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@hoff97/tensor-js

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PyTorch like deep learning inferrence library

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import { DTypeGpu, GPUTensorConstructor, GPUTensorI } from '../../../tensor/gpu/interface'; import { GPUMemoryAllocator } from '../../../tensor/gpu/memory'; import { Input, Operation } from '../operation'; export interface UpsampleInfo { shapeX?: readonly number[]; widthX?: number; heightX?: number; shapeOutput?: readonly number[]; widthOutput?: number; heightOutput?: number; scales?: readonly number[]; } export interface UpsampleInput { X: GPUTensorI; scales: readonly number[]; } export declare class UpsampleOperation<GPUTensor extends GPUTensorI> extends Operation<GPUTensor, UpsampleInfo, UpsampleInput> { constructor(tensorConstructor: GPUTensorConstructor<GPUTensor>, dtype: DTypeGpu, allocator?: GPUMemoryAllocator); getFragmentShader(info: UpsampleInfo): string; getTextureNames(): string[]; getVariables(): string; getUniformAttrs(): Input[]; calc(input: UpsampleInput): GPUTensor; getOutputShape(input: UpsampleInput): readonly number[]; compile(info: UpsampleInfo): void; getCompilationInfo(input: UpsampleInput): UpsampleInfo; getInputInfoString(input: UpsampleInput): string; }