Baunsgaard commented on a change in pull request #919:
URL: https://github.com/apache/systemml/pull/919#discussion_r430215341
##########
File path:
src/main/java/org/apache/sysds/runtime/instructions/cp/VariableCPInstruction.java
##########
@@ -598,192 +545,116 @@ else if ( getInput1().getDataType() == DataType.SCALAR
){
break;
case RemoveVariableAndFile:
- // Remove the variable from HashMap _variables, and
possibly delete the data on disk.
- boolean del = ( (BooleanObject)
ec.getScalarInput(getInput2().getName(), getInput2().getValueType(), true)
).getBooleanValue();
- MatrixObject m = (MatrixObject)
ec.removeVariable(getInput1().getName());
-
- if ( !del ) {
- // HDFS file should be retailed after
clearData(),
- // therefore data must be exported if dirty
flag is set
- if ( m.isDirty() )
- m.exportData();
- }
- else {
- //throw new DMLRuntimeException("rmfilevar w/
true is not expected! " + instString);
- //cleanDataOnHDFS(pb, input1.getName());
- cleanDataOnHDFS( m );
- }
-
- // check if in-memory object can be cleaned up
- if ( !ec.getVariables().hasReferences(m) ) {
- // no other variable in the symbol table points
to the same Data object as that of input1.getName()
-
- //remove matrix object from cache
- m.clearData();
- }
-
+ processRemoveVariableAndFileInstruction(ec);
break;
case CastAsScalarVariable: //castAsScalarVariable
- if( getInput1().getDataType().isFrame() ) {
- FrameBlock fBlock =
ec.getFrameInput(getInput1().getName());
- if( fBlock.getNumRows()!=1 ||
fBlock.getNumColumns()!=1 )
- throw new
DMLRuntimeException("Dimension mismatch - unable to cast frame
'"+getInput1().getName()+"' of dimension ("+fBlock.getNumRows()+" x
"+fBlock.getNumColumns()+") to scalar.");
- Object value = fBlock.get(0,0);
- ec.releaseFrameInput(getInput1().getName());
- ec.setScalarOutput(output.getName(),
-
ScalarObjectFactory.createScalarObject(fBlock.getSchema()[0], value));
- }
- else if( getInput1().getDataType().isMatrix() ) {
- MatrixBlock mBlock =
ec.getMatrixInput(getInput1().getName());
- if( mBlock.getNumRows()!=1 ||
mBlock.getNumColumns()!=1 )
- throw new
DMLRuntimeException("Dimension mismatch - unable to cast matrix
'"+getInput1().getName()+"' of dimension ("+mBlock.getNumRows()+" x
"+mBlock.getNumColumns()+") to scalar.");
- double value = mBlock.getValue(0,0);
- ec.releaseMatrixInput(getInput1().getName());
- ec.setScalarOutput(output.getName(), new
DoubleObject(value));
- }
- else if( getInput1().getDataType().isTensor() ) {
- TensorBlock tBlock =
ec.getTensorInput(getInput1().getName());
- if (tBlock.getNumDims() != 2 ||
tBlock.getNumRows() != 1 || tBlock.getNumColumns() != 1)
- throw new
DMLRuntimeException("Dimension mismatch - unable to cast tensor '" +
getInput1().getName() + "' to scalar.");
- ValueType vt = !tBlock.isBasic() ?
