Matrix: 'fromList' and 'fromFlattenedList' speed up (#180)

CHANGELOG.md

@@ -1,5 +1,9 @@
 # Changelog
 
+## 13.12.6
+- `Matrix.fromList`, `Matrix.fromFlattenedList`:
+  - speed up
+
 ## 13.12.5
 - `Vector.randomFilled`:
   - factory-constructor speed-up

benchmark/matrix/float32/matrix_initializing/float32_matrix_from_flattened.dart

@@ -1,5 +1,5 @@
 // Approx. 2.8 seconds (MacBook Air mid 2017), Dart VM version: 2.5.0
-// Approx. 1.1 second (MacBook Pro mid 2019), Dart VM version: 2.16.0
+// Approx. 0.6 second (MacBook Pro mid 2019), Dart VM version: 3.2.4
 
 import 'package:benchmark_harness/benchmark_harness.dart';
 import 'package:ml_linalg/dtype.dart';

benchmark/matrix/float32/matrix_initializing/float32_matrix_from_flattened_float32.dart

@@ -0,0 +1,40 @@
+// Approx. 86 microsecond (MacBook Pro mid 2019), Dart VM version: 3.2.4
+
+import 'dart:typed_data';
+
+import 'package:benchmark_harness/benchmark_harness.dart';
+import 'package:ml_linalg/dtype.dart';
+import 'package:ml_linalg/matrix.dart';
+import 'package:ml_linalg/vector.dart';
+
+const numOfRows = 10000;
+const numOfColumns = 1000;
+
+class Float32MatrixFromFlattenedFloat32ListBenchmark extends BenchmarkBase {
+  Float32MatrixFromFlattenedFloat32ListBenchmark()
+      : super(
+            'Matrix initialization (fromFlattenedList, source list is Float32List)');
+
+  late Float32List _source;
+
+  static void main() {
+    Float32MatrixFromFlattenedFloat32ListBenchmark().report();
+  }
+
+  @override
+  void run() {
+    Matrix.fromFlattenedList(_source, numOfRows, numOfColumns,
+        dtype: DType.float32);
+  }
+
+  @override
+  void setup() {
+    _source = Float32List.fromList(Vector.randomFilled(numOfRows * numOfColumns,
+            min: -1000, max: 1000, seed: 12)
+        .toList(growable: false));
+  }
+}
+
+void main() {
+  Float32MatrixFromFlattenedFloat32ListBenchmark.main();
+}

benchmark/matrix/float32/matrix_initializing/float32_matrix_from_list.dart

@@ -1,5 +1,5 @@
 // Approx. 1 second (MacBook Air mid 2017), Dart VM version: 2.5.0
-// Approx. 0.5 second (MacBook Pro mid 2019), Dart VM version: 2.16.0
+// Approx. 0.38 second (MacBook Pro mid 2019), Dart VM version: 3.2.4
 
 import 'package:benchmark_harness/benchmark_harness.dart';
 import 'package:ml_linalg/dtype.dart';

benchmark/matrix/float32/matrix_initializing/float32_matrix_from_rows.dart

@@ -1,5 +1,5 @@
 // Approx. 1.2 seconds (MacBook Air mid 2017), Dart VM version: 2.5.0
-// Approx. 0.8 second (MacBook Pro mid 2019), Dart VM version: 2.16.0
+// Approx. 0.8 second (MacBook Pro mid 2019), Dart VM version: 3.2.4
 
 import 'package:benchmark_harness/benchmark_harness.dart';
 import 'package:ml_linalg/dtype.dart';

lib/src/matrix/float32_matrix.dart

@@ -44,13 +44,13 @@ class Float32Matrix
         _flattenedList =
             Float32List(source.length * getLengthOfFirstOrZero(source)) {
     for (var i = 0; i < source.length; i++) {
-      if (source[i].length != columnCount) {
-        throw Exception('Wrong nested list length: ${source[i].length}, '
+      final column = source[i];
+      if (column.length != columnCount) {
+        throw Exception('Wrong nested list length: ${column.length}, '
             'expected length: $columnCount');
       }
-
-      for (var j = 0; j < source[i].length; j++) {
-        _flattenedList[i * columnCount + j] = source[i][j];
+      for (var j = 0; j < column.length; j++) {
+        _flattenedList[i * columnCount + j] = column[j];
       }
     }
   }
@@ -112,12 +112,18 @@ class Float32Matrix
         _rowCache = List<Vector?>.filled(rowCount, null),
         _colCache = List<Vector?>.filled(colCount, null),
         _flattenedList =
-            source is Float32List ? source : Float32List.fromList(source) {
+            source is Float32List ? source : Float32List(source.length) {
     if (source.length < rowCount * colCount) {
       throw Exception('Invalid matrix dimension has been provided - '
           '$rowCount x $colCount, but given a collection of length '
           '${source.length}');
     }
+
+    if (source is! Float32List) {
+      for (var i = 0; i < _flattenedList.length; i++) {
+        _flattenedList[i] = source[i];
+      }
+    }
   }
 
   Float32Matrix.fromByteData(ByteData source, int rowCount, int colCount)

lib/src/matrix/float64_matrix.g.dart

@@ -47,13 +47,13 @@ class Float64Matrix
         _flattenedList =
             Float64List(source.length * getLengthOfFirstOrZero(source)) {
     for (var i = 0; i < source.length; i++) {
-      if (source[i].length != columnCount) {
-        throw Exception('Wrong nested list length: ${source[i].length}, '
+      final column = source[i];
+      if (column.length != columnCount) {
+        throw Exception('Wrong nested list length: ${column.length}, '
             'expected length: $columnCount');
       }
-
-      for (var j = 0; j < source[i].length; j++) {
-        _flattenedList[i * columnCount + j] = source[i][j];
+      for (var j = 0; j < column.length; j++) {
+        _flattenedList[i * columnCount + j] = column[j];
       }
     }
   }
@@ -115,12 +115,18 @@ class Float64Matrix
         _rowCache = List<Vector?>.filled(rowCount, null),
         _colCache = List<Vector?>.filled(colCount, null),
         _flattenedList =
-            source is Float64List ? source : Float64List.fromList(source) {
+            source is Float64List ? source : Float64List(source.length) {
     if (source.length < rowCount * colCount) {
       throw Exception('Invalid matrix dimension has been provided - '
           '$rowCount x $colCount, but given a collection of length '
           '${source.length}');
     }
+
+    if (source is! Float64List) {
+      for (var i = 0; i < _flattenedList.length; i++) {
+        _flattenedList[i] = source[i];
+      }
+    }
   }
 
   Float64Matrix.fromByteData(ByteData source, int rowCount, int colCount)

pubspec.yaml

@@ -1,6 +1,6 @@
 name: ml_linalg
 description: SIMD-based linear algebra and statistics, efficient manipulation with numeric data
-version: 13.12.5
+version: 13.12.6
 homepage: https://github.com/gyrdym/ml_linalg
 
 environment: