Do not use deprecated usePropertiesAsAttributes=0 for tf_saved_model …

…ops.

PiperOrigin-RevId: 578099160

tensorflow/compiler/mlir/lite/tests/legalize-tf-variables.mlir

@@ -46,7 +46,7 @@ module attributes {tf_saved_model.semantics} {
   }
 
   "tf_saved_model.session_initializer"() {initializers = [@init_all_tables]} : () -> ()
-  // CHECK: "tf_saved_model.session_initializer"() {initializers = [@init_all_tables]} : () -> ()
+  // CHECK: "tf_saved_model.session_initializer"() <{initializers = [@init_all_tables]}> : () -> ()
 
   // CHECK-LABEL: serving_default
   func.func @serving_default(%arg0: tensor<1x10xf32> {tf_saved_model.index_path = ["x"]}) ->

tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_main_function.mlir

@@ -49,8 +49,8 @@ module attributes {tf.versions = {producer = 1132 : i32}, tf_saved_model.semanti
   "tf_saved_model.session_initializer"() {initializers = [@NoOp]} : () -> ()
   "tf_saved_model.asset"() {filename = "assets/mydata.txt", sym_name = "__tf_saved_model_asset0_mydata.txt"} : () -> ()
 // Session initializer ops and asset ops untouched.
-// CHECK: "tf_saved_model.session_initializer"() {initializers = [@NoOp]} : () -> ()
-// CHECK: "tf_saved_model.asset"() {filename = "assets/mydata.txt", sym_name = "__tf_saved_model_asset0_mydata.txt"} : () -> ()
+// CHECK: "tf_saved_model.session_initializer"() <{initializers = [@NoOp]}> : () -> ()
+// CHECK: "tf_saved_model.asset"() <{filename = "assets/mydata.txt", sym_name = "__tf_saved_model_asset0_mydata.txt"}> : () -> ()
 
   func.func @NoOp(%arg0: tensor<!tf_type.string> {tf_saved_model.bound_input = @__tf_saved_model_asset0_mydata.txt}) attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_NoOp"]} {
     %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

tensorflow/compiler/mlir/quantization/tensorflow/tests/merge_initializer_function_ops_to_main.mlir

@@ -303,7 +303,7 @@ func.func @NoOp_0(%arg0: tensor<!tf_type.string> {tf_saved_model.bound_input = @
 // CHECK-LABEL: module
 module attributes {tf_saved_model.semantics} {
   "tf_saved_model.session_initializer"() {initializers = [@init_func_restore_op]} : () -> ()
-// CHECK: "tf_saved_model.session_initializer"() {initializers = []}
+// CHECK: "tf_saved_model.session_initializer"() <{initializers = []}>
 
   func.func @init_func_restore_op(%arg: tensor<!tf_type.string> {tf_saved_model.index_path = ["__tf_file_prefix"]})
     attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_NoOp"], tf_saved_model.initializer_type = "restore_op"} {
@@ -383,7 +383,7 @@ module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, p
 // CHECK-LABEL: module
 module attributes {tf_saved_model.semantics} {
   "tf_saved_model.session_initializer"() {initializers = [@init_func_restore_op]} : () -> ()
-// CHECK: "tf_saved_model.session_initializer"() {initializers = []}
+// CHECK: "tf_saved_model.session_initializer"() <{initializers = []}>
 
   func.func @init_func_restore_op(%arg: tensor<!tf_type.string> {tf_saved_model.index_path = ["file_prefix"]})
     attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_NoOp"], tf_saved_model.initializer_type = "restore_op"} {

tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model_ops.td

@@ -83,7 +83,6 @@ def TfSavedModel_Dialect : Dialect {
   }];
 
   let cppNamespace = "::mlir::tf_saved_model";
-  let usePropertiesForAttributes = 0;
 }
 
 

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/basic.py

@@ -39,9 +39,9 @@ def __init__(self):
     self.c43 = tf.constant(43.0)
 
   # During serialization, the constants are given internal (non-user-accessible, non-semantically-load-bearing) exported names.
-  # CHECK: "tf_saved_model.global_tensor"() {sym_name = "[[CONST:[a-zA-Z_0-9.]+]]", tf_saved_model.exported_names = [{{.*}}], type = tensor<f32>, value = dense<4.300000e+01> : tensor<f32>} : () -> ()
+  # CHECK: "tf_saved_model.global_tensor"() <{sym_name = "[[CONST:[a-zA-Z_0-9.]+]]", type = tensor<f32>, value = dense<4.300000e+01> : tensor<f32>}> {tf_saved_model.exported_names = [{{.*}}]} : () -> ()
 
-  # CHECK: "tf_saved_model.global_tensor"() {is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", tf_saved_model.exported_names = ["v42"], type = tensor<f32>, value = dense<4.200000e+01> : tensor<f32>} : () -> ()
+  # CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", type = tensor<f32>, value = dense<4.200000e+01> : tensor<f32>}> {tf_saved_model.exported_names = ["v42"]} : () -> ()
   # CHECK:      func {{@[a-zA-Z_0-9]+}}(
   # CHECK-SAME:   %arg0: tensor<f32> {tf._user_specified_name = "x", tf_saved_model.index_path = [0]},
   # CHECK-SAME:   %arg1: tensor<!tf_type.resource<tensor<f32>>>