tBlock.getSchema()[0] : tBlock.getValueType();
- ec.setScalarOutput(output.getName(),
ScalarObjectFactory
- .createScalarObject(vt, tBlock.get(new
int[] {0, 0})));
- ec.releaseTensorInput(getInput1().getName());
- }
- else if( getInput1().getDataType().isList() ) {
- //TODO handling of cleanup status, potentially
new object
- ListObject list =
(ListObject)ec.getVariable(getInput1().getName());
- ec.setVariable(output.getName(), list.slice(0));
- }
- else {
- throw new DMLRuntimeException("Unsupported data
type "
- + "in as.scalar():
"+getInput1().getDataType().name());
- }
+ processCastAsScalarVariableInstruction(ec);
break;
- case CastAsMatrixVariable:{
- if( getInput1().getDataType().isFrame() ) {
- FrameBlock fin =
ec.getFrameInput(getInput1().getName());
- MatrixBlock out =
DataConverter.convertToMatrixBlock(fin);
- ec.releaseFrameInput(getInput1().getName());
- ec.setMatrixOutput(output.getName(), out);
- }
- else if( getInput1().getDataType().isScalar() ) {
- ScalarObject scalarInput = ec.getScalarInput(
- getInput1().getName(),
getInput1().getValueType(), getInput1().isLiteral());
- MatrixBlock out = new
MatrixBlock(scalarInput.getDoubleValue());
- ec.setMatrixOutput(output.getName(), out);
- }
- else if( getInput1().getDataType().isList() ) {
- //TODO handling of cleanup status, potentially
new object
- ListObject list =
(ListObject)ec.getVariable(getInput1().getName());
- if( list.getLength() > 1 ) {
- if(
!list.checkAllDataTypes(DataType.SCALAR) )
- throw new
DMLRuntimeException("as.matrix over multi-entry list only allows scalars.");
- MatrixBlock out = new
MatrixBlock(list.getLength(), 1, false);
- for( int i=0; i<list.getLength(); i++ )
- out.quickSetValue(i, 0,
((ScalarObject)list.slice(i)).getDoubleValue());
- ec.setMatrixOutput(output.getName(),
out);
- }
- else {
- //pass through matrix input or create
1x1 matrix for scalar
- Data tmp = list.slice(0);
- if( tmp instanceof ScalarObject &&
tmp.getValueType()!=ValueType.STRING ) {
- MatrixBlock out = new
MatrixBlock(((ScalarObject)tmp).getDoubleValue());
-
ec.setMatrixOutput(output.getName(), out);
- }
- else {
-
ec.setVariable(output.getName(), tmp);
- }
- }
- }
- else {
- throw new DMLRuntimeException("Unsupported data
type "
- + "in as.matrix():
"+getInput1().getDataType().name());
- }
+
+ case CastAsMatrixVariable:
+ processCastAsMatrixVariableInstruction(ec);
break;
- }
- case CastAsFrameVariable:{
- FrameBlock out = null;
- if( getInput1().getDataType()==DataType.SCALAR ) {
- ScalarObject scalarInput =
ec.getScalarInput(getInput1());
- out = new FrameBlock(1,
getInput1().getValueType());
- out.ensureAllocatedColumns(1);
- out.set(0, 0, scalarInput.getStringValue());
- }
- else { //DataType.FRAME
- MatrixBlock min =
ec.getMatrixInput(getInput1().getName());
- out = DataConverter.convertToFrameBlock(min);
- ec.releaseMatrixInput(getInput1().getName());
- }
- ec.setFrameOutput(output.getName(), out);
+
+ case CastAsFrameVariable:
+ processCastAsFrameVariableInstruction(ec);
break;
- }
- case CastAsDoubleVariable:{
- ScalarObject in = ec.getScalarInput(getInput1());
- ec.setScalarOutput(output.getName(),
ScalarObjectFactory.castToDouble(in));
+
+ case CastAsDoubleVariable:
+ ScalarObject scalarDoubleInput =
ec.getScalarInput(getInput1());
+ ec.setScalarOutput(output.getName(),
ScalarObjectFactory.castToDouble(scalarDoubleInput));
break;
- }
- case CastAsIntegerVariable:{
- ScalarObject in = ec.getScalarInput(getInput1());
- ec.setScalarOutput(output.getName(),
ScalarObjectFactory.castToLong(in));
+
+ case CastAsIntegerVariable:
+ ScalarObject scalarLongInput =
ec.getScalarInput(getInput1());
+ ec.setScalarOutput(output.getName(),
ScalarObjectFactory.castToLong(scalarLongInput));
break;
- }
- case CastAsBooleanVariable:{
- ScalarObject scalarInput =
ec.getScalarInput(getInput1());
- ec.setScalarOutput(output.getName(), new
BooleanObject(scalarInput.getBooleanValue()));
+
+ case CastAsBooleanVariable:
+ ScalarObject scalarBooleanInput =
ec.getScalarInput(getInput1());
+ ec.setScalarOutput(output.getName(), new
BooleanObject(scalarBooleanInput.getBooleanValue()));
