Add implementations and tests for reduceLogSum and reduceSumSquare ops

src/nn/graph_builder.ts

@@ -15,7 +15,7 @@ import {LeakyRelu} from './ops/leaky_relu';
 import {Pad} from './ops/pad';
 import {AveragePool2d, L2Pool2d, MaxPool2d} from './ops/pool2d';
 import {PRelu} from './ops/prelu';
-import {ReduceL1, ReduceL2, ReduceLogSumExp, ReduceMax, ReduceMean, ReduceMin, ReduceProduct, ReduceSum} from './ops/reduce';
+import {ReduceL1, ReduceL2, ReduceLogSum, ReduceLogSumExp, ReduceMax, ReduceMean, ReduceMin, ReduceProduct, ReduceSum, ReduceSumSquare} from './ops/reduce';
 import {Resample2d} from './ops/resample2d';
 import {Reshape} from './ops/reshape';
 import {Slice} from './ops/slice';
@@ -759,6 +759,14 @@ export class MLGraphBuilder {
     return (new ReduceL2(input, options)).output;
   }
 
+  /**
+   * [spec](https://webmachinelearning.github.io/webnn/#dom-mlgraphbuilder-reducelogsum)
+   */
+  reduceLogSum(input: MLOperand, options: MLReduceOptions = {}): MLOperand {
+    this.validateOperandBuilder([input]);
+    return (new ReduceLogSum(input, options)).output;
+  }
+
   /**
    * [spec](https://webmachinelearning.github.io/webnn/#dom-mlgraphbuilder-reducelogsumexp)
    */
@@ -806,6 +814,14 @@ export class MLGraphBuilder {
     this.validateOperandBuilder([input]);
     return (new ReduceSum(input, options)).output;
   }
+
+  /**
+   * [spec](https://webmachinelearning.github.io/webnn/#dom-mlgraphbuilder-reducesumsquare)
+   */
+  reduceSumSquare(input: MLOperand, options: MLReduceOptions = {}): MLOperand {
+    this.validateOperandBuilder([input]);
+    return (new ReduceSumSquare(input, options)).output;
+  }
   // end of reduction operations
 
   /**

src/nn/ops/reduce.ts

@@ -64,6 +64,24 @@ abstract class Reduce extends SingleOutputOperation {
       tf.Tensor;
 }
 
+export class ReduceL1 extends Reduce {
+  runOp(input: tf.Tensor, axes: number[], keepDimensions: boolean): tf.Tensor {
+    return tf.sum(tf.abs(input), axes, keepDimensions);
+  }
+}
+
+export class ReduceL2 extends Reduce {
+  runOp(input: tf.Tensor, axes: number[], keepDimensions: boolean): tf.Tensor {
+    return tf.sqrt(tf.sum(tf.pow(input, 2), axes, keepDimensions));
+  }
+}
+
+export class ReduceLogSum extends Reduce {
+  runOp(input: tf.Tensor, axes: number[], keepDimensions: boolean): tf.Tensor {
+    return tf.log(tf.sum(input, axes, keepDimensions));
+  }
+}
+
 export class ReduceLogSumExp extends Reduce {
   runOp(input: tf.Tensor, axes: number[], keepDimensions: boolean): tf.Tensor {
     return tf.logSumExp(input, axes, keepDimensions);
@@ -100,14 +118,8 @@ export class ReduceSum extends Reduce {
   }
 }
 
-export class ReduceL1 extends Reduce {
-  runOp(input: tf.Tensor, axes: number[], keepDimensions: boolean): tf.Tensor {
-    return tf.sum(tf.abs(input), axes, keepDimensions);
-  }
-}
-
-export class ReduceL2 extends Reduce {
+export class ReduceSumSquare extends Reduce {
   runOp(input: tf.Tensor, axes: number[], keepDimensions: boolean): tf.Tensor {
-    return tf.sqrt(tf.sum(tf.pow(input, 2), axes, keepDimensions));
+    return tf.sum(tf.pow(input, 2), axes, keepDimensions);
   }
 }