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| Original file line number | Diff line number | Diff line change |
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| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Licensed under the MIT License. | ||
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| import {Graph} from '../../../graph'; | ||
| import {OperatorImplementation, OperatorInitialization} from '../../../operators'; | ||
| import {Tensor} from '../../../tensor'; | ||
| import {ShapeUtil} from '../../../util'; | ||
| import {WebGpuInferenceHandler} from '../inference-handler'; | ||
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| export const squeeze: OperatorImplementation<number[]> = | ||
| (inferenceHandler: WebGpuInferenceHandler, inputs: Tensor[], axes: number[]): Tensor[] => { | ||
| validateInputs(inputs); | ||
| const outputShape = ShapeUtil.squeezeShape(inputs[0].dims, axes); | ||
| const output = inferenceHandler.reshape(inputs[0], outputShape); | ||
| return [output]; | ||
| }; | ||
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| export const squeezeV13 = (inferenceHandler: WebGpuInferenceHandler, inputs: Tensor[]): Tensor[] => { | ||
| validateInputsV13(inputs); | ||
| return squeeze(inferenceHandler, [inputs[0]], Array.from(inputs[1].integerData)); | ||
| }; | ||
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| export const parseSqueezeAttributes: OperatorInitialization<number[]> = (node: Graph.Node): number[] => | ||
| node.attributes.getInts('axes'); | ||
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| const validateInputs = (inputs: Tensor[]): void => { | ||
| if (!inputs || inputs.length !== 1) { | ||
| throw new Error('Squeeze requires 1 input.'); | ||
| } | ||
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| if (inputs[0].type === 'string') { | ||
| throw new Error('invalid input tensor types.'); | ||
| } | ||
| }; | ||
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| const validateInputsV13 = (inputs: Tensor[]): void => { | ||
| if (!inputs || inputs.length !== 2) { | ||
| throw new Error('Squeeze requires 2 inputs.'); | ||
| } | ||
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| if (inputs[1].type !== 'int32') { | ||
| throw new Error('Invalid input type.'); | ||
| } | ||
| }; |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,116 @@ | ||
| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Licensed under the MIT License. | ||
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| import {AttributeWithCacheKey, createAttributeWithCacheKey} from '../../../attribute-with-cache-key'; | ||
| import {Graph} from '../../../graph'; | ||
| import {OperatorAsyncImplementation, OperatorInitialization} from '../../../operators'; | ||
| import {Tensor} from '../../../tensor'; | ||
| import {ShapeUtil} from '../../../util'; | ||
| import {WebGpuInferenceHandler} from '../inference-handler'; | ||
| import {GpuDataType, ProgramInfo} from '../types'; | ||
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| import {createIndicesHelper, WORKGROUP_SIZE} from './common'; | ||
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| export interface TransposeAttributes extends AttributeWithCacheKey { | ||
| readonly perm: number[]; | ||
| } | ||
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| const transposeProgramMetadata = { | ||
| name: 'Transpose', | ||
| inputTypes: [GpuDataType.default] | ||
| }; | ||
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| export const transpose: OperatorAsyncImplementation<TransposeAttributes> = async( | ||
| inferenceHandler: WebGpuInferenceHandler, inputs: Tensor[], attributes: TransposeAttributes): Promise<Tensor[]> => { | ||
| validateInputs(inputs); | ||
| return inferenceHandler.run( | ||
| { | ||
| ...transposeProgramMetadata, | ||
| cacheHint: attributes.cacheKey, | ||
| get: () => createTransposeProgramInfo(inferenceHandler, inputs[0], attributes.perm) | ||