break;
- }
case Read:
- ScalarObject res = null;
- try {
- switch(getInput1().getValueType()) {
- case FP64:
- res = new
DoubleObject(HDFSTool.readDoubleFromHDFSFile(getInput2().getName()));
- break;
- case INT64:
- res = new
IntObject(HDFSTool.readIntegerFromHDFSFile(getInput2().getName()));
- break;
- case BOOLEAN:
- res = new
BooleanObject(HDFSTool.readBooleanFromHDFSFile(getInput2().getName()));
- break;
- case STRING:
- res = new
StringObject(HDFSTool.readStringFromHDFSFile(getInput2().getName()));
- break;
- default:
- throw new
DMLRuntimeException("Invalid value type ("
- +
getInput1().getValueType() + ") while processing readScalar instruction.");
- }
- } catch ( IOException e ) {
- throw new DMLRuntimeException(e);
- }
- ec.setScalarOutput(getInput1().getName(), res);
-
+ processReadInstruction(ec);
break;
case Write:
processWriteInstruction(ec);
break;
case SetFileName:
- Data data = ec.getVariable(getInput1().getName());
- if ( data.getDataType() == DataType.MATRIX ) {
- if (
getInput3().getName().equalsIgnoreCase("remote") ) {
-
((MatrixObject)data).setFileName(getInput2().getName());
- }
- else {
- throw new DMLRuntimeException("Invalid
location (" + getInput3().getName() + ") in SetFileName instruction: " +
instString);
- }
- } else{
- throw new DMLRuntimeException("Invalid data
type (" + getInput1().getDataType() + ") in SetFileName instruction: " +
instString);
- }
+ processSetFileNameInstruction(ec);
break;
default:
throw new DMLRuntimeException("Unknown opcode: " +
opcode );
}
}
+
+ /**
+ * Handler for processInstruction "CreateVariable" case
+ * @param ec execution context of the instruction
+ */
+ private void processCreateVariableInstruction(ExecutionContext ec){
+ //PRE: for robustness we cleanup existing variables, because a
setVariable
+ //would cause a buffer pool memory leak as these objects would
never be removed
+ if(ec.containsVariable(getInput1()))
+ processRemoveVariableInstruction(ec,
getInput1().getName());
+
+ if ( getInput1().getDataType() == DataType.MATRIX ) {
+ String fname = createUniqueFilename();
+ MatrixObject obj = new
MatrixObject(getInput1().getValueType(), fname);
+ setCacheableDataFields(obj);
+ obj.setUpdateType(_updateType);
+ obj.setMarkForLinCache(true);
+ ec.setVariable(getInput1().getName(), obj);
+ if(DMLScript.STATISTICS && _updateType.isInPlace())
+ Statistics.incrementTotalUIPVar();
+ }
+ else if( getInput1().getDataType() == DataType.TENSOR ) {
+ String fname = createUniqueFilename();
+ CacheableData<?> obj = new
TensorObject(getInput1().getValueType(), fname);
+ setCacheableDataFields(obj);
+ ec.setVariable(getInput1().getName(), obj);
+ }
+ else if( getInput1().getDataType() == DataType.FRAME ) {
+ String fname = createUniqueFilename();
+ FrameObject fobj = new FrameObject(fname);
+ setCacheableDataFields(fobj);
+ if( _schema != null )
+ fobj.setSchema(_schema); //after metadata
+ ec.setVariable(getInput1().getName(), fobj);
+ }
+ else if ( getInput1().getDataType() == DataType.SCALAR ){
+ //created variable not called for scalars
+ ec.setScalarOutput(getInput1().getName(), null);
+ }
+ else {
Review comment:
This could be a switch statement
##########
File path:
src/main/java/org/apache/sysds/runtime/instructions/cp/VariableCPInstruction.java
##########
@@ -898,20 +955,38 @@ else if( fmt == FileFormat.CSV )
else {
// Default behavior
MatrixObject mo =
ec.getMatrixObject(getInput1().getName());
-
mo.setPrivacyConstraints(getPrivacyConstraint());
mo.exportData(fname, fmtStr, _formatProperties);
}
+ // Set privacy constraint of write instruction to the
same as that of the input
+
setPrivacyConstraint(ec.getMatrixObject(getInput1().getName()).getPrivacyConstraint());
}
else if( getInput1().getDataType() == DataType.FRAME ) {
FrameObject mo =
ec.getFrameObject(getInput1().getName());
mo.exportData(fname, fmtStr, _formatProperties);
+ setPrivacyConstraint(mo.getPrivacyConstraint());
}
else if( getInput1().getDataType() == DataType.TENSOR ) {
Review comment:
Also is there a significance in either calling set PrivacyConstraint
before calling ExportData or not?
