int* num_retvals, ForwardOperation* forward_op_,
                     Tape* tape, const GradientRegistry& registry) {
  TF_RETURN_IF_ERROR(op_->Execute(retvals, num_retvals));
  for (int i = 0; i < *num_retvals; i++) {
    // TODO(srbs): Manage refcount of ForwardOperation's inputs/outputs.
    forward_op_->outputs.push_back(retvals[i]);
  }

            if (retValue.length() >= 2 && retValue.charAt(1) == '|') {
                retValue = retValue.charAt(0) + ":" + retValue.substring(2);
            }

            // normalize separators
            retValue = new File(retValue).getPath();
        }

        if (retValue == null) {
            retValue = "/";
        }
        return retValue.trim();
    }

    /**

		}
	}
	if !updated {
		// Append to the end of tags list
		r.tags = append(r.tags, KeyVal{key, val})
	}
	return r
}

// GetTags - returns the user defined tags
func (r *ReqInfo) GetTags() []KeyVal {
	if r == nil {
		return nil
	}
	r.RLock()
	defer r.RUnlock()
	return append(make([]KeyVal, 0, len(r.tags)), r.tags...)
}

// GetTagsMap - returns the user defined tags in a map structure

### 3.1 Automatic removal of non current objects versions

A non-current object version is a version which is not the latest for a given object. It is possible to set up an automatic removal of non-current versions when a version becomes older than a given number of days.

  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TFE_TensorHandle* retvals[1];
  int num_retvals = 1;
  TFE_Execute(matmul, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  auto* retval_task0 =
      TFE_TensorHandleCopyToDevice(retvals[0], ctx, local_device_name, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

	h.mutex.RLock()
	defer h.mutex.RUnlock()

	// Make a copy before returning the value
	retMap := make(map[madmin.HealItemType]int64, len(h.scannedItemsMap))
	for k, v := range h.scannedItemsMap {
		retMap[k] = v
	}

	return retMap
}

// getHealedItemsMap - returns the map of all healed items against type

${packaging.scripts.header}

#
# This script is executed in the post-removal phase
#
#   On Debian,
#       $1=remove    : indicates a removal
#       $1=purge     : indicates an upgrade
#
#   On RedHat,
#       $1=0         : indicates a removal
#       $1=1         : indicates an upgrade



SOURCE_ENV_FILE=true
REMOVE_DIRS=false
REMOVE_SERVICE=false
REMOVE_USER_AND_GROUP=false

case "$1" in

                       ImmediateExecutionTensorHandle** retvals,
                       int* num_retvals) override {
    std::vector<TFE_TensorHandle*> outputs(*num_retvals);
    TF_Status status;
    device_.execute(tensorflow::wrap(op), num_retvals, outputs.data(), &status,
                    info_);
    if (status.status.ok()) {
      for (int i = 0; i < *num_retvals; ++i) {
        retvals[i] = tensorflow::unwrap(outputs[i]);

    while (true) {
      long current = longs.get(i);
      double currentVal = longBitsToDouble(current);
      double nextVal = updaterFunction.applyAsDouble(currentVal);
      long next = doubleToRawLongBits(nextVal);
      if (longs.compareAndSet(i, current, next)) {
        return nextVal;
      }
    }
  }

  /**
   * Returns the String representation of the current values of array.
   *

// Execute the operation defined by 'op' and return handles to computed
// tensors in `retvals`.
//
// 'retvals' must point to a pre-allocated array of TFE_TensorHandle* and
// '*num_retvals' should be set to the size of this array. It is an error if
// the size of 'retvals' is less than the number of outputs. This call sets
// *num_retvals to the number of outputs.
//