# tfcompile.bzl correctly handles usage from outside of the package that it is
# defined in.

# A simple test of tf_library from a text protobuf, to enable benchmark_test.
# This test uses an incompleted graph with a node that is not defined. The
# compilation works because the undefined node is a feed node.
tf_library(
    name = "test_graph_tfadd",
    testonly = 1,
    config = "test_graph_tfadd.config.pbtxt",

"""Build macro that compiles a TensorFlow graph into a cc_library.

To use from your BUILD file, add the following line to load the macro:

load("//tensorflow/compiler/aot:tfcompile.bzl", "tf_library")

Then call the macro like this:

tf_library(
    name = "test_graph_tfmatmul",
    config = "test_graph_tfmatmul.config.pbtxt",
    cpp_class = "MatMulComp",
    graph = ":test_graph_tfmatmul.pb",
)
"""

load(

// for the first time.
TF_Library* TF_LoadPluggableDeviceLibrary(const char* library_filename,
                                          TF_Status* status) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "PluggableDevice plugin functionality is not supported on mobile");
  return nullptr;
#else
  TF_Library* lib_handle = new TF_Library;

    TF_ASSIGN_OR_RETURN(std::unique_ptr<xla::HloSnapshot> module,
                        computation.Snapshot());
    // Serialize the HloSnapshot deterministically so that all the outputs of a
    // tf_library genrule are deterministic.
    const size_t size = module->ByteSizeLong();
    auto serialized = std::make_unique<char[]>(size);
    TF_RET_CHECK(
        SerializeToBufferDeterministic(*module, serialized.get(), size));

  }
  TF_Run_Helper(s->session, handle, nullptr, input_pairs, output_names,
                c_outputs, target_oper_names, nullptr, status);
}

TF_Library* TF_LoadLibrary(const char* library_filename, TF_Status* status) {
  TF_Library* lib_handle = new TF_Library;
  status->status = tensorflow::LoadDynamicLibrary(
      library_filename, &lib_handle->lib_handle, &lib_handle->op_list.data,
      &lib_handle->op_list.length);

load("@llvm-project//mlir:tblgen.bzl", "gentbl_cc_library", "td_library")

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

td_library(
    name = "mlrt_td_files",
    srcs = [
        "mlrt_dialect.td",
        "mlrt_ops.td",
    ],
    includes = ["."],
    visibility = [
        # copybara:uncomment "//learning/brain/tfrt/mlir:__subpackages__",
    ],

load("@llvm-project//mlir:tblgen.bzl", "gentbl_cc_library", "td_library")

# Note: keep the following lines separate due to the way copybara works
load("//tensorflow:tensorflow.default.bzl", "get_compatible_with_portable")

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

cc_library(
    name = "tfrt_fallback_opdefs",
    srcs = [

    ],
    licenses = ["notice"],
)

td_library(
    name = "lift_as_function_call_td_files",
    srcs = [
        "lift_as_function_call.td",
    ],
    compatible_with = get_compatible_with_portable(),
    deps = [
        "@llvm-project//mlir:FuncTdFiles",
    ],
)

cc_library(
    name = "lift_as_function_call",
    srcs = ["lift_as_function_call.cc"],

  {
    // Load the library.
    TF_Status* status = TF_NewStatus();
    string lib_path = tensorflow::GetDataDependencyFilepath(
        tensorflow::io::JoinPath("tensorflow", "c", "test_op1.so"));
    TF_Library* lib = TF_LoadLibrary(lib_path.c_str(), status);
    TF_Code code = TF_GetCode(status);
    string status_msg(TF_Message(status));
    TF_DeleteStatus(status);
    ASSERT_EQ(TF_OK, code) << status_msg;

load("@llvm-project//mlir:tblgen.bzl", "gentbl_cc_library", "td_library")
load("//tensorflow:tensorflow.bzl", "tf_cc_test")
load("//tensorflow:tensorflow.default.bzl", "filegroup", "get_compatible_with_portable")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

# copybara:uncomment_end(google-only)
package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:public"],