##########
File path:
src/main/java/org/apache/sysds/runtime/instructions/cp/VariableCPInstruction.java
##########
@@ -843,6 +714,192 @@ else if (object instanceof FrameObject)
+
((FrameObject)object).getNumColumns() + "," +
((FrameObject)object).getNumColumns() + "] to " + getInput3().getName());
}
}
+
+ /**
+ * Handler for RemoveVariableAndFile instruction
+ *
+ * @param ec execution context
+ */
+ private void processRemoveVariableAndFileInstruction(ExecutionContext
ec){
+ // Remove the variable from HashMap _variables, and possibly
delete the data on disk.
+ boolean del = ( (BooleanObject)
ec.getScalarInput(getInput2().getName(), getInput2().getValueType(), true)
).getBooleanValue();
+ MatrixObject m = (MatrixObject)
ec.removeVariable(getInput1().getName());
+
+ if ( !del ) {
+ // HDFS file should be retailed after clearData(),
+ // therefore data must be exported if dirty flag is set
+ if ( m.isDirty() )
+ m.exportData();
+ }
+ else {
+ //throw new DMLRuntimeException("rmfilevar w/ true is
not expected! " + instString);
+ //cleanDataOnHDFS(pb, input1.getName());
+ cleanDataOnHDFS( m );
+ }
+
+ // check if in-memory object can be cleaned up
+ if ( !ec.getVariables().hasReferences(m) ) {
+ // no other variable in the symbol table points to the
same Data object as that of input1.getName()
+
+ //remove matrix object from cache
+ m.clearData();
+ }
+ }
+
+ /**
+ * Process CastAsScalarVariable instruction.
+ * @param ec execution context
+ */
+ private void processCastAsScalarVariableInstruction(ExecutionContext
ec){
+ //TODO: Create privacy constraints for ScalarObject so that the
privacy constraints can be propagated to scalars as well.
+ blockIfInputPrivacyActivated(ec.getVariable(getInput1()));
+
+ if( getInput1().getDataType().isFrame() ) {
+ FrameBlock fBlock =
ec.getFrameInput(getInput1().getName());
+ if( fBlock.getNumRows()!=1 || fBlock.getNumColumns()!=1
)
+ throw new DMLRuntimeException("Dimension
mismatch - unable to cast frame '"+getInput1().getName()+"' of dimension
("+fBlock.getNumRows()+" x "+fBlock.getNumColumns()+") to scalar.");
+ Object value = fBlock.get(0,0);
+ ec.releaseFrameInput(getInput1().getName());
+ ec.setScalarOutput(output.getName(),
+
ScalarObjectFactory.createScalarObject(fBlock.getSchema()[0], value));
+ }
+ else if( getInput1().getDataType().isMatrix() ) {
+ MatrixBlock mBlock =
ec.getMatrixInput(getInput1().getName());
+ if( mBlock.getNumRows()!=1 || mBlock.getNumColumns()!=1
)
+ throw new DMLRuntimeException("Dimension
mismatch - unable to cast matrix '"+getInput1().getName()+"' of dimension
("+mBlock.getNumRows()+" x "+mBlock.getNumColumns()+") to scalar.");
+ double value = mBlock.getValue(0,0);
+ ec.releaseMatrixInput(getInput1().getName());
+ ec.setScalarOutput(output.getName(), new
DoubleObject(value));
+ }
+ else if( getInput1().getDataType().isTensor() ) {
+ TensorBlock tBlock =
ec.getTensorInput(getInput1().getName());
+ if (tBlock.getNumDims() != 2 || tBlock.getNumRows() !=
1 || tBlock.getNumColumns() != 1)
+ throw new DMLRuntimeException("Dimension
mismatch - unable to cast tensor '" + getInput1().getName() + "' to scalar.");
+ ValueType vt = !tBlock.isBasic() ?
tBlock.getSchema()[0] : tBlock.getValueType();
+ ec.setScalarOutput(output.getName(), ScalarObjectFactory
+ .createScalarObject(vt, tBlock.get(new int[]
{0, 0})));
+ ec.releaseTensorInput(getInput1().getName());
+ }
+ else if( getInput1().getDataType().isList() ) {
+ //TODO handling of cleanup status, potentially new
object
+ ListObject list =
(ListObject)ec.getVariable(getInput1().getName());
+ ec.setVariable(output.getName(), list.slice(0));
+ }
+ else {
Review comment:
Again could be switch statement, and if this is doing the same as the
last comment on if else.
why is there a separate method build in to check it?