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/basic_v1.py

@@ -29,7 +29,7 @@
 # CHECK-SAME: min_consumer
 # CHECK-SAME: producer
 
-# CHECK: "tf_saved_model.global_tensor"() {is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", type = tensor<1x3xf32>, value = {{.*}} : tensor<1x3xf32>} : () -> ()
+# CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", type = tensor<1x3xf32>, value = {{.*}} : tensor<1x3xf32>}> : () -> ()
 
 # CHECK:      func {{@[a-zA-Z_0-9]+}}(
 # CHECK-SAME:   [[ARG0:%.*]]: tensor<3x1xf32> {tf_saved_model.index_path = ["x"]},

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/hash_table_asset_v1.py

@@ -22,9 +22,9 @@
 import tensorflow.compat.v1 as tf
 from tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model import common_v1
 
-# 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: "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]]}

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/hash_table_v1.py

@@ -30,7 +30,7 @@
 # CHECK-SAME: producer
 
 # CHECK: "tf_saved_model.global_tensor"()
-# CHECK: "tf_saved_model.session_initializer"() {initializers = [@[[init:.*]]]} : () -> ()
+# CHECK: "tf_saved_model.session_initializer"() <{initializers = [@[[init:.*]]]}> : () -> ()
 
 # CHECK:      func @[[init]]
 # CHECK-SAME: tf_saved_model.initializer_type = "init_op"

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/import_restore_v1.py

@@ -33,7 +33,7 @@
 # CHECK-SAME: initializers = [@[[restore:.*]]]
 
 # CHECK: "tf_saved_model.asset"()
-# CHECK-SAME: {filename = [[filename:.*]], sym_name = "[[sym_name:.*]]"} : () -> ()
+# 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]]}

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/include_variables_in_init_v1.py

@@ -30,7 +30,7 @@
 # CHECK-SAME: producer
 
 # CHECK: "tf_saved_model.global_tensor"()
-# CHECK: "tf_saved_model.session_initializer"() {initializers = [@[[INIT_FUNC:[a-zA-Z_0-9]+]]]} : () -> ()
+# CHECK: "tf_saved_model.session_initializer"() <{initializers = [@[[INIT_FUNC:[a-zA-Z_0-9]+]]]}> : () -> ()
 
 # Initializer function. This should contain the initialization sequence for the
 # variable.

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/multi_variables_v1.py

@@ -19,8 +19,8 @@
 import tensorflow.compat.v1 as tf
 from tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model import common_v1
 
-# CHECK: "tf_saved_model.global_tensor"() {is_mutable, sym_name = "[[VAR0:[a-zA-Z_0-9]+]]", type = tensor<5x3xf32>, value = {{.*}} : tensor<5x3xf32>} : () -> ()
-# CHECK: "tf_saved_model.global_tensor"() {is_mutable, sym_name = "[[VAR1:[a-zA-Z_0-9]+]]", type = tensor<3x5xf32>, value = {{.*}} : tensor<3x5xf32>} : () -> ()
+# CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR0:[a-zA-Z_0-9]+]]", type = tensor<5x3xf32>, value = {{.*}} : tensor<5x3xf32>}> : () -> ()
+# CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR1:[a-zA-Z_0-9]+]]", type = tensor<3x5xf32>, value = {{.*}} : tensor<3x5xf32>}> : () -> ()
 # CHECK:      func {{@[a-zA-Z_0-9]+}}(
 # CHECK-SAME:   [[ARG0:%.*]]: tensor<!tf_type.resource<tensor<5x3xf32>>> {tf_saved_model.bound_input = @[[VAR0]]},
 # CHECK-SAME:   [[ARG1:%.*]]: tensor<!tf_type.resource<tensor<3x5xf32>>> {tf_saved_model.bound_input = @[[VAR1]]})

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/partially_shaped_variables.py

@@ -24,8 +24,8 @@ class TestModule(tf.Module):
 
   def __init__(self):
     super(TestModule, self).__init__()
-    # CHECK: "tf_saved_model.global_tensor"() {is_mutable, {{.*}} tf_saved_model.exported_names = ["v0"], type = tensor<*xf32>, value = dense<0.000000e+00> : tensor<1xf32>} : () -> ()
-    # CHECK: "tf_saved_model.global_tensor"() {is_mutable, {{.*}} tf_saved_model.exported_names = ["v1"], type = tensor<?xf32>, value = dense<[0.000000e+00, 1.000000e+00]> : tensor<2xf32>} : () -> ()
+    # CHECK: "tf_saved_model.global_tensor"() <{is_mutable, {{.*}} type = tensor<*xf32>, value = dense<0.000000e+00> : tensor<1xf32>}> {tf_saved_model.exported_names = ["v0"]} : () -> ()
+    # CHECK: "tf_saved_model.global_tensor"() <{is_mutable, {{.*}} type = tensor<?xf32>, value = dense<[0.000000e+00, 1.000000e+00]> : tensor<2xf32>}> {tf_saved_model.exported_names = ["v1"]} : () -> ()
     self.v0 = tf.Variable([0.], shape=tf.TensorShape(None))
     self.v1 = tf.Variable([0., 1.], shape=[None])
 

