diff options
Diffstat (limited to 'vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java')
-rw-r--r-- | vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java | 85 |
1 files changed, 58 insertions, 27 deletions
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java b/vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java index bebd706f815..87157495485 100644 --- a/vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java +++ b/vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java @@ -16,9 +16,11 @@ import com.yahoo.tensor.MixedTensor; import com.yahoo.tensor.Tensor; import com.yahoo.tensor.TensorAddress; import com.yahoo.tensor.TensorType; +import com.yahoo.tensor.evaluation.Name; import com.yahoo.tensor.functions.ConstantTensor; import com.yahoo.tensor.functions.Slice; +import java.util.ArrayList; import java.util.HashSet; import java.util.Iterator; import java.util.List; @@ -61,23 +63,23 @@ public class JsonFormat { // Encode as nested lists if indexed tensor if (tensor instanceof IndexedTensor) { IndexedTensor denseTensor = (IndexedTensor) tensor; - encodeList(denseTensor, root.setArray("value"), new long[denseTensor.dimensionSizes().dimensions()], 0); + encodeValues(denseTensor, root.setArray("values"), new long[denseTensor.dimensionSizes().dimensions()], 0); } // Short form for a single mapped dimension else if (tensor instanceof MappedTensor && tensor.type().dimensions().size() == 1) { - encodeMap((MappedTensor) tensor, root.setObject("value")); + encodeSingleDimensionCells((MappedTensor) tensor, root); } - // Short form for a mixed tensor with a single mapped dimension + // Short form for a mixed tensor else if (tensor instanceof MixedTensor && - tensor.type().dimensions().stream().filter(TensorType.Dimension::isMapped).count() == 1) { - encodeMapBlocks((MixedTensor) tensor, root.setObject("value")); + tensor.type().dimensions().stream().filter(TensorType.Dimension::isMapped).count() >= 1) { + encodeBlocks((MixedTensor) tensor, root); } // No other short forms exist: default to standard cell address output else { - encodeCells(tensor, root.setObject("value")); + encodeCells(tensor, root); } return com.yahoo.slime.JsonFormat.toJsonBytes(slime); @@ -93,47 +95,76 @@ public class JsonFormat { } } + private static void encodeSingleDimensionCells(MappedTensor tensor, Cursor cursor) { + Cursor cells = cursor.setObject("cells"); + if (tensor.type().dimensions().size() > 1) + throw new IllegalStateException("JSON encode of mapped tensor can only contain a single dimension"); + tensor.cells().forEach((k,v) -> cells.setDouble(k.label(0), v)); + } + private static void encodeAddress(TensorType type, TensorAddress address, Cursor addressObject) { for (int i = 0; i < address.size(); i++) addressObject.setString(type.dimensions().get(i).name(), address.label(i)); } - private static void encodeList(IndexedTensor tensor, Cursor cursor, long[] indexes, int dimension) { + private static void encodeValues(IndexedTensor tensor, Cursor cursor, long[] indexes, int dimension) { DimensionSizes sizes = tensor.dimensionSizes(); for (indexes[dimension] = 0; indexes[dimension] < sizes.size(dimension); ++indexes[dimension]) { if (dimension < (sizes.dimensions() - 1)) { - encodeList(tensor, cursor.addArray(), indexes, dimension + 1); + encodeValues(tensor, cursor.addArray(), indexes, dimension + 1); } else { cursor.addDouble(tensor.get(indexes)); } } } - private static void encodeMap(MappedTensor tensor, Cursor cursor) { - if (tensor.type().dimensions().size() > 1) - throw new IllegalStateException("JSON encode of mapped tensor can only contain a single dimension"); - tensor.cells().forEach((k,v) -> cursor.setDouble(k.label(0), v)); - } - - private static void encodeMapBlocks(MixedTensor tensor, Cursor cursor) { - var mappedDimensions = tensor.type().dimensions().stream().filter(d -> !d.isIndexed()).collect(Collectors.toList()); - if (mappedDimensions.size() != 1) { + private static void encodeBlocks(MixedTensor tensor, Cursor cursor) { + var mappedDimensions = tensor.type().dimensions().stream().filter(d -> d.isMapped()) + .map(d -> TensorType.Dimension.mapped(d.name())).collect(Collectors.toList()); + if (mappedDimensions.size() < 1) { throw new IllegalArgumentException("Should be ensured by caller"); } - String mappedDimensionName = mappedDimensions.get(0).name(); - int mappedDimensionIndex = tensor.type().indexOfDimension(mappedDimensionName). - orElseThrow(() -> new IllegalStateException("Could not find mapped dimension index")); + cursor = (mappedDimensions.size() == 1) ? cursor.setObject("blocks") : cursor.setArray("blocks"); - // Find all unique indices for the mapped dimension - Set<String> mappedIndices = new HashSet<>(); - tensor.cellIterator().forEachRemaining((cell) -> mappedIndices.add(cell.getKey().label(mappedDimensionIndex))); + // Create tensor type for mapped dimensions subtype + TensorType mappedSubType = new TensorType.Builder(mappedDimensions).build(); + + // Find all unique indices for the mapped dimensions + Set<TensorAddress> denseSubSpaceAddresses = new HashSet<>(); + tensor.cellIterator().forEachRemaining((cell) -> { + denseSubSpaceAddresses.add(subAddress(cell.getKey(), mappedSubType, tensor.type())); + }); // Slice out dense subspace of each and encode dense subspace as a list - for (String mappedIndex : mappedIndices) { - IndexedTensor denseSubspace = (IndexedTensor) new Slice<>(new ConstantTensor<>(tensor), - List.of(new Slice.DimensionValue<>(mappedDimensionName, mappedIndex))).evaluate(); - encodeList(denseSubspace, cursor.setArray(mappedIndex), new long[denseSubspace.dimensionSizes().dimensions()], 0); + for (TensorAddress denseSubSpaceAddress : denseSubSpaceAddresses) { + IndexedTensor denseSubspace = (IndexedTensor) sliceSubAddress(tensor, denseSubSpaceAddress, mappedSubType); + + if (mappedDimensions.size() == 1) { + encodeValues(denseSubspace, cursor.setArray(denseSubSpaceAddress.label(0)), new long[denseSubspace.dimensionSizes().dimensions()], 0); + } else { + Cursor block = cursor.addObject(); + encodeAddress(mappedSubType, denseSubSpaceAddress, block.setObject("address")); + encodeValues(denseSubspace, block.setArray("values"), new long[denseSubspace.dimensionSizes().dimensions()], 0); + } + + } + } + + private static TensorAddress subAddress(TensorAddress address, TensorType subType, TensorType origType) { + TensorAddress.Builder builder = new TensorAddress.Builder(subType); + for (TensorType.Dimension dim : subType.dimensions()) { + builder.add(dim.name(), address.label(origType.indexOfDimension(dim.name()). + orElseThrow(() -> new IllegalStateException("Could not find mapped dimension index")))); + } + return builder.build(); + } + + private static Tensor sliceSubAddress(Tensor tensor, TensorAddress subAddress, TensorType subType) { + List<Slice.DimensionValue<Name>> sliceDims = new ArrayList<>(subAddress.size()); + for (int i = 0; i < subAddress.size(); ++i) { + sliceDims.add(new Slice.DimensionValue<>(subType.dimensions().get(i).name(), subAddress.label(i))); } + return new Slice<>(new ConstantTensor<>(tensor), sliceDims).evaluate(); } /** Deserializes the given tensor from JSON format */ |