##########
File path:
src/main/java/org/apache/sysds/runtime/instructions/cp/VariableCPInstruction.java
##########
@@ -843,6 +714,192 @@ else if (object instanceof FrameObject)
+
((FrameObject)object).getNumColumns() + "," +
((FrameObject)object).getNumColumns() + "] to " + getInput3().getName());
}
}
+
+ /**
+ * Handler for RemoveVariableAndFile instruction
+ *
+ * @param ec execution context
+ */
+ private void processRemoveVariableAndFileInstruction(ExecutionContext
ec){
+ // Remove the variable from HashMap _variables, and possibly
delete the data on disk.
+ boolean del = ( (BooleanObject)
ec.getScalarInput(getInput2().getName(), getInput2().getValueType(), true)
).getBooleanValue();
+ MatrixObject m = (MatrixObject)
ec.removeVariable(getInput1().getName());
+
+ if ( !del ) {
+ // HDFS file should be retailed after clearData(),
+ // therefore data must be exported if dirty flag is set
+ if ( m.isDirty() )
+ m.exportData();
+ }
+ else {
+ //throw new DMLRuntimeException("rmfilevar w/ true is
not expected! " + instString);
+ //cleanDataOnHDFS(pb, input1.getName());
+ cleanDataOnHDFS( m );
+ }
+
+ // check if in-memory object can be cleaned up
+ if ( !ec.getVariables().hasReferences(m) ) {
+ // no other variable in the symbol table points to the
same Data object as that of input1.getName()
+
+ //remove matrix object from cache
+ m.clearData();
+ }
+ }
+
+ /**
+ * Process CastAsScalarVariable instruction.
+ * @param ec execution context
+ */
+ private void processCastAsScalarVariableInstruction(ExecutionContext
ec){
+ //TODO: Create privacy constraints for ScalarObject so that the
privacy constraints can be propagated to scalars as well.
+ blockIfInputPrivacyActivated(ec.getVariable(getInput1()));
+
+ if( getInput1().getDataType().isFrame() ) {
+ FrameBlock fBlock =
ec.getFrameInput(getInput1().getName());
+ if( fBlock.getNumRows()!=1 || fBlock.getNumColumns()!=1
)
+ throw new DMLRuntimeException("Dimension
mismatch - unable to cast frame '"+getInput1().getName()+"' of dimension
("+fBlock.getNumRows()+" x "+fBlock.getNumColumns()+") to scalar.");
+ Object value = fBlock.get(0,0);
+ ec.releaseFrameInput(getInput1().getName());
+ ec.setScalarOutput(output.getName(),
+
ScalarObjectFactory.createScalarObject(fBlock.getSchema()[0], value));
+ }
+ else if( getInput1().getDataType().isMatrix() ) {
+ MatrixBlock mBlock =
ec.getMatrixInput(getInput1().getName());
+ if( mBlock.getNumRows()!=1 || mBlock.getNumColumns()!=1
)
+ throw new DMLRuntimeException("Dimension
mismatch - unable to cast matrix '"+getInput1().getName()+"' of dimension
("+mBlock.getNumRows()+" x "+mBlock.getNumColumns()+") to scalar.");
+ double value = mBlock.getValue(0,0);
+ ec.releaseMatrixInput(getInput1().getName());
+ ec.setScalarOutput(output.getName(), new
DoubleObject(value));
+ }
+ else if( getInput1().getDataType().isTensor() ) {
+ TensorBlock tBlock =
ec.getTensorInput(getInput1().getName());
+ if (tBlock.getNumDims() != 2 || tBlock.getNumRows() !=
1 || tBlock.getNumColumns() != 1)
+ throw new DMLRuntimeException("Dimension
mismatch - unable to cast tensor '" + getInput1().getName() + "' to scalar.");
+ ValueType vt = !tBlock.isBasic() ?
