// or return 0 if they cannot be combined.
func mergePPC64SldiSrw(sld, srw int64) int64 {
	if sld > srw || srw >= 32 {
		return 0
	}
	mask_r := uint32(0xFFFFFFFF) >> uint(srw)
	mask_l := uint32(0xFFFFFFFF) >> uint(sld)
	mask := (mask_r & mask_l) << uint(sld)
	return encodePPC64RotateMask((32-srw+sld)&31, int64(mask), 32)
}

// Convert a PPC64 opcode from the Op to OpCC form. This converts (op x y)

		// Whatever user has set (with --log_output_level) for 'cni-plugin', pass it down to the plugin. It will use this to determine
		// what level to use for itself.
		// This masks the fact we are doing this weird log-over-UDS to users, and allows them to configure it the same way.
		PluginLogLevel:        istiolog.LevelToString(istiolog.FindScope(constants.CNIPluginLogScope).GetOutputLevel()),

on Go programs. In rare cases, the non-Go code may run before the Go
code, in which case the next section also applies.

If the non-Go code called by the Go program does not change any signal
handlers or masks, then the behavior is the same as for a pure Go
program.

If the non-Go code installs any signal handlers, it must use the
SA_ONSTACK flag with sigaction. Failing to do so is likely to cause

		s.writeErrorResponse(w, errInvalidArgument)
		return
	}
	var verifier *BitrotVerifier
	if r.Form.Get(storageRESTBitrotAlgo) != "" {
		hashStr := r.Form.Get(storageRESTBitrotHash)
		var hash []byte
		hash, err = hex.DecodeString(hashStr)
		if err != nil {
			s.writeErrorResponse(w, err)
			return
		}
		verifier = NewBitrotVerifier(BitrotAlgorithmFromString(r.Form.Get(storageRESTBitrotAlgo)), hash)

    std::string flops_str;
    std::string mac_str;
    if (ops_count < 10000) {
      flops_str = absl::StrFormat("%ld ", ops_count);
      mac_str = absl::StrFormat("%ld ", ops_count / 2);
    } else if (ops_count < billion) {
      flops_str =
          absl::StrFormat("%.3f M ", static_cast<double>(ops_count) / million);
      mac_str = absl::StrFormat("%.3f M ",

    // Output shape needs to be static to apply 'new_axis_mask' or
    // 'shrink_axis_mask' by reshaping tensor after slice.
    //
    // TODO(hinsu): Relax this constraint for ops without the above masks.
    auto result_ty = mlir::dyn_cast<RankedTensorType>(op.getType());
    if (!result_ty || !result_ty.hasStaticShape()) return failure();

    DenseIntElementsAttr sparse_begin_attr, sparse_end_attr;

  0. Definitions.

  "This License" refers to version 3 of the GNU Affero General Public License.

  "Copyright" also means copyright-like laws that apply to other kinds of
works, such as semiconductor masks.

  "The Program" refers to any copyrightable work licensed under this
License.  Each licensee is addressed as "you".  "Licensees" and
"recipients" may be individuals or organizations.

        [`tf.keras.layers.MultiHeadAttention`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MultiHeadAttention).
        *   Implicit masks for `query`, `key` and `value` inputs will
            automatically be used to compute a correct attention mask for the
            layer. These padding masks will be combined with any
            `attention_mask` passed in directly when calling the layer. This can
            be used with

		// In that case (handled below), we emit a bound check (and Spectre mask)
		// and then the prove pass will remove the bounds check.
		// In theory the prove pass could potentially remove certain
		// Spectre masks, but it's very delicate and probably better
		// to be conservative and leave them all in.
		return idx
	}

	bNext := s.f.NewBlock(ssa.BlockPlain)
	bPanic := s.f.NewBlock(ssa.BlockExit)

`end = begin + 1 = 2`. To disambiguate from the original spec `2:4` we
also set the appropriate bit in `shrink_axis_mask`.

2. `2:4` is contributes 2, 4, 1 to begin, end, and stride. All masks have
zero bits contributed.

3. None is a synonym for `tf.newaxis`. This means insert a dimension of size 1
dimension in the final shape. Dummy values are contributed to begin,