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Add LogSoftmax for CPU #254

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Add LogSoftmax for CPU #254

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e13cee6
Add LogSoftmax for CPU
hayashikun Jan 3, 2021
4af5aa5
format
hayashikun Jan 13, 2021
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2 changes: 1 addition & 1 deletion docs/operators.md
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Expand Up @@ -75,7 +75,7 @@ _This file is automatically generated from the def files via [this script](/tool
| [Less](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Less) | | | [7-8](https://github.com/onnx/onnx/blob/master/docs/Changelog.md#Less-7), [9+](https://github.com/onnx/onnx/blob/master/docs/Changelog.md#Less-9) |
| [LessOrEqual](https://github.com/onnx/onnx/blob/master/docs/Operators.md#LessOrEqual) | | | |
| [Log](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Log) | [6+](https://github.com/onnx/onnx/blob/master/docs/Changelog.md#Log-6) | | [6+](https://github.com/onnx/onnx/blob/master/docs/Changelog.md#Log-6) |
| [LogSoftmax](https://github.com/onnx/onnx/blob/master/docs/Operators.md#LogSoftmax) | | | |
| [LogSoftmax](https://github.com/onnx/onnx/blob/master/docs/Operators.md#LogSoftmax) | [1-10](https://github.com/onnx/onnx/blob/master/docs/Changelog.md#LogSoftmax-1), [11+](https://github.com/onnx/onnx/blob/master/docs/Changelog.md#LogSoftmax-11) | | |
| [Loop](https://github.com/onnx/onnx/blob/master/docs/Operators.md#Loop) | | | |
| [LpNormalization](https://github.com/onnx/onnx/blob/master/docs/Operators.md#LpNormalization) | | | |
| [LpPool](https://github.com/onnx/onnx/blob/master/docs/Operators.md#LpPool) | | | |
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2 changes: 2 additions & 0 deletions lib/backends/cpu/op-resolve-rules.ts
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Expand Up @@ -17,6 +17,7 @@ import {CpuGather} from './ops/gather';
import {CpuGemm} from './ops/gemm';
import {CpuImageScaler} from './ops/image-scaler';
import {CpuInstanceNormalization} from './ops/instance-normalization';
import {CpuLogSoftmax} from './ops/log-softmax';
import {CpuLrn} from './ops/lrn';
import {CpuMatMul} from './ops/matmul';
import {CpuPad} from './ops/pad';
Expand Down Expand Up @@ -72,6 +73,7 @@ export const CPU_OP_RESOLVE_RULES: ReadonlyArray<OpSet.ResolveRule> = [
['IsNaN', '', '9+', () => new CpuUnaryOp(FLOAT_TYPES, unaryOps.isNan, undefined, 'bool')],
['LeakyRelu', '', '6+', () => new CpuUnaryOp(FLOAT_TYPES, unaryOps.leakyRelu, unaryOps.leakyReluInitializer)],
['Log', '', '6+', () => new CpuUnaryOp(FLOAT_TYPES, unaryOps.log)],
['LogSoftmax', '', '1+', () => new CpuLogSoftmax()],
['LRN', '', '1+', () => new CpuLrn()],
['MatMul', '', '1+', () => new CpuMatMul()],
['MaxPool', '', '1-9', () => new CpuMaxPool()], // TODO: support new attributes for MaxPool-8 and MaxPool-10
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28 changes: 28 additions & 0 deletions lib/backends/cpu/ops/log-softmax.ts
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@@ -0,0 +1,28 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT license.

import {LogSoftmax} from '../../../ops/log-softmax';
import {Tensor} from '../../../tensor';
import {CpuInferenceHandler} from '../inference-handler';
import {softmax} from './softmax';

export class CpuLogSoftmax extends LogSoftmax {
run(inferenceHandler: CpuInferenceHandler, inputs: Tensor[]): Tensor[] {
const output = logSoftmax(inputs[0], this.axis);
return [output];
}
}

export function logSoftmax(x: Tensor, axis: number): Tensor {
const y = softmax(x, axis);
const yData = y.numberData;

const output = new Tensor(x.dims, x.type);
const data = output.numberData;

for (let i = 0; i < yData.length; ++i) {
data[i] = Math.log(yData[i]);
}

return output;
}
33 changes: 33 additions & 0 deletions lib/ops/log-softmax.ts
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@@ -0,0 +1,33 @@
// 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 LogSoftmax implements Operator {
abstract run(inferenceHandler: InferenceHandler, inputs: Tensor[]): Tensor[]|Promise<Tensor[]>;

initialize(attributes: Attribute): void {
this.axis = attributes.getInt('axis', 1);
}

checkInputs(inputs: Tensor[]): boolean {
if (!inputs || inputs.length !== 1) {
return false;
}

return this.checkInputTypes(inputs);
}

protected checkInputTypes(inputs: Tensor[]): boolean {
if (inputs[0].type !== 'float32' && inputs[0].type !== 'float64') {
return false;
}

return true;
}

protected axis: number;
}
8 changes: 8 additions & 0 deletions test/test-suite-whitelist.jsonc
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Expand Up @@ -101,6 +101,13 @@
"test_leakyrelu",
// "test_lrn_default", <-- failing due to low precison. If absolute CPU error threshold is increased from 1e-4 to 1e-2 (100x increase), it passes the test.
// "test_lrn", <-- failing due to low precison. If absolute CPU error threshold is increased from 1e-4 to 1e-3 (10x increase), it passes the test.
"test_logsoftmax_example_1",
"test_logsoftmax_large_number",
"test_logsoftmax_axis_0",
"test_logsoftmax_axis_1",
"test_logsoftmax_axis_2",
"test_logsoftmax_negative_axis",
"test_logsoftmax_default_axis",
"test_matmul_2d",
"test_matmul_3d",
"test_matmul_4d",
Expand Down Expand Up @@ -245,6 +252,7 @@
"image-scaler.jsonc",
//"less.jsonc",
"log.jsonc",
// "log-softmax.jsonc",
"matmul.jsonc",
"mul.jsonc",
"neg.jsonc",
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