tBlock.getSchema()[0] : tBlock.getValueType();
+ ec.setScalarOutput(output.getName(), ScalarObjectFactory
+ .createScalarObject(vt, tBlock.get(new int[]
{0, 0})));
+ ec.releaseTensorInput(getInput1().getName());
+ }
+ else if( getInput1().getDataType().isList() ) {
+ //TODO handling of cleanup status, potentially new
object
+ ListObject list =
(ListObject)ec.getVariable(getInput1().getName());
+ ec.setVariable(output.getName(), list.slice(0));
+ }
+ else {
+ throw new DMLRuntimeException("Unsupported data type "
+ + "in as.scalar():
"+getInput1().getDataType().name());
+ }
+ }
+
+
+ /**
+ * Throw DMLPrivacyException if privacy is activated for the input
variable
+ * @param input variable for which the privacy constraint is checked
+ */
+ private void blockIfInputPrivacyActivated(Data input){
+ if ( input != null && (input instanceof CacheableData<?>)){
+ PrivacyConstraint privacyConstraintIn =
((CacheableData<?>) input).getPrivacyConstraint();
+ if ( privacyConstraintIn != null &&
(privacyConstraintIn.getPrivacyLevel() == PrivacyLevel.Private) ){
+ throw new DMLPrivacyException("Privacy
constraint cannot be propagated to scalar for input " + getInput1().getName());
+ }
+ }
Review comment:
so PrivacyConstaints is associated with CacheableData in general?
##########
File path: src/main/java/org/apache/sysds/runtime/privacy/PrivacyConstraint.java
##########
@@ -24,19 +24,26 @@
*/
public class PrivacyConstraint
{
- protected boolean _privacy = false;
+
+ public enum PrivacyLevel {
Review comment:
static
##########
File path:
src/main/java/org/apache/sysds/runtime/instructions/cp/VariableCPInstruction.java
##########
@@ -956,7 +1031,7 @@ private void writeCSVFile(ExecutionContext ec, String
fname) {
else {
mo.exportData(fname, outFmt,
_formatProperties);
}
- HDFSTool.writeMetaDataFile (fname + ".mtd",
mo.getValueType(), dc, FileFormat.CSV, _formatProperties);
+ HDFSTool.writeMetaDataFile (fname + ".mtd",
mo.getValueType(), dc, FileFormat.CSV, _formatProperties,
mo.getPrivacyConstraint());
Review comment:
you might want to remove your extra space
##########
File path:
src/test/java/org/apache/sysds/test/functions/privacy/FederatedWorkerHandlerTest.java
##########
@@ -0,0 +1,341 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.sysds.test.functions.privacy;
+
+import java.util.Arrays;
+
+import org.apache.sysds.api.DMLException;
+import org.apache.sysds.api.DMLScript;
+import org.apache.sysds.runtime.meta.MatrixCharacteristics;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint.PrivacyLevel;
+import org.apache.sysds.test.AutomatedTestBase;
+import org.apache.sysds.test.TestConfiguration;
+import org.apache.sysds.test.TestUtils;
+import org.junit.Test;
+import org.apache.sysds.common.Types;
+import static java.lang.Thread.sleep;
+
+public class FederatedWorkerHandlerTest extends AutomatedTestBase {
Review comment:
Indentation needs fixing! TABS !
##########
File path:
src/test/java/org/apache/sysds/test/functions/privacy/MatrixMultiplicationPropagationTest.java
##########
@@ -46,26 +47,36 @@ public void setUp() {
}
@Test
- public void testMatrixMultiplicationPropagation() throws JSONException {
- matrixMultiplicationPropagation(true, true);
+ public void testMatrixMultiplicationPropagationPrivate() throws
JSONException {
Review comment:
I see the JSON throwing is here as well.
