@hoff97/tensor-js/dist/lib/ops/gpu/pool/pool.d.ts

PyTorch like deep learning inferrence library

import { DTypeGpu, GPUTensorConstructor, GPUTensorI } from '../../../tensor/gpu/interface';
import { GPUMemoryAllocator } from '../../../tensor/gpu/memory';
import { Input, Operation } from '../operation';
export interface PoolInfo {
    shapeX?: readonly number[];
    widthX?: number;
    heightX?: number;
    shapeOutput?: readonly number[];
    widthOutput?: number;
    heightOutput?: number;
    axes?: readonly number[];
    keepDims?: boolean;
    mappedInputStrides?: number[];
    sumDims?: number[];
    sumSize?: number;
}
export interface PoolInput {
    X: GPUTensorI;
    axes: number[];
    keepDims: boolean;
}
export declare abstract class PoolOperation<GPUTensor extends GPUTensorI> extends Operation<GPUTensor, PoolInfo, PoolInput> {
    protected maxIterations: number;
    constructor(tensorConstructor: GPUTensorConstructor<GPUTensor>, dtype: DTypeGpu, allocator?: GPUMemoryAllocator);
    getVariables(): string;
    getFragmentShader(info: PoolInfo): string;
    abstract update(a: string, b: string): string;
    post(res: string): string;
    init(res: string): string;
    getTextureNames(): string[];
    getUniformAttrs(): Input[];
    calc(input: PoolInput): GPUTensor;
    getOutputShape(input: PoolInput): readonly number[];
    compile(info: PoolInfo): void;
    getCompilationInfo(input: PoolInput): PoolInfo;
    getInputInfoString(input: PoolInput): string;
}