// 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> } : () -> ()

    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.*}}"]

  // CHECK: ml_program.global private mutable [[V:@.+]](dense<1.000000e+00> : tensor<1xf32>) : tensor<?xf32>
  // CHECK: func.func @f
  // CHECK: [[T:%.+]] = ml_program.global_load [[V]]
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()
  func.func @f(%arg0: tensor<!tf_type.resource<tensor<?xf32>>> {tf_saved_model.bound_input = @v})
  -> (tensor<?xf32> {tf_saved_model.index_path = []})

  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v0", type = tensor<3xf32>, value = dense<42.0> : tensor<9xf32> } : () -> ()
}

// -----

module attributes {tf_saved_model.semantics} {
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.0> : tensor<f32> } : () -> ()

// CHECK-LABEL: module
module attributes {tf_saved_model.semantics} {
  // CHECK: ml_program.global {{.*}} @vars.v
  // CHECK: ml_program.global {{.*}} @vars.bar
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<10xf32>, value = dense<[0.,1.,2.,3.,4.,5.,6.,7.,8.,9.]> : tensor<10xf32> } : () -> ()
  func.func @read(%arg0: tensor<!tf_type.resource<tensor<10xf32>>> {tf_saved_model.bound_input = @v})

# CHECK: "tf_saved_model.session_initializer"() <{initializers = [@[[init:.*]]]}> : () -> ()
# CHECK: "tf_saved_model.asset"() <{filename = {{.*}}, sym_name = "[[asset1:__tf_saved_model_asset1_.*]]"}>
# CHECK: "tf_saved_model.asset"() <{filename = {{.*}}, sym_name = "[[asset0:__tf_saved_model_asset0_.*]]"}>

# CHECK:      func @[[init]]
# CHECK-SAME: [[ARG0:%.*]]: tensor<!tf_type.string> {tf_saved_model.bound_input = @[[asset0]]}

			$modname = "libc";
		}
		$modname .= ".so";

	}

	# System call name.
	if($sysname eq "") {
		$sysname = "$func";
	}

	# System call pointer variable name.
	my $sysvarname = "libc_${sysname}";

	my $strconvfunc = "BytePtrFromString";
	my $strconvtype = "*byte";

	$sysname =~ y/A-Z/a-z/; # All libc functions are lowercase.

	# Runtime import of function to allow cross-platform builds.

// RUN: tf-opt %s -allow-unregistered-dialect --tf-localize-var-handles --split-input-file | FileCheck %s

// CHECK-LABEL: module
module attributes {tf_saved_model.semantics} {
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<10xf32>, value = dense<[0.,1.,2.,3.,4.,5.,6.,7.,8.,9.]> : tensor<10xf32> } : () -> ()
  // CHECK-LABEL: @read_from_global

  "tf_saved_model.session_initializer"() {initializers = [@init]} : () -> ()

  // CHECK-NOT: "tf_saved_model.asset"
  "tf_saved_model.asset"() {filename = "assets/test0.txt", sym_name = "asset0"} : () -> ()
  "tf_saved_model.asset"() {filename = "assets/test1.txt", sym_name = "asset1"} : () -> ()

  // CHECK: func @init()