// RUN: tf-tfrt-opt -tf-to-tfrt %s | FileCheck %s --dump-input=fail

// _output_shapes and f.* attributes are removed during tf-to-tfrt lowering.
// CHECK-LABEL: func @remove_unused_attr
func.func @remove_unused_attr() {
  // CHECK: %out_op_chain = tfrt_fallback_async.executeop.seq(%arg0) key(0) cost({{.*}}) device("/device:CPU:0") "tf.SomeOp2"()

    // CHECK: tf_executor.island wraps "tf.VarHandleOp"() <{container = "a", shared_name = "x"}> {_mlir_name = "x", _output_shapes = [#tf_type.shape<>], allowed_devices = [], device = "/device:CPU:0", dtype = i64, shape = #tf_type.shape<>} : () -> tensor<!tf_type.resource<tensor<i64>>>

  %0 = "tf.ReadVariableOp"(%handle) {_output_shapes = ["tfshape$dim { size: 3 }"], device = "/device:CPU:0", dtype = f32} : (tensor<!tf_type.resource<tensor<3xf32>>>) -> tensor<3xf32>

# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -o - | FileCheck %s

node {
  name: "unnamed"
  op: "foo"
  attr {
    key: "_output_shapes"
    value {
      list {
        shape {
        }
      }
    }
  }
  attr {
    key: "_disable_call_shape_inference"
    value {
      b: true
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "unnamed1"

    %arg1: tensor<1x3xf32> {tf_saved_model.index_path = [0]})
      -> (tensor<3x3xf32> {tf_saved_model.index_path = []}) {
  // CHECK: {{%.*}} = corert.get_op_handler %arg0 "/device:GPU:0"
  %2 = "tf.MatMul"(%arg0, %arg1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:GPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
  func.return %2 : tensor<3x3xf32>

    tf_executor.fetch
  }
  func.return
}

// CHECK:       name: "RecvTPUEmbedding"
// CHECK-NEXT:  op: "RecvTPUEmbeddingActivations"
// CHECK-NEXT:  attr {
// CHECK-NEXT:    key: "_output_shapes"
// CHECK-NEXT:    value {
// CHECK-NEXT:      list {
// CHECK-NEXT:        shape {
// CHECK-NEXT:          dim {
// CHECK-NEXT:            size: 512
// CHECK-NEXT:          }
// CHECK-NEXT:          dim {

// `ignore_unregistered_attrs` argument is set to true, the attributes which are
// not in the op registry will be ignored. If the `ignore_unregistered_attrs`
// argument is not set to true, _output_shapes attribute is added to nodes with
// ShapedType for the leading values with ShapedType in the results of the
// nodes. Set it to true if the returned NodeDef will be executed by the linked
// TF Eager runtime.

    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> unconditionally_use_set_output_shapes(
    "tf-enable-unconditionally-use-set-output-shapes-on-import",
    llvm::cl::desc("Enable using the _output_shapes unconditionally on import "
                   "(temporary)"),
    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> enable_soft_placement(
    "tf-enable-soft-placement-on-import",

  bool restrict_functionalization_to_compiled_nodes = false;
  // If true, enables shape inference on input.
  // TODO(jpienaar): This will be removed shortly.
  bool enable_shape_inference = true;
  // _output_shapes is an unregistered attribute which is used during
  // GraphConstructor::ConvertGraph to override shapes. It is unfortunately
  // not always set correctly (which is undesirable and should be addressed)

  // Create a bad output shape attr.
  AttrValue shape_attr;
  TensorShapeProto* shape_proto = shape_attr.mutable_list()->add_shape();
  shape_proto->add_dim()->set_size(1);
  builder.Attr("_output_shapes", shape_attr);

  TF_RETURN_IF_ERROR(builder.Finalize(&node));

  return CreateSingleOpGraph(node, {}, {DataType::DT_INT32});
}

absl::Status BuildHloFromGraph(Graph& graph, bool use_output_shapes) {