This transformation pass modifies the input and output types of the function
      to what are specified. The task was not just adding cast operations, but,
      instead, using tfl.quantize and tfl.dequantize ops to scale the tensors.
  }];
  let constructor = "CreateModifyIONodesPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
  let options = [
      ListOption<"io_node_types_", "test-io-types", "std::string",

{% block metas %}
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
{% endblock %}

<title>Simple Bookstore App</title>
{% block scripts %}
<script src="static/tailwind/tailwind.css"></script>
<script type="text/javascript">
  window.addEventListener("DOMContentLoaded", (event) => {
    const dialog = document.querySelector("dialog");

	// is likely to be the originator, so requeuing would hot-loop us.  Failures are requeued by the workqueue directly.
	// This is a low traffic and scale resource, so the copy is terrible.  It's not good, so better ideas
	// are welcome.
	oldCopy := oldCRD.DeepCopy()
	newCopy := newCRD.DeepCopy()
	oldCopy.ResourceVersion = ""
	newCopy.ResourceVersion = ""

        if (op->hasOneUse() &&
            op->user_begin()->hasTrait<OpTrait::IsTerminator>())
          return failure();
      }
      // If the quantize op is a requantize op, it is being used in other scale
      // adjustments and should be kept. Instead, moving dequantize op before
      // the requantize op to remove the unnecessary requantize op.
      if (auto qtype = quant::QuantizedType::getQuantizedElementType(

	return RegisterDefaults(scheme)
}

func SetDefaults_ResourceList(obj *v1.ResourceList) {
	for key, val := range *obj {
		// TODO(#18538): We round up resource values to milli scale to maintain API compatibility.
		// In the future, we should instead reject values that need rounding.
		const milliScale = -3
		val.RoundUp(milliScale)

		(*obj)[v1.ResourceName(key)] = val
	}
}

//
// It uses a brute-force recursive approach to enumerate all objects
// defined by dependencies of pkg, so that it can learn the set of
// package paths that may be mentioned in the fact encoding. This does
// not scale well; use [NewDecoderFunc] where possible.
func NewDecoder(pkg *types.Package) *Decoder {
	// Compute the import map for this package.
	// See the package doc comment.
	m := importMap(pkg.Imports())

func (p *Parser) validSymbol(pseudo string, addr *obj.Addr, offsetOk bool) bool {
	if addr.Sym == nil || addr.Name != obj.NAME_EXTERN && addr.Name != obj.NAME_STATIC || addr.Scale != 0 || addr.Reg != 0 {
		p.errorf("%s symbol %q must be a symbol(SB)", pseudo, symbolName(addr))
		return false
	}
	if !offsetOk && addr.Offset != 0 {

			//  get below a certain floor value, since we want the server to
			//  drain the active watch requests as soon as possible.
			//  For now, it's hard coded to 200, and it is subject to change
			//  based on the result from the scale testing.
			if qps < 200 {
				qps = 200
			}

			ctx, cancel := context.WithTimeout(context.Background(), grace)
			// We don't expect more than one token to be consumed