diff options
author | Henning Baldersheim <balder@yahoo-inc.com> | 2022-12-04 23:02:42 +0100 |
---|---|---|
committer | GitHub <noreply@github.com> | 2022-12-04 23:02:42 +0100 |
commit | 5381962e747ea9ac515abcf51dc70ad40bbbf70d (patch) | |
tree | d25af24e6a007091bb4a321a63747f1c7b439045 /vespajlib/src/main/java/com/yahoo/tensor/serialization | |
parent | 2555b49b4390ed9dac9eab3959d6cc6e3511515c (diff) |
Revert "Revert collect(Collectors.toList())"
Diffstat (limited to 'vespajlib/src/main/java/com/yahoo/tensor/serialization')
-rw-r--r-- | vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java | 2 | ||||
-rw-r--r-- | vespajlib/src/main/java/com/yahoo/tensor/serialization/MixedBinaryFormat.java | 8 |
2 files changed, 5 insertions, 5 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 b683519988c..a7afc1efc6d 100644 --- a/vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java +++ b/vespajlib/src/main/java/com/yahoo/tensor/serialization/JsonFormat.java @@ -124,7 +124,7 @@ public class JsonFormat { 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()); + .map(d -> TensorType.Dimension.mapped(d.name())).toList(); if (mappedDimensions.size() < 1) { throw new IllegalArgumentException("Should be ensured by caller"); } diff --git a/vespajlib/src/main/java/com/yahoo/tensor/serialization/MixedBinaryFormat.java b/vespajlib/src/main/java/com/yahoo/tensor/serialization/MixedBinaryFormat.java index 2a55ac658b1..c18e9f179d6 100644 --- a/vespajlib/src/main/java/com/yahoo/tensor/serialization/MixedBinaryFormat.java +++ b/vespajlib/src/main/java/com/yahoo/tensor/serialization/MixedBinaryFormat.java @@ -43,7 +43,7 @@ class MixedBinaryFormat implements BinaryFormat { } private void encodeSparseDimensions(GrowableByteBuffer buffer, MixedTensor tensor) { - List<TensorType.Dimension> sparseDimensions = tensor.type().dimensions().stream().filter(d -> !d.isIndexed()).collect(Collectors.toList()); + List<TensorType.Dimension> sparseDimensions = tensor.type().dimensions().stream().filter(d -> !d.isIndexed()).toList(); buffer.putInt1_4Bytes(sparseDimensions.size()); for (TensorType.Dimension dimension : sparseDimensions) { buffer.putUtf8String(dimension.name()); @@ -51,7 +51,7 @@ class MixedBinaryFormat implements BinaryFormat { } private void encodeDenseDimensions(GrowableByteBuffer buffer, MixedTensor tensor) { - List<TensorType.Dimension> denseDimensions = tensor.type().dimensions().stream().filter(d -> d.isIndexed()).collect(Collectors.toList()); + List<TensorType.Dimension> denseDimensions = tensor.type().dimensions().stream().filter(d -> d.isIndexed()).toList(); buffer.putInt1_4Bytes(denseDimensions.size()); for (TensorType.Dimension dimension : denseDimensions) { buffer.putUtf8String(dimension.name()); @@ -71,7 +71,7 @@ class MixedBinaryFormat implements BinaryFormat { } private void encodeCells(GrowableByteBuffer buffer, MixedTensor tensor, Consumer<Double> consumer) { - List<TensorType.Dimension> sparseDimensions = tensor.type().dimensions().stream().filter(d -> !d.isIndexed()).collect(Collectors.toList()); + List<TensorType.Dimension> sparseDimensions = tensor.type().dimensions().stream().filter(d -> !d.isIndexed()).toList(); long denseSubspaceSize = tensor.denseSubspaceSize(); if (sparseDimensions.size() > 0) { buffer.putInt1_4Bytes((int)(tensor.size() / denseSubspaceSize)); // XXX: Size truncation @@ -137,7 +137,7 @@ class MixedBinaryFormat implements BinaryFormat { } private void decodeCells(GrowableByteBuffer buffer, MixedTensor.BoundBuilder builder, TensorType type, Supplier<Double> supplier) { - List<TensorType.Dimension> sparseDimensions = type.dimensions().stream().filter(d -> !d.isIndexed()).collect(Collectors.toList()); + List<TensorType.Dimension> sparseDimensions = type.dimensions().stream().filter(d -> !d.isIndexed()).toList(); TensorType sparseType = MixedTensor.createPartialType(type.valueType(), sparseDimensions); long denseSubspaceSize = builder.denseSubspaceSize(); |