| }, | ||
| inputs); | ||
| }; | ||
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| export const parseTransposeAttributes: OperatorInitialization<TransposeAttributes> = | ||
| (node: Graph.Node): TransposeAttributes => createAttributeWithCacheKey({perm: node.attributes.getInts('perm', [])}); | ||
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| const createTransposeProgramInfo = | ||
| (_inferenceHandler: WebGpuInferenceHandler, input: Tensor, perm: number[]): ProgramInfo => { | ||
| const dataType = 'f32'; // TODO: support other data type | ||
| const inputShape = input.dims; | ||
| perm = getAdjustedPerm(inputShape, perm); | ||
| const outputShape = getOutputShape(inputShape, perm); | ||
| const rank = inputShape.length; | ||
| const outputSize = ShapeUtil.size(outputShape); | ||
| // A dims=[${inputs[0].dims.toString()}] | ||
| // out Dims=[${unpackedOutputShape.toString()}] | ||
| // based on perm=[${perm.toString()}] | ||
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| const outputIndicesHelper = createIndicesHelper('output', outputShape); | ||
| const inputIndicesHelper = createIndicesHelper('a', inputShape); | ||
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| const shaderSource = ` | ||
| const WORKGROUP_SIZE: u32 = ${WORKGROUP_SIZE}u; | ||
| @group(0) @binding(0) var<storage, read> a : array<${dataType}>; | ||
| @group(0) @binding(1) var<storage, read_write> output : array<${dataType}>; | ||
| ${permFunctionBody(perm, rank)} | ||
| ${outputIndicesHelper.o2iImpl} | ||
| ${inputIndicesHelper.i2oImpl} | ||
| @compute @workgroup_size(WORKGROUP_SIZE) | ||
| fn main(@builtin(global_invocation_id) global_id : vec3<u32>) { | ||
| // Guard against out-of-bounds work group sizes | ||
| if (global_id.x >= ${outputSize}u) { | ||
| return; | ||
| } | ||
| ${outputIndicesHelper.indicesVariableDeclaration('indices')} | ||
| ${outputIndicesHelper.o2iCall('global_id.x', 'indices')} | ||
| ${inputIndicesHelper.indicesVariableDeclaration('aIndices')} | ||
| perm(&aIndices, &indices); | ||
| output[global_id.x] = a[${inputIndicesHelper.i2oExpression('aIndices')}]; | ||
| }`; | ||
| return { | ||
| ...transposeProgramMetadata, | ||
| outputs: [{dims: outputShape, type: input.type, gpuDataType: GpuDataType.default}], | ||
| shaderSource, | ||
| dispatchGroup: () => ({x: Math.ceil(outputSize / 64 /* workgroup size */)}) | ||
| }; | ||
| }; | ||
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| const getAdjustedPerm = (inputShape: readonly number[], perm: number[]): number[] => { | ||
| if (perm && perm.length !== inputShape.length) { | ||
| perm = [...(inputShape.keys())].reverse(); | ||
| } | ||
| return perm; | ||
| }; | ||
|
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| const getOutputShape = (inputShape: readonly number[], perm: number[]): readonly number[] => { | ||
| perm = getAdjustedPerm(inputShape, perm); | ||
| return ShapeUtil.sortBasedOnPerm(inputShape, perm); | ||
| }; | ||
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| const permFunctionBody = (perm: number[], rank: number): string => { | ||
| const reverseFunc = []; | ||
| reverseFunc.push(`fn perm(a: ptr<function, array<u32, ${rank}>>, i: ptr<function, array<u32, ${rank}>>) {`); | ||
| for (let i = 0; i < rank; ++i) { | ||
| reverseFunc.push(`\t(*a)[${perm[i]}]=(*i)[${i}];`); | ||
| } | ||
| reverseFunc.push('\t}'); | ||
| return reverseFunc.join('\n'); | ||
| }; | ||
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| const validateInputs = (inputs: Tensor[]): void => { | ||
| if (!inputs || inputs.length !== 1) { | ||
| throw new Error('Transpose requires 1 input.'); | ||
| } | ||
|
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| if (inputs[0].type !== 'float32' && inputs[0].type !== 'float64') { | ||
| throw new Error('input should be float tensor'); | ||
| } | ||
| }; |
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