if err != nil {
				return fmt.Errorf("go tool compile -o %s %s: %v\n%s", go2obj, go2src, err, out)
			}
			out, err = testenv.Command(t, gotool, "tool", "pack", "c", goarchive, go1obj, go2obj).CombinedOutput()
			if err != nil {
				return fmt.Errorf("go tool pack c %s %s %s: %v\n%s", goarchive, go1obj, go2obj, err, out)
			}

			if testenv.HasCGO() {
				cgoarchive = filepath.Join(buildDir, "mycgo.a")

  }
};

std::unique_ptr<TargetHardwareOperation> CreateBasicOpNoCost() {
  return std::make_unique<NNAPIBasicSupportedOpNoCost>();
}

// Currently used for these ops:
// tfl.concatenation / tfl.reshape / tfl.pack
class NNAPIConcatOp : public TargetHardwareOperation {
  double GetOpCost(mlir::Operation* op) const override {
    int64_t count;
    if (ArithmeticCountUtilHelper::GetInputTensorTotalSize(op, &count))

                          </td>
            <td></td>
          </tr>
                  <tr>
            <td><a href="https://oss.sonatype.org/content/repositories/snapshots/org/codelibs/fess/fess-xpack/">fess-xpack/</a></td>
            <td>Sun Jun 02 23:11:23 UTC 2019</td>
            <td align="right">
                              &nbsp;
                          </td>
            <td></td>
          </tr>

		t.Tag.goString(indent+2, "Tag: "))
}

// PackExpansion is a pack expansion.  The Pack field may be nil.
type PackExpansion struct {
	Base AST
	Pack *ArgumentPack
}

func (pe *PackExpansion) print(ps *printState) {
	// We normally only get here if the simplify function was
	// unable to locate and expand the pack.
	if pe.Pack == nil {
		if ps.llvmStyle {
			ps.print(pe.Base)
		} else {

  // Fold pack operation if it computes the input tensor shape:
  //
  //   %shape  = tf.Shape(%arg)                    // [? x ...]
  //   %dim0   = tf.StridedSlice(%shape, 0, 1, 1)  // get unknown dim0 value
  //   %pack   = tf.Pack(dim0, ...) { axis = 0 }   // [? x ...]
  //
  // Where `...` are some statically known dimensions. In this case %pack can be

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir {
namespace TFL {
namespace tac {

// TODO(renjieliu): add more patterns.

// This basically:
// Pack => (Concat -> Reshape)
struct LowerPackIntoConcatReshape : public OpRewritePattern<TFL::PackOp> {
  using OpRewritePattern<TFL::PackOp>::OpRewritePattern;

  LogicalResult matchAndRewrite(TFL::PackOp pack_op,

// A ParallelDevice on its own is not registered with a TFE_Context, and so has
// no device name (e.g. for `tf.device`). `NamedParallelDevice` associates a
// name with it, which lets us pack its `ParallelTensor`s into TFE_TensorHandles
// placed on the parallel device.
class NamedParallelDevice {
 public:
  NamedParallelDevice(const std::string& name,

// for various reasons (historical, convenience).
type Sym struct {
	Linkname string // link name

	Pkg  *Pkg
	Name string // object name

	// The unique ONAME, OTYPE, OPACK, or OLITERAL node that this symbol is
	// bound to within the current scope. (Most parts of the compiler should
	// prefer passing the Node directly, rather than relying on this field.)
	//

  using OpRewritePattern::OpRewritePattern;

  LogicalResult matchAndRewrite(TF::TensorListPopBackOp op,
                                PatternRewriter& rewriter) const override {
    // It is currently not possible to easily pack the output of a multi-result
    // op into an op with a single varidic output in `.td`.
    auto converted = rewriter.create<TFL::CustomOp>(
        op->getLoc(), op->getResultTypes(), op->getOperands(),

		st.advance(2)
		e := st.expression()
		pack := st.findArgumentPack(e)
		return &PackExpansion{Base: e, Pack: pack}
	} else if st.str[0] == 's' && len(st.str) > 1 && st.str[1] == 'Z' {
		st.advance(2)
		off := st.off
		e := st.expression()
		ap := st.findArgumentPack(e)
		if ap == nil {
			st.failEarlier("missing argument pack", st.off-off)
		}
		return &SizeofPack{Pack: ap}