AbstractFunctionKind kind_;
};

using AbstractFunctionPtr =
    tensorflow::core::IntrusivePtr<tensorflow::AbstractFunction>;

}  // namespace tensorflow

        "//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",