// Copyright (c) Microsoft Corporation. All rights reserved. // Licensed under the MIT License. import {AttributeWithCacheKey, createAttributeWithCacheKey} from '../../../attribute-with-cache-key'; import {Graph} from '../../../graph'; import {NUMBER_TYPES, OperatorImplementation, OperatorInitialization} from '../../../operators'; import {Tensor} from '../../../tensor'; import {ShapeUtil} from '../../../util'; import {WebGLInferenceHandler} from '../inference-handler'; import {ProgramInfo, TextureType} from '../types'; export interface SliceAttributes extends AttributeWithCacheKey { readonly axes: number[]; readonly ends: number[]; readonly starts: number[]; } const sliceProgramMetadata = { name: 'Slice', inputNames: ['A'], inputTypes: [TextureType.unpacked] }; export const slice: OperatorImplementation = (inferenceHandler: WebGLInferenceHandler, inputs: Tensor[], attributes: SliceAttributes): Tensor[] => { validateInputs(inputs); const output = inferenceHandler.run( { ...sliceProgramMetadata, cacheHint: attributes.cacheKey, get: () => createSliceProgramInfo(inferenceHandler, inputs[0], attributes) }, inputs); return [output]; }; export const parseSliceAttributes: OperatorInitialization = (node: Graph.Node): SliceAttributes => { const starts = node.attributes.getInts('starts'); const ends = node.attributes.getInts('ends'); const axes = node.attributes.getInts('axes', []); return createAttributeWithCacheKey({starts, ends, axes}); }; const createSliceProgramInfo = (_inferenceHandler: WebGLInferenceHandler, input: Tensor, attributes: SliceAttributes): ProgramInfo => { const axes = (attributes.axes.length === 0) ? input.dims.slice(0).map((_val, i) => i) : attributes.axes; const normalizedAxes = ShapeUtil.normalizeAxes(axes, input.dims.length); const starts = attributes.starts.map((start, i) => { if (start > input.dims[normalizedAxes[i]] - 1) { return input.dims[normalizedAxes[i]]; } return ShapeUtil.normalizeAxis(start, input.dims[normalizedAxes[i]]); }); const ends = attributes.ends.map((end, i) => { if (end > input.dims[normalizedAxes[i]] - 1) { return input.dims[normalizedAxes[i]]; } return ShapeUtil.normalizeAxis(end, input.dims[normalizedAxes[i]]); }); const outputShape = input.dims.slice(); const sliceOps: string[] = []; for (let i = 0; i < normalizedAxes.length; i++) { outputShape[normalizedAxes[i]] = ends[i] - starts[i]; if (starts[i] > 0) { sliceOps.push(`outputIdx[${normalizedAxes[i]}] += ${starts[i]};`); } // else { sliceOps.push(`outputIdx[${normalizedAxes[i]}] += 0;`); } } const rank = outputShape.length; const shaderSource = ` float process(int outputIdx[${rank}]) { ${sliceOps.join('\n ')} return _A(outputIdx); }`; return { ...sliceProgramMetadata, output: {dims: outputShape, type: input.type, textureType: TextureType.unpacked}, shaderSource }; }; const validateInputs = (inputs: Tensor[]): void => { if (!inputs || inputs.length !== 1) { throw new Error('Slice requires 1 input.'); } if (NUMBER_TYPES.indexOf(inputs[0].type) === -1) { throw new Error('Invalid input type.'); } }; export const sliceV10 = (inferenceHandler: WebGLInferenceHandler, inputs: Tensor[]): Tensor[] => { validateInputsV10(inputs); const attributes = generateSliceAttributesFromInputs(inferenceHandler, inputs); const output = inferenceHandler.run( { ...sliceProgramMetadata, cacheHint: attributes.cacheKey, get: () => createSliceProgramInfo(inferenceHandler, inputs[0], attributes) }, [inputs[0]]); return [output]; }; const generateSliceAttributesFromInputs = (inferenceHandler: WebGLInferenceHandler, inputs: Tensor[]): SliceAttributes => { if (!inferenceHandler.session.isInitializer(inputs[1].dataId) || !inferenceHandler.session.isInitializer(inputs[2].dataId) || (inputs.length >= 4 && !inferenceHandler.session.isInitializer(inputs[3].dataId)) || (inputs.length >= 5 && !inferenceHandler.session.isInitializer(inputs[4].dataId))) { throw new Error('dynamic slice attributes are not allowed'); } if (inputs.length >= 5 && inputs[4].integerData.some((i: number) => i !== 1)) { throw new Error('currently non-1 steps is not supported for Slice'); } const starts = Array.from(inputs[1].integerData); const ends = Array.from(inputs[2].integerData); const axes = inputs.length >= 4 ? Array.from(inputs[3].integerData) : []; const cacheKey = `${axes};${starts};${ends}`; return {starts, ends, axes, cacheKey}; }; const validateInputsV10 = (inputs: Tensor[]): void => { if (!inputs || inputs.length < 3 || inputs.length > 5) { throw new Error('Invalid input number.'); } if (inputs[1].type !== 'int32' || inputs[1].dims.length !== 1) { throw new Error('Invalid input type.'); } if (inputs[2].type !== 'int32' || inputs[2].dims.length !== 1) { throw new Error('Invalid input type.'); } if (inputs.length >= 4 && (inputs[3].type !== 'int32' || inputs[3].dims.length !== 1)) { throw new Error('Invalid input type.'); } if (inputs.length >= 5 && (inputs[4].type !== 'int32' || inputs[4].dims.length !== 1)) { throw new Error('Invalid input type.'); } };