##########
File path:
src/test/java/org/apache/sysds/test/functions/privacy/FederatedL2SVMTest.java
##########
@@ -0,0 +1,386 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.sysds.test.functions.privacy;
+
+import org.junit.Test;
+import org.apache.sysds.api.DMLException;
+import org.apache.sysds.api.DMLScript;
+import org.apache.sysds.common.Types;
+import org.apache.sysds.runtime.meta.MatrixCharacteristics;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint.PrivacyLevel;
+import org.apache.sysds.test.AutomatedTestBase;
+import org.apache.sysds.test.TestConfiguration;
+import org.apache.sysds.test.TestUtils;
+import org.apache.wink.json4j.JSONException;
+
+import java.util.HashMap;
+import java.util.Map;
+
[email protected]
+public class FederatedL2SVMTest extends AutomatedTestBase {
+
+ private final static String TEST_DIR = "functions/federated/";
+ private final static String TEST_NAME = "FederatedL2SVMTest";
+ private final static String TEST_CLASS_DIR = TEST_DIR +
FederatedL2SVMTest.class.getSimpleName() + "/";
+
+ private final static int blocksize = 1024;
+ private int rows = 100;
+ private int cols = 10;
+
+ @Override
+ public void setUp() {
+ TestUtils.clearAssertionInformation();
+ addTestConfiguration(TEST_NAME, new
TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[] {"Z"}));
+ }
+
+ // PrivateAggregation Single Input
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationX1() throws JSONException
{
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.PrivateAggregation);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationX2() throws JSONException
{
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.PrivateAggregation);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationY() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.PrivateAggregation);
+ }
+
+ // Private Single Input
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedX1() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedX2() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedY() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.Private);
+ }
+
+ // Setting Privacy of Matrix (Throws Exception)
+
+ @Test
+ public void federatedL2SVMCPPrivateMatrixX1() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, null,
privacyConstraints, PrivacyLevel.Private, true, DMLException.class, false,
null);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateMatrixX2() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, null,
privacyConstraints, PrivacyLevel.Private, true, DMLException.class, false,
null);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateMatrixY() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, null,
privacyConstraints, PrivacyLevel.Private, true, DMLException.class, false,
null);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedAndMatrixX1() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
privacyConstraints, PrivacyLevel.Private, true, DMLException.class, true,
DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedAndMatrixX2() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
privacyConstraints, PrivacyLevel.Private, true, DMLException.class, true,
DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedAndMatrixY() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
privacyConstraints, PrivacyLevel.Private, true, DMLException.class, false,
null);
+ }
+
+ // Privacy Level Private Combinations
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedX1X2() throws JSONException
{
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedX1Y() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedX2Y() throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateFederatedX1X2Y() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ // Privacy Level PrivateAggregation Combinations
+ @Test
+ public void federatedL2SVMCPPrivateAggregationFederatedX1X2() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.PrivateAggregation);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationFederatedX1Y() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.PrivateAggregation);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationFederatedX2Y() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.PrivateAggregation);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationFederatedX1X2Y() throws
JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.PrivateAggregation);
+ }
+
+ // Privacy Level Combinations
+ @Test
+ public void federatedL2SVMCPPrivatePrivateAggregationFederatedX1X2()
throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivatePrivateAggregationFederatedX1Y()
throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivatePrivateAggregationFederatedX2Y()
throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivatePrivateAggregationFederatedYX1()
throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.Private);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivatePrivateAggregationFederatedYX2()
throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("Y", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVMNoException(Types.ExecMode.SINGLE_NODE,
privacyConstraints, null, PrivacyLevel.Private);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivatePrivateAggregationFederatedX2X1()
throws JSONException {
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.Private));
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ // Require Federated Workers to return matrix
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationX1Exception() throws
JSONException {
+ this.rows = 1000;
+ this.cols = 1;
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.PrivateAggregation, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateAggregationX2Exception() throws
JSONException {
+ this.rows = 1000;
+ this.cols = 1;
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X2", new
PrivacyConstraint(PrivacyLevel.PrivateAggregation));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.PrivateAggregation, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateX1Exception() throws JSONException {
+ this.rows = 1000;
+ this.cols = 1;
+ Map<String, PrivacyConstraint> privacyConstraints = new
HashMap<>();
+ privacyConstraints.put("X1", new
PrivacyConstraint(PrivacyLevel.Private));
+ federatedL2SVM(Types.ExecMode.SINGLE_NODE, privacyConstraints,
null, PrivacyLevel.Private, false, null, true, DMLException.class);
+ }
+
+ @Test
+ public void federatedL2SVMCPPrivateX2Exception() throws JSONException {
Review comment:
Every method in this class throws JSONException. Can this be caught,
since i worry that if for some reason it is thrown we get the odd error of fork
crashed in our tests.?
##########
File path:
src/test/java/org/apache/sysds/test/functions/privacy/MatrixRuntimePropagationTest.java
##########
@@ -0,0 +1,127 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.sysds.test.functions.privacy;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.fail;
+
+import org.apache.sysds.parser.DataExpression;
+import org.apache.sysds.runtime.meta.MatrixCharacteristics;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint.PrivacyLevel;
+import org.apache.sysds.test.AutomatedTestBase;
+import org.apache.sysds.test.TestConfiguration;
+import org.apache.sysds.test.TestUtils;
+import org.apache.wink.json4j.JSONException;
+import org.junit.Test;
+
+public class MatrixRuntimePropagationTest extends AutomatedTestBase {
Review comment:
Indentation!
