name: "custom_relu"
    }
    attr {
      key: "_implements"
      value {
        func {
          name: "tensorflow.relu"
        }
      }
    }
  }
  function {
    signature {
      name: "custom_embedding_matmul"
    }
    attr {
      key: "_implements"
      value {
        func {
          name: "tensorflow.embedding_matmul"
          attr {
            key: "key1"

      new llvm::StringSet<>({"asymmetric_quantize_inputs"});
  return *ops;
}

void CollectAllowedAttrs(CallOp src, NamedAttrList* attrs) {
  for (auto& attr : src->getAttrs()) {
    if (GetAllowedAttributes().contains(attr.getName().strref())) {
      attrs->append(attr);
    }
  }
}

// Adds `attrs` to all the operations between `begin` and `end` in the same
// block. Does not include `end`.

		}
	}
	ne := countEmptyGroups(attrs[i:])
	r.back = slices.Grow(r.back, len(attrs[i:])-ne)
	for _, a := range attrs[i:] {
		if !a.Value.isEmptyGroup() {
			r.back = append(r.back, a)
		}
	}
}

// Add converts the args to Attrs as described in [Logger.Log],
// then appends the Attrs to the [Record]'s list of Attrs.
// It omits empty groups.
func (r *Record) Add(args ...any) {

      // will not use this representation.
      mlir::NamedAttrList attrs;
      for (const auto& func_attr : value.func().attr()) {
        TF_ASSIGN_OR_RETURN(auto attr,
                            ConvertAttributeValue(func_attr.second, builder));
        attrs.push_back(builder->getNamedAttr(func_attr.first, attr));
      }
      auto func_attrs = builder->getDictionaryAttr(attrs);

}

func newRecordWithAttrs(as []Attr) Record {
	r := NewRecord(time.Now(), LevelInfo, "", 0)
	r.AddAttrs(as...)
	return r
}

func attrsSlice(r Record) []Attr {
	s := make([]Attr, 0, r.NumAttrs())
	r.Attrs(func(a Attr) bool { s = append(s, a); return true })
	return s
}

func attrsEqual(as1, as2 []Attr) bool {
	return slices.EqualFunc(as1, as2, Attr.Equal)
}

// RUN: tf-mlir-translate -mlir-tf-mlir-to-str-attr -mlir-print-local-scope %s | FileCheck %s

module attributes {tf.versions = {producer = 888 : i32}} {
  func.func @main(%arg0: tensor<?xi32>) -> tensor<?xi32> {
    %0 = "tf.Identity"(%arg0) : (tensor<?xi32>) -> tensor<?xi32> loc(unknown)
    func.return %0 : tensor<?xi32> loc(unknown)
  } loc(unknown)
} loc(unknown)

	// stack consists of IP point-to-point numbered or unnumbered
	// addressing.
	for _, a := range attrs {
		if a.Attr.Type == syscall.IFA_LOCAL {
			ipPointToPoint = true
			break
		}
	}
	for _, a := range attrs {
		if ipPointToPoint && a.Attr.Type == syscall.IFA_ADDRESS {
			continue
		}
		switch ifam.Family {
		case syscall.AF_INET:

      DeviceNameUtils::ParsedName device;
      if (DeviceNameUtils::ParseFullName(device_name, &device) &&
          device.has_job && device.job == jobType) {
        for (const auto& attr : node->attrs()) {
          auto attr_key = attr.first;
          auto attr_value = attr.second;
          if (attr_key == attrKey &&
              attr_value.value_case() == AttrValue::kType &&
              attr_value.type() == DT_RESOURCE) {
            return true;

      // as shared names.
      if (!std::any_of(op_def.attr().begin(), op_def.attr().end(),
                       [](const auto& attr_def) {
                         return attr_def.name() == "use_node_name_sharing" &&
                                attr_def.type() == "bool";
                       }))
        return false;
    }

    if (!std::any_of(op_def.attr().begin(), op_def.attr().end(),
                     [](const auto& attr_def) {

			t.Fatal(err)
		}
		got := h.ringBuffer[0]
		if !got.Time.Equal(r.Time) || !slices.EqualFunc(attrSlice(got), attrSlice(r), slog.Attr.Equal) {
			t.Errorf("got %+v, want %+v", got, r)
		}
	})
}

func attrSlice(r slog.Record) []slog.Attr {
	var as []slog.Attr
	r.Attrs(func(a slog.Attr) bool { as = append(as, a); return true })
	return as