@hoff97/tensor-js
Version:
PyTorch like deep learning inferrence library
24 lines (23 loc) • 927 B
TypeScript
import { Mode } from '../../../model/module';
import Tensor, { Activation, DType } from '../../../types';
import { OnnxNode } from '../../node';
import { Attributes, Constants } from '../../types';
export declare class ConvNode extends OnnxNode {
private group;
private dilations?;
private pads?;
private strides?;
kernel?: Tensor<any>;
bias?: Tensor<any>;
private activation;
constructor(attributes: Attributes, inputs: string[], outputs: string[], constants: Constants, onnxVersion: number, mode: Mode, kernel?: Tensor<any>, bias?: Tensor<any>, activation?: Activation);
forward<DTpe extends DType>(inputs: Tensor<DTpe>[]): Promise<Tensor<DTpe>[]>;
getDilations(rank: number): any[];
getPads(rank: number): any[];
getStrides(rank: number): any[];
getType(): string;
toCPU(): Promise<void>;
toWASM(): Promise<void>;
toGPU(): Promise<void>;
delete(): void;
}