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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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export declare type PadInfo = { top: number; left: number; right: number; bottom: number; type: string; }; export declare type Conv2DInfo = { batchSize: number; inHeight: number; inWidth: number; inChannels: number; outHeight: number; outWidth: number; outChannels: number; dataFormat: 'channelsFirst' | 'channelsLast'; strideHeight: number; strideWidth: number; dilationHeight: number; dilationWidth: number; filterHeight: number; filterWidth: number; padInfo: PadInfo; inShape: [number, number, number, number]; outShape: [number, number, number, number]; filterShape: [number, number, number, number]; }; export declare function computePool2DInfo(inShape: [number, number, number, number], filterSize: [number, number] | number, strides: number | [number, number], pad: 'same' | 'valid' | number, roundingMode?: 'floor' | 'round' | 'ceil', dataFormat?: 'channelsFirst' | 'channelsLast'): Conv2DInfo; export declare function computeConv2DInfo(inShape: [number, number, number, number], filterShape: [number, number, number, number], strides: number | [number, number], dilations: number | [number, number], pad: 'same' | 'valid' | number, roundingMode?: 'floor' | 'round' | 'ceil', depthwise?: boolean, dataFormat?: 'channelsFirst' | 'channelsLast'): Conv2DInfo; export declare function computeDefaultPad(inputShape: [number, number, number], fieldSize: number, stride: number, dilation?: number): number;