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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 ConcatInfo { shapeA?: readonly number[]; widthA?: number; heightA?: number; shapeB?: readonly number[]; widthB?: number; heightB?: number; shapeOutput?: readonly number[]; widthOutput?: number; heightOutput?: number; axis?: number; } export interface ConcatInput { A: GPUTensorI; B: GPUTensorI; axis: number; } export declare class ConcatOperation<GPUTensor extends GPUTensorI> extends Operation<GPUTensor, ConcatInfo, ConcatInput> { constructor(tensorConstructor: GPUTensorConstructor<GPUTensor>, dtype: DTypeGpu, allocator?: GPUMemoryAllocator); getVariables(): string; getUniformAttrs(): Input[]; getFragmentShader(info: ConcatInfo): string; getTextureNames(): string[]; calc(input: ConcatInput): GPUTensor; getOutputShape(input: ConcatInput): readonly number[]; compile(info: ConcatInfo): void; getCompilationInfo(input: ConcatInput): ConcatInfo; getInputInfoString(input: ConcatInput): string; }