@tensorflow/tfjs-core/dist/kernels/webgl/binaryop_packed_gpu.d.ts

Hardware-accelerated JavaScript library for machine intelligence

import { GPGPUContext } from './gpgpu_context';
import { GPGPUProgram } from './gpgpu_math';
export declare const PACKED_DIV = "\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  result.x = a.x == b.x ? 1. : result.x;\n  result.y = a.y == b.y ? 1. : result.y;\n  result.z = a.z == b.z ? 1. : result.z;\n  result.w = a.w == b.w ? 1. : result.w;\n  return result;\n";
export declare const PACKED_INT_DIV = "\n  vec4 resultSign = sign(a) * sign(b);\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  ivec4 result = ia / ib;\n  ivec4 amodb = ia - ib * result;\n\n  // Vectorize INT_DIV\n  // if (resultSign < 0.0 && amodb != 0) result -= 1;\n  // return float(result);\n  return vec4(result -\n     ivec4(lessThan(resultSign, vec4(0.0))) * ivec4(notEqual(amodb, ivec4(0))));\n";
export declare const PACKED_POW = "\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  result.r = isNaN.r == 1.0 ? NAN : result.r;\n  result.g = isNaN.g == 1.0 ? NAN : result.g;\n  result.b = isNaN.b == 1.0 ? NAN : result.b;\n  result.a = isNaN.a == 1.0 ? NAN : result.a;\n\n  return result;\n";
export declare class BinaryOpPackedProgram implements GPGPUProgram {
    variableNames: string[];
    outputShape: number[];
    userCode: string;
    supportsBroadcasting: boolean;
    usesPackedTextures: boolean;
    startLoc: WebGLUniformLocation;
    constructor(op: string, aShape: number[], bShape: number[]);
    getCustomSetupFunc(): (gpgpu: GPGPUContext, webGLProgram: WebGLProgram) => void;
}