return (emitError(loc, "unsupported FakeQuant number of bits: ") << numBits,
            nullptr);
  }

  SmallVector<double, 4> scales;
  SmallVector<int64_t, 4> zeroPoints;
  scales.reserve(axisSize);
  zeroPoints.reserve(axisSize);
  for (size_t axis = 0; axis != axisSize; ++axis) {
    double rmin = rmins[axis];
    double rmax = rmaxs[axis];
    if (std::fabs(rmax - rmin) < std::numeric_limits<double>::epsilon()) {

    }
    if (argument.HasDefaultValue()) {
      args_with_default_val.push_back(text);
    } else {
      args_without_default_val.push_back(text);
    }
  }
  std::vector<string> arguments;
  arguments.reserve(args_without_default_val.size() +
                    args_with_default_val.size());
  arguments.insert(arguments.end(),
                   std::make_move_iterator(args_without_default_val.begin()),

}

// varintAt writes varint v at byte position pos in buf. This always
// consumes traceBytesPerNumber bytes. This is intended for when the caller
// needs to reserve space for a varint but can't populate it until later.
// Use varintReserve to reserve this space.
func (buf *traceBuf) varintAt(pos int, v uint64) {
	for i := 0; i < traceBytesPerNumber; i++ {
		if i < traceBytesPerNumber-1 {
			buf.arr[pos] = 0x80 | byte(v)

  for (int core = 0; core < num_cores_per_replica; ++core) {
    llvm::SmallVector<StringRef, 8> devices_by_core;
    devices_by_core.reserve(num_replicas);
    llvm::SmallVector<StringRef, 8> hosts_by_core;
    hosts_by_core.reserve(num_replicas);
    for (int replica = 0; replica < num_replicas; ++replica) {
      devices_by_core.push_back(tpu_devices[replica][core].device);

        op_->colocation_constraints.emplace(static_cast<const char*>(values[i]),
                                            lengths[i]);
      }
    } else {
      std::vector<tensorflow::StringPiece> v;
      v.reserve(num_values);
      for (int i = 0; i < num_values; ++i) {
        v.emplace_back(static_cast<const char*>(values[i]), lengths[i]);
      }
      op_->node_builder.Attr(attr_name, v);
    }

  } while (succeeded(parser->parseOptionalComma()));

  region_args->reserve(replicated_region_args.size() +
                       packed_region_args.size());
  region_args->append(replicated_region_args.begin(),
                      replicated_region_args.end());
  region_args->append(packed_region_args.begin(), packed_region_args.end());

  region_arg_types->reserve(replicated_region_arg_types.size() +

        "Length of input node array and data shape doesn't match (#arrays ",
        node_names.size(), ", #input_shapes ", node_shapes.size(), ")"));
  }

  // StringMap doesn't support reserve else reserve input map size here.
  for (int i = 0, end = node_names.size(); i < end; i++) {
    auto& name = node_names[i];
    const string& type = used_node_dtypes[i];
    if (name.empty()) continue;

  return var_handle_op.getSharedName().str();
}

std::vector<std::string> GetVariableNames(
    llvm::ArrayRef<TF::VarHandleOp> var_handle_ops) {
  std::vector<std::string> names;
  names.reserve(var_handle_ops.size());
  for (auto var_handle_op : var_handle_ops)
    names.push_back(GetVariableName(var_handle_op));
  return names;
}

tensorflow::Var* GetVariableFromSession(mlir::TF::VarHandleOp var_handle_op,

    def "does not reserve idle client when no clients"() {
        expect:
        manager.reserveIdleClient(options) == null
    }

    def "does not reserve idle client when no matching client found"() {
        def noMatch = Stub(WorkerDaemonClient) {
            isCompatibleWith(_) >> false
        }

  mlir::DictionaryAttr tf_attrs =
      entry_function->getAttrOfType<mlir::DictionaryAttr>("tf.entry_function");
  llvm::SmallVector<llvm::StringRef, 4> function_input_names;
  function_input_names.reserve(model_flags.input_arrays().size());
  auto input_attr = tf_attrs.get("inputs");
  if (!input_attr) {
    return errors::InvalidArgument("no inputs attribute found");
  }