// RUN: tf-opt %s --tf-decompose-optionals --split-input-file | FileCheck %s

// CHECK-LABEL: @from_value
func.func @from_value(%arg0: tensor<f32>) {
  // CHECK-NOT: Optional
  %0 = "tf.OptionalFromValue"(%arg0) : (tensor<f32>) -> tensor<!tf_type.variant<tensor<f32>>>
  return
}

// -----

// CHECK-LABEL: @get_value
func.func @get_value(%arg0: tensor<!tf_type.variant<tensor<f32>>>) {
  // CHECK-NOT: Optional

  let hasVerifier = 1;
}

def TF_SplitVOp : TF_Op<"SplitV", [Pure]> {
  let summary = "Splits a tensor into `num_split` tensors along one dimension.";

  let arguments = (ins
    Arg<TF_Tensor, [{The tensor to split.}]>:$value,
    Arg<TensorOf<[TF_Int32, TF_Int64, TF_Int8]>, [{list containing the sizes of each output tensor along the split
dimension. Must sum to the dimension of value along split_dim.

		{"error", "error log", nil},
		{"info", "with labels", ptr.Of(float64(2))},
	}
	// For each level, there should be two lines, one from direct log,
	// the other one from UDS server
	gotLogs := strings.Split(
		strings.TrimSuffix(string(out), "\n"), "\n")
	if want, got := len(cases)*2, len(gotLogs); want != got {
		t.Fatalf("Number of logs want %v, got %v logs: %v", want, got, gotLogs)
	}
	i := 0
	for _, l := range gotLogs {

	encodedResource := req.URL.RawPath
	encodedQuery := req.URL.RawQuery
	if encodedResource == "" {
		splits := strings.SplitN(req.URL.Path, "?", 2)
		encodedResource = splits[0]
		if len(splits) == 2 {
			encodedQuery = splits[1]
		}
	}

	unescapedQueries, err := unescapeQueries(encodedQuery)
	if err != nil {
		return err
	}

        "//tensorflow/lite/tools/optimize:testdata/single_softmax_min_minus_5_max_plus_5.bin",
        "//tensorflow/lite/tools/optimize:testdata/split.bin",
        "//tensorflow/lite/tools/optimize:testdata/svdf_calibrated.bin",
        "//tensorflow/lite/tools/optimize:testdata/svdf_quantized.bin",
        "//tensorflow/lite/tools/optimize:testdata/transpose.bin",

    res.status = 200
    res.body = {'status' => 'Details is healthy'}.to_json
    res['Content-Type'] = 'application/json'
end

server.mount_proc '/details' do |req, res|
    pathParts = req.path.split('/')
    headers = get_forward_headers(req)

    begin
        begin
          id = Integer(pathParts[-1])
        rescue
          raise 'please provide numeric product id'
        end

	}
	if len(s) == 0 {
		return
	}
	for _, p := range strings.Split(s, ",") {
		if p == "" {
			continue
		}
		slc := strings.Split(p, "=")
		if len(slc) != 2 {
			return r, errInvalidReplicateDecisionFormat
		}
		tgtStr := strings.TrimSuffix(strings.TrimPrefix(slc[1], `"`), `"`)
		tgt := strings.Split(tgtStr, ";")
		if len(tgt) != 4 {
			return r, errInvalidReplicateDecisionFormat
		}

        "@llvm-project//mlir:FuncDialect",
        "@llvm-project//mlir:IR",
        "@llvm-project//mlir:Pass",
        "@llvm-project//mlir:Support",
    ],
    alwayslink = 1,
)

# TODO(b/177376459): split tac_module and passes dependency to separate libraries.
cc_library(
    name = "target_aware_conversion",
    srcs = [
        "tac_module.cc",
        "transforms/compute_cost.cc",

}

func (i *informer[I]) GetKey(k Key[I]) *I {
	// ns, n := splitKeyFunc(string(k))
	// Internal optimization: we know kclient will eventually lookup "ns/name"
	// We also have a key in this format.
	// Rather than split and rejoin it later, just pass it as the name
	// This is depending on "unstable" implementation details, but we own both libraries and tests would catch any issues.
	if got := i.inf.Get(string(k), ""); !controllers.IsNil(got) {

// the empty value and an error indicating the parse failure.
func parseRestoreObjStatus(restoreHdr string) (restoreObjStatus, error) {
	tokens := strings.SplitN(restoreHdr, ",", 2)
	progressTokens := strings.SplitN(tokens[0], "=", 2)
	if len(progressTokens) != 2 {
		return restoreObjStatus{}, errRestoreHDRMalformed
	}
	if strings.TrimSpace(progressTokens[0]) != "ongoing-request" {