return h.commonHandler.enabled(level)
}

// WithAttrs returns a new [TextHandler] whose attributes consists
// of h's attributes followed by attrs.
func (h *TextHandler) WithAttrs(attrs []Attr) Handler {
	return &TextHandler{commonHandler: h.commonHandler.withAttrs(attrs)}
}

func (h *TextHandler) WithGroup(name string) Handler {
	return &TextHandler{commonHandler: h.commonHandler.withGroup(name)}
}

  return absl::OkStatus();
}

Status Encapsulator::GetFunctionNameAttr(Node const* node, string* attr) const {
  AttrSlice attrs = node->attrs();
  attr->clear();
  for (const auto& node_attr : attrs) {
    if (node_attr.first == group_attribute_) {
      TF_RETURN_IF_ERROR(AttrValueHasType(node_attr.second, "string"));
      *attr = node_attr.second.s();
      break;
    }
  }
  return absl::OkStatus();
}

  let description = [{
    The `attr` operation stores TF op's attribute, which doesn't support
    arithmetic operations.

    Example:

    ```mlir
    %1 = "tfr.constant"() { value: i32 } : () -> !tfr.attr
    %2 = "tfr.constant"() { value: [i32, f32] } : () -> !tfr.attr
    %3 = tfr.constant [i32, f32] -> !tfr.attr
    %4 = tfr.constant f32 -> !tfr.attr
    ```
  }];

type AttrTest struct {
	Int   int     `xml:",attr"`
	Named int     `xml:"int,attr"`
	Float float64 `xml:",attr"`
	Uint8 uint8   `xml:",attr"`
	Bool  bool    `xml:",attr"`
	Str   string  `xml:",attr"`
	Bytes []byte  `xml:",attr"`
}

type AttrsTest struct {
	Attrs []Attr  `xml:",any,attr"`
	Int   int     `xml:",attr"`
	Named int     `xml:"int,attr"`
	Float float64 `xml:",attr"`
	Uint8 uint8   `xml:",attr"`

A. Unique TensorFlower <******@****.***> 1651827499 -0700

// RUN: tf-mlir-translate -mlir-to-graphdef %s -o - | FileCheck %s

// Verify that attribute T is not set as ref type.
// CHECK-LABEL: name: "Ref_Variable"
// CHECK-LABEL: name: "foo"
// CHECK:      attr {
// CHECK-NEXT:   key: "T"
// CHECK-NEXT:   value {
// CHECK-NEXT:     type: DT_INT32{{$}}
// CHECK-NEXT:   }
// CHECK-NEXT: }

func.func @main() {
  tf_executor.graph {

Yifan Jiang <******@****.***> 1684349180 -0700

to create tf2xla kernel: INVALID_ARGUMENT: NodeDef missing attrs 'shrink_axis_mask', 'new_axis_mask', 'begin_mask', 'ellipsis_mask', 'end_mask' from Op<name=StridedSlice; signature=input:T, begin:Index, end:Index, strides:Index -> output:T; attr=T:type; attr=Index:type,allowed=[DT_INT16, DT_INT32, DT_INT64]; attr=begin_mask:int,default=0; attr=end_mask:int,default=0; attr=ellipsis_mask:int,default=0; attr=new_axis_mask:int,default=0; attr=shrink_axis_mask:int,default=0>; NodeDef: {{node tf.StridedSlice}}}}...

    attrs = {
        "model_name": attr.string(),
        "srcs": attr.label_list(mandatory = True, allow_files = True),
        "header_out": attr.output(),
        "cmd": attr.string(),
        "tfcompile_tool": attr.label(cfg = "exec", executable = True, allow_files = True),
        "tfcompile_graph": attr.label(allow_single_file = True),
        "tfcompile_config": attr.label(allow_single_file = True),

        def attrs = ImmutableAttributes.EMPTY

        expect:
        registry.mapAttributesFor(attrs, []) == attrs
    }

    def "does not apply any mapping when variant has no artifacts"() {
        def attrs = ImmutableAttributes.EMPTY

        given:
        registry.create().create("aar")

        expect:
        registry.mapAttributesFor(attrs, []) == attrs
    }