Scatter ops for webworker

lib/backends/cpu/op-resolve-rules.ts

@@ -21,6 +21,7 @@ import {CpuPad} from './ops/pad';
 import {CpuAveragePool, CpuGlobalAveragePool, CpuGlobalMaxPool, CpuMaxPool} from './ops/pool';
 import * as cpuReduce from './ops/reduce';
 import {CpuReshape} from './ops/reshape';
+import {CpuScatter} from './ops/scatter';
 import {CpuSlice, CpuSliceV10} from './ops/slice';
 import {CpuSoftmax} from './ops/softmax';
 import {CpuSqueeze} from './ops/squeeze';
@@ -104,4 +105,5 @@ export const CPU_OP_RESOLVE_RULES: ReadonlyArray<OpSet.ResolveRule> = [
   ['Unsqueeze', '', '1+', () => new CpuUnsqueeze()],
   ['Upsample', '', '7-8', () => new CpuUpsample()],
   ['Xor', '', '7+', () => new CpuBinaryOp(['bool'], (e1, e2) => (e1 ^ e2))],
+  ['Scatter', '', '7+', () => new CpuScatter()],
 ];

lib/backends/cpu/ops/scatter.ts

@@ -0,0 +1,29 @@
+import {Scatter} from '../../../ops/scatter';
+import {Tensor} from '../../../tensor';
+import {CpuInferenceHandler} from '../inference-handler';
+
+export class CpuScatter extends Scatter {
+  run(inferenceHandler: CpuInferenceHandler, inputs: Tensor[]): Tensor[]|Promise<Tensor[]> {
+    const output = scatter(inputs[0], inputs[1], inputs[2]);
+    return [output];
+  }
+}
+
+export function scatter(data: Tensor, indices: Tensor, updates: Tensor): Tensor {
+  const datadims = data.dims;
+  const indicedims = indices.dims;
+  const updatedims = updates.dims;
+  const datanew = new Tensor(datadims, data.type);
+  const Y = datanew.data;
+  const X = updates.data;
+  let flatIndex = 0;
+  let updateFlatIndex = 0;
+  for (let i = 0; i < datadims[0]; ++i) {
+    for (let j = 0; j < indicedims[1]; ++j) {
+      flatIndex = i * datadims[1] + (indices.data[j] as number);
+      updateFlatIndex = i * updatedims[1] + j;
+      Y[flatIndex] = X[updateFlatIndex];
+    }
+  }
+  return new Tensor(datadims, data.type, undefined, undefined, Y);
+}

lib/ops/scatter.ts

@@ -0,0 +1,39 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT license.
+
+import {Attribute} from '../attribute';
+import {InferenceHandler} from '../backend';
+import {Operator} from '../operators';
+import {Tensor} from '../tensor';
+
+export abstract class Scatter implements Operator {
+  // Inputs are {data_tensor->float32/float64, indices_tensor-> int32, update_data_tensor->float32/float64}
+  abstract run(inferenceHandler: InferenceHandler, inputs: Tensor[]): Tensor[]|Promise<Tensor[]>;
+
+  initialize(attributes: Attribute): void {}
+
+  checkInputs(inputs: Tensor[]): boolean {
+    if (!inputs || inputs.length !== 3) {
+      return false;
+    }
+    const tensorRank = inputs[0].dims.length;
+    if (tensorRank < 1) {
+      return false;
+    }
+
+    return this.checkInputTypes(inputs);
+  }
+
+  protected checkInputTypes(inputs: Tensor[]): boolean {
+    if (inputs[0].type !== 'float32' && inputs[0].type !== 'float64') {
+      return false;
+    }
+    if (inputs[1].type !== 'int32' && inputs[1].type !== 'int16') {
+      return false;
+    }
+    if (inputs[2].type !== 'float32' && inputs[2].type !== 'float64') {
+      return false;
+    }
+    return true;
+  }
+}

test/test-suite-whitelist.jsonc

@@ -82,6 +82,7 @@
       "test_flatten_default_axis",
       "test_gather_0",
       "test_gather_1",
+      "test_scatter_0",
       "test_gemm_broadcast",
       "test_gemm_nobroadcast",
       "test_globalaveragepool_precomputed",