const char* name) {
  unique_tensor_ptr tensor(BoolTensor(v), TF_DeleteTensor);
  return Const(tensor.get(), graph, s, name);
}

TF_Operation* ScalarConst(int32_t v, TF_Graph* graph, TF_Status* s,
                          const char* name) {
  unique_tensor_ptr tensor(Int32Tensor(v), TF_DeleteTensor);
  return Const(tensor.get(), graph, s, name);
}

			}
		case []interface{}: // Handle array types.
			if len(condt) != 3 { // Return error if we have insufficient elements.
				return parsedPolicy, fmt.Errorf("Malformed conditional fields %s of type %s found in POST policy form", condt, reflect.TypeOf(condt).String())
			}
			switch toLowerString(condt[0]) {
			case policyCondEqual, policyCondStartsWith:
				for _, v := range condt { // Pre-check all values for type.
					if !isString(v) {

pkg debug/elf, const R_390_COPY = 9
pkg debug/elf, const R_390_COPY R_390
pkg debug/elf, const R_390_GLOB_DAT = 10
pkg debug/elf, const R_390_GLOB_DAT R_390
pkg debug/elf, const R_390_GOT12 = 6
pkg debug/elf, const R_390_GOT12 R_390
pkg debug/elf, const R_390_GOT16 = 15
pkg debug/elf, const R_390_GOT16 R_390
pkg debug/elf, const R_390_GOT20 = 58
pkg debug/elf, const R_390_GOT20 R_390
pkg debug/elf, const R_390_GOT32 = 7

pkg math (linux-arm), const MaxInt = 2147483647
pkg math (linux-arm), const MaxUint = 4294967295
pkg math (linux-arm), const MinInt = -2147483648
pkg math (linux-arm-cgo), const MaxInt = 2147483647
pkg math (linux-arm-cgo), const MaxUint = 4294967295
pkg math (linux-arm-cgo), const MinInt = -2147483648
pkg math (netbsd-386), const MaxInt = 2147483647
pkg math (netbsd-386), const MaxUint = 4294967295

-	  ((const char *) (src))[2], ((const char *) (src))[3],		      \
-	  ((const char *) (src))[4], ((const char *) (src))[5] } }),	      \
-     __extension__ ((__STRING2_COPY_ARR7)				      \
-      { { ((const char *) (src))[0], ((const char *) (src))[1],		      \
-	  ((const char *) (src))[2], ((const char *) (src))[3],		      \
-	  ((const char *) (src))[4], ((const char *) (src))[5],		      \

    const TF_Operation* const* opers, int ninputs, const TF_Output* inputs,
    int noutputs, const TF_Output* outputs, const char* const* output_names,
    int ncontrol_outputs, const TF_Operation* const* control_outputs,
    const char* const* control_output_names, const TF_FunctionOptions* opts,
    const char* description, TF_Status* status) {
  tensorflow::mutex_lock l(fn_body->mu);

  // Process inputs.

    TFE_MonitoringStringGauge2* gauge, const char* label1, const char* label2) {
  return static_cast<TFE_MonitoringStringGaugeCell*>(
      static_cast<void*>(gauge->gauge->GetCell(label1, label2)));
}

TFE_MonitoringStringGauge3* TFE_MonitoringNewStringGauge3(
    const char* name, TF_Status* status, const char* description,
    const char* label1, const char* label2, const char* label3) {

pkg debug/elf, const PT_OPENBSD_NOBTCFI = 1705237480 #66054
pkg debug/elf, const PT_OPENBSD_NOBTCFI ProgType #66054
pkg debug/elf, const STT_GNU_IFUNC = 10 #66836
pkg debug/elf, const STT_GNU_IFUNC SymType #66836
pkg debug/elf, const STT_RELC = 8 #66836
pkg debug/elf, const STT_RELC SymType #66836
pkg debug/elf, const STT_SRELC = 9 #66836
pkg debug/elf, const STT_SRELC SymType #66836

				this.mem.setUint32(addr, id, true);
			}

			const loadSlice = (addr) => {
				const array = getInt64(addr + 0);
				const len = getInt64(addr + 8);
				return new Uint8Array(this._inst.exports.mem.buffer, array, len);
			}

			const loadSliceOfValues = (addr) => {
				const array = getInt64(addr + 0);
				const len = getInt64(addr + 8);
				const a = new Array(len);
				for (let i = 0; i < len; i++) {

                                                   const char* attr_name,
                                                   const void* const* values,
                                                   const size_t* lengths,
                                                   int num_values);
TF_CAPI_EXPORT extern void TFE_OpSetAttrIntList(TFE_Op* op,
                                                const char* attr_name,