}];

  let arguments = (ins
    StrAttr:$device
  );

  let results = (outs
    Variadic<AnyType>:$results
  );

  let regions = (region SizedRegion<1>:$body);

  let extraClassDeclaration = [{
    Block &GetBody() { return getOperation()->getRegion(0).front(); }
    bool WrapsSingleOp();
  }];

  let builders = [
    OpBuilder<(ins "StringAttr":$device, "TypeRange":$result_types),
    [{

// it is legal to use a quantized representation (but is not known to be
// acceptable).
def Quantization_QuantizeCastOp : Quantization_Op<"qcast", [Pure]> {
  let arguments = (ins quant_RealValueType:$arg);
  let results = (outs quant_RealValueType);
}

// A DequantizeCast op (dcast) represents the inverse of a qcast,
// converting back from a quantized to quantizable (expressed) type.
//

def TF_UniformQuantizedDotGeneralOp : TF_Op<"UniformQuantizedDotGeneral", [Pure]> {
  // TODO(b/230804708): Improve the operator description.
  let summary = "Quantized dot general operator.";

  let arguments = (ins
    TensorOf<[TF_Float32, TF_Qint8]>:$lhs,
    TensorOf<[TF_Qint8]>:$rhs,
    TF_Float32Tensor:$lhs_scales,
    TF_Int32Tensor:$lhs_zps,
    TF_Float32Tensor:$rhs_scales,
    TF_Int32Tensor:$rhs_zps,

  let description = [{
    Setting a tensor value in TFRT runtime's static resource manager, using
    index as its identifier. It can be retrieved by _TfrtGetResource using the
    same index.
  }];

  let arguments = (ins
    TF_Tensor:$arg,
    I64Attr:$index
  );
}

def TF__TfrtGetResourceOp : TF_Op<"_TfrtGetResource",
    [Pure, TF_NoConstantFold, DeclareOpInterfaceMethods<TF_ResourceHandleAllocatorInterface>]> {

  let description = [{
    Transfer a CPU tensor to device.

    Example:
      %device_tensor = gpurt.transfer_to_device %cpu_tensor
  }];

  let arguments = (ins TFTensorType);
  let results = (outs TFTensorType);
  let assemblyFormat = "operands attr-dict";
}

// TODO(b/260267885): We may add a device argument when we want to support
// GPU MIG.

    Await a tensor from a !mlrt.future.

    $future: A value of type !mlrt.future. The underlying value must be a tensorflow tensor.

    $result: a tensorflow tensor.
  }];

  let arguments = (ins
    MlrtFutureType:$future
  );

  let results = (outs
    TF_Tensor:$result
  );
}

// tf_mlrt.tf_promise takes a tensorflow Tensor. It is a fake op that is only

    private val directDependentsByKtModule: Map<KtModule, Set<KtModule>> by lazy {
        // Direct dependencies should be computed lazily, because the built-ins module will be reachable via module dependencies. Getting
        // the built-ins module relies on the built-ins session, which may depend on services that are registered after
        // `KtStaticModuleDependentsProvider`.
        buildDependentsMap(modules) { it.allDirectDependencies() }

		for _, ent := range tt.ents {
			testStaticHost(t, tt.name, ent)
		}
	}
}

func testStaticHost(t *testing.T, hostsPath string, ent staticHostEntry) {
	ins := []string{ent.in, absDomainName(ent.in), strings.ToLower(ent.in), strings.ToUpper(ent.in)}
	for _, in := range ins {
		addrs, _ := lookupStaticHost(in)
		if !reflect.DeepEqual(addrs, ent.out) {
			t.Errorf("%s, lookupStaticHost(%s) = %v; want %v", hostsPath, in, addrs, ent.out)
		}

	if err := os.Mkdir(outdir, 0777); err != nil {
		t.Fatalf("can't create outdir %s: %v", outdir, err)
	}

	// Merge the two dirs into a final result.
	ins := fmt.Sprintf("-i=%s,%s", indir1, indir2)
	out := fmt.Sprintf("-o=%s", outdir)
	margs := []string{ins, out}
	lines := runToolOp(t, s, "merge", margs)
	if len(lines) != 0 {
		t.Errorf("merge run produced %d lines of unexpected output", len(lines))
		dumplines(lines)

            res.setEntry(resEntry);

            res.setScope(requestedScope);

            for (MetadataGraphVertex v : vertices) {
                final List<MetadataGraphEdge> ins = graph.getIncidentEdges(v);
                final MetadataGraphEdge edge = cleanEdges(v, ins, requestedScope);

                if (edge == null) { // no edges - don't need this vertex anymore
                    if (entry.equals(v)) { // unless it's an entry point.