module attributes {tf_saved_model.semantics} {

  // Test case: Fail if some global tensor ops remain

 "tf_saved_model.global_tensor"() {sym_name = "v", type = tensor<f32>, value = dense<1.0> : tensor<f32> } : () -> ()
 "tf_saved_model.global_tensor"() {sym_name = "v2", type = tensor<f32>, value = dense<1.0> : tensor<f32> } : () -> ()

  func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v})

	var uts unix.Utsname
	if err := unix.Uname(&uts); err != nil {
		return "", err
	}

	sysname := unix.ByteSliceToString(uts.Sysname[:])
	release := unix.ByteSliceToString(uts.Release[:])
	version := unix.ByteSliceToString(uts.Version[:])
	machine := unix.ByteSliceToString(uts.Machine[:])

	return sysname + " " + release + " " + version + " " + machine, nil

	my $funcname = "";
	if($sysname eq "") {
		$sysname = "SYS_$func";
		$sysname =~ s/([a-z])([A-Z])/${1}_$2/g;	# turn FooBar into Foo_Bar
		$sysname =~ y/a-z/A-Z/;
		if($libc) {
			$sysname =~ y/A-Z/a-z/;
			$sysname = substr $sysname, 4;
			$funcname = "libc_$sysname";
		}
	}
	if($libc) {
		if($funcname eq "") {
			$sysname = substr $sysname, 4;
			$sysname =~ y/A-Z/a-z/;

  // CHECK: tf_saved_model.asset
  "tf_saved_model.asset"() {
    filename = "asset_filename",
    sym_name = "asset_sym_name"
  } : () -> ()

  // Representation for constants: (immutable) global tensor.
  // CHECK: tf_saved_model.global_tensor
  "tf_saved_model.global_tensor"() {
    tf_saved_model.exported_names = ["some_const"],
    sym_name = "some_constant",
    type = tensor<1x64xf32>,
    value = dense<42.0> : tensor<1x64xf32>

    "func.return"() : () -> ()
  }) {sym_name = "__inference_wrapped_function_4260250_0", sym_visibility = "private", tf._input_shapes = [#tf_type.shape<>], tf.signature.is_stateful, function_type = (tensor<i32>) -> ()} : () -> ()
  "func.func"() ({
  ^bb0(%arg0: tensor<i32>):
    "func.return"(%arg0) : (tensor<i32>) -> ()

    func.return %4 : tensor<100x50xf32>
  }
  // CHECK: "tf_saved_model.global_tensor"()
  // CHECK:    sym_name = "dense/kernel"
  // CHECK: "tf_saved_model.global_tensor"()
  // CHECK:    sym_name = "dense/bias"
  // CHECK:  func @serving_default(
  // CHECK:    %arg0: tensor<!tf_type.resource<tensor<100x50xf32>>> {tf_saved_model.bound_input = @"dense/kernel"},

  // CHECK: "tf_saved_model.global_tensor"() <{
  // CHECK-NOT: is_mutable
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()

  // CHECK: "tf_saved_model.global_tensor"() <{
  // CHECK-NOT: is_mutable
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v2", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()

  // Test case: Remove duplicate bound_input symbols.
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.0> : tensor<f32> } : () -> ()
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "w", type = tensor<f32>, value = dense<43.0> : tensor<f32> } : () -> ()
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "x", type = tensor<f32>, value = dense<44.0> : tensor<f32> } : () -> ()
  // CHECK: func @f

    func.return
  }
}

// -----

module attributes {tf_saved_model.semantics} {

  "tf_saved_model.asset"() {filename = "assets/table.txt", sym_name = "v"} : () -> ()
  "tf_saved_model.asset"() {filename = "assets/table2.txt", sym_name = "w"} : () -> ()

  // CHECK: func @f()
  func.func @f(%arg0: tensor<!tf_type.string> {tf_saved_model.bound_input = @v}, %arg1: tensor<!tf_type.string> {tf_saved_model.bound_input = @w})

# CHECK-SAME: initializers = [@[[restore:.*]]]

# CHECK: "tf_saved_model.asset"()
# CHECK-SAME: <{filename = [[filename:.*]], sym_name = "[[sym_name:.*]]"}> : () -> ()

# CHECK:      func @[[restore]](
# CHECK-SAME:   [[variable_path:%.*]]: tensor<!tf_type.string> {tf_saved_model.bound_input = @[[sym_name]]}
# CHECK-SAME: tf_saved_model.exported_names = ["{{__tf_saved_model_session_initializer.*}}"]