##########
File path:
src/main/java/org/apache/sysds/runtime/instructions/cp/VariableCPInstruction.java
##########
@@ -898,20 +955,38 @@ else if( fmt == FileFormat.CSV )
else {
// Default behavior
MatrixObject mo =
ec.getMatrixObject(getInput1().getName());
-
mo.setPrivacyConstraints(getPrivacyConstraint());
mo.exportData(fname, fmtStr, _formatProperties);
}
+ // Set privacy constraint of write instruction to the
same as that of the input
+
setPrivacyConstraint(ec.getMatrixObject(getInput1().getName()).getPrivacyConstraint());
}
else if( getInput1().getDataType() == DataType.FRAME ) {
FrameObject mo =
ec.getFrameObject(getInput1().getName());
mo.exportData(fname, fmtStr, _formatProperties);
+ setPrivacyConstraint(mo.getPrivacyConstraint());
}
else if( getInput1().getDataType() == DataType.TENSOR ) {
Review comment:
you could make a switch here again
##########
File path:
src/test/java/org/apache/sysds/test/functions/privacy/MatrixRuntimePropagationTest.java
##########
@@ -0,0 +1,127 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.sysds.test.functions.privacy;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.fail;
+
+import org.apache.sysds.parser.DataExpression;
+import org.apache.sysds.runtime.meta.MatrixCharacteristics;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint.PrivacyLevel;
+import org.apache.sysds.test.AutomatedTestBase;
+import org.apache.sysds.test.TestConfiguration;
+import org.apache.sysds.test.TestUtils;
+import org.apache.wink.json4j.JSONException;
+import org.junit.Test;
+
+public class MatrixRuntimePropagationTest extends AutomatedTestBase {
+
+ private static final String TEST_DIR = "functions/privacy/";
+ private final static String TEST_CLASS_DIR = TEST_DIR +
MatrixMultiplicationPropagationTest.class.getSimpleName() + "/";
+ private final int m = 20;
+ private final int n = 20;
+ private final int k = 20;
Review comment:
most of the time k refers to thread count inside SystemDS, when i
started reading this test, i assumed it was the same here, but it is a matrix
size variable.
##########
File path:
src/main/java/org/apache/sysds/runtime/instructions/cp/VariableCPInstruction.java
##########
@@ -956,7 +1031,7 @@ private void writeCSVFile(ExecutionContext ec, String
fname) {
else {
mo.exportData(fname, outFmt,
_formatProperties);
}
- HDFSTool.writeMetaDataFile (fname + ".mtd",
mo.getValueType(), dc, FileFormat.CSV, _formatProperties);
+ HDFSTool.writeMetaDataFile (fname + ".mtd",
mo.getValueType(), dc, FileFormat.CSV, _formatProperties,
mo.getPrivacyConstraint());
Review comment:
before File format
##########
File path: src/main/java/org/apache/sysds/runtime/privacy/PrivacyConstraint.java
##########
@@ -24,19 +24,26 @@
*/
public class PrivacyConstraint
{
- protected boolean _privacy = false;
+
+ public enum PrivacyLevel {
Review comment:
searching around our code base leads to ... everyone doing it this way
... hmm, and here i thought i could find many examples of static enums around
in the code. but clearly everyone does it this way. I guess just ignore the
comment :P
##########
File path:
src/test/java/org/apache/sysds/test/functions/privacy/FederatedWorkerHandlerTest.java
##########
@@ -0,0 +1,341 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.sysds.test.functions.privacy;
+
+import java.util.Arrays;
+
+import org.apache.sysds.api.DMLException;
+import org.apache.sysds.api.DMLScript;
+import org.apache.sysds.runtime.meta.MatrixCharacteristics;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint;
+import org.apache.sysds.runtime.privacy.PrivacyConstraint.PrivacyLevel;
+import org.apache.sysds.test.AutomatedTestBase;
+import org.apache.sysds.test.TestConfiguration;
+import org.apache.sysds.test.TestUtils;
+import org.junit.Test;
+import org.apache.sysds.common.Types;
+import static java.lang.Thread.sleep;
+
+public class FederatedWorkerHandlerTest extends AutomatedTestBase {
Review comment:
Tabs?
you could if you want to be extra nice, try to use the codeformatter.
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