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/remove_init_variable_v1.py

@@ -29,7 +29,7 @@
 # CHECK-SAME: min_consumer
 # CHECK-SAME: producer
 
-# CHECK: "tf_saved_model.global_tensor"() {is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", type = tensor<1x3xf32>, value = {{.*}} : tensor<1x3xf32>} : () -> ()
+# CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", type = tensor<1x3xf32>, value = {{.*}} : tensor<1x3xf32>}> : () -> ()
 # CHECK-NOT: session_initializer
 
 # CHECK:      func {{@[a-zA-Z_0-9]+}}(

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/shared_variable_v1.py

@@ -19,7 +19,7 @@
 import tensorflow.compat.v1 as tf
 from tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model import common_v1
 
-# CHECK: "tf_saved_model.global_tensor"() {is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", type = tensor<1x3xf32>, value = {{.*}} : tensor<1x3xf32>} : () -> ()
+# CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR:[a-zA-Z_0-9]+]]", type = tensor<1x3xf32>, value = {{.*}} : tensor<1x3xf32>}> : () -> ()
 
 # CHECK:      func {{@[a-zA-Z_0-9]+}}(
 # CHECK-SAME:   [[ARG0:%.*]]: tensor<3x1xf32> {tf_saved_model.index_path = ["x"]},

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model_optimize_global_tensors.mlir

@@ -8,9 +8,9 @@ module attributes {tf_saved_model.semantics} {
 
   // Test case: Basic test of marking immutable.
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-NOT: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []})
@@ -27,9 +27,9 @@ module attributes {tf_saved_model.semantics} {
 
   // Test case: Don't mark immutable if the variable is mutated.
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v})
@@ -47,9 +47,9 @@ module attributes {tf_saved_model.semantics} {
 
   // Test case: Don't mark immutable if the variable is exported.
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> {{{.*}}} : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", tf_saved_model.exported_names = ["v"], type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []})
@@ -148,9 +148,9 @@ module {}
 // Test use as an input in unhandled op
 module attributes {tf_saved_model.semantics} {
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v})
@@ -166,9 +166,9 @@ module attributes {tf_saved_model.semantics} {
 // Test use as a region capture in an unhandled op
 module attributes {tf_saved_model.semantics} {
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v})
@@ -187,14 +187,14 @@ module attributes {tf_saved_model.semantics} {
 // to the unhandled op.
 module attributes {tf_saved_model.semantics} {
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "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: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "u", type = tensor<f32>, value = dense<22.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}, %arg1: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @u})
@@ -212,14 +212,14 @@ module attributes {tf_saved_model.semantics} {
 // Test multiple global tensors uses as operands for an unhandled op.
 module attributes {tf_saved_model.semantics} {
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "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: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "u", type = tensor<f32>, value = dense<22.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}, %arg1: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @u})

tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model_optimize_global_tensors_interprocedural.mlir

@@ -9,9 +9,9 @@ module attributes {tf_saved_model.semantics} {
   // Test case: This test exercises marking a global tensor as immutable after it propagates
   // via set of chained calls -> f -> f_callee -> f_callee_callee
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-NOT: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []})
@@ -39,11 +39,11 @@ module attributes {tf_saved_model.semantics} {
   // Test case:
   // This test exercises trying to mark immutable when same func is called by multiple callers
   // with different global tensors.
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // 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: "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> } : () -> ()
 
@@ -73,9 +73,9 @@ module attributes {tf_saved_model.semantics} {
   // Test case: This test exercises immutability without explicit use
   // via ReadVariableOp
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-NOT: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []})
@@ -99,9 +99,9 @@ module attributes {tf_saved_model.semantics} {
 
 // CHECK-LABEL: module attributes {tf_saved_model.semantics}
 module attributes {tf_saved_model.semantics} {
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   // CHECK: func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v})
@@ -133,9 +133,9 @@ module attributes {tf_saved_model.semantics} {
   // Test case: The inter-procedural analysis with different types of
   // TF call ops
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   // CHECK: func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v})
@@ -166,9 +166,9 @@ module attributes {tf_saved_model.semantics} {
 
   // Test case: The inter-procedural analysis does not recurse infinitely
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-NOT: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @exported_f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []})
@@ -199,9 +199,9 @@ module attributes {tf_saved_model.semantics} {
   // Test case: Inter-procedural analysis with resource usage in an
   // unknown op, we assume mutating behavior and propagate that.
 
-  // CHECK: "tf_saved_model.global_tensor"() {
+  // CHECK: "tf_saved_model.global_tensor"() <{
   // CHECK-SAME: is_mutable
-  // CHECK-SAME: } : () -> ()
+  // CHECK-SAME: }> : () -> ()
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()
 
   func.func @exported_f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []})