Sam-Izdat

// MICROSOFT SPYWARE
zone "telemetry.microsoft.com" { type master; file "/etc/bind/blockeddomains.db"; };
zone "a-0001.a-msedge.net" { type master; file "/etc/bind/blockeddomains.db"; };
zone "choice.microsoft.com" { type master; file "/etc/bind/blockeddomains.db"; };
zone "choice.microsoft.com.nsatc.net" { type master; file "/etc/bind/blockeddomains.db"; };
zone "compatexchange.cloudapp.net" { type master; file "/etc/bind/blockeddomains.db"; };
zone "corp.sts.microsoft.com" { type master; file "/etc/bind/blockeddomains.db"; };
zone "corpext.msitadfs.glbdns2.microsoft.com" { type master; file "/etc/bind/blockeddomains.db"; };
zone "cs1.wpc.v0cdn.net" { type master; file "/etc/bind/blockeddomains.db"; };
zone "df.telemetry.microsoft.com" { type master; file "/etc/bind/blockeddomains.db"; };

Sam-Izdat

KiB Mem:   1012384 total,   974288 used,    38096 free,   128872 buffers
KiB Swap:  3068924 total,      372 used,  3068552 free.   356848 cached Mem

PID USER      PR  NI    VIRT    RES    SHR S  %CPU %MEM     TIME+ COMMAND
 6395 bind      20   0  312536 231284   2476 S   0.0 22.8   0:55.11 /usr/sbin/named -u bin

Sam-Izdat

@ti.func
def _bilateral_interp_coeffs(self, 
    uv_grid:tm.vec2, 
    probe_elevation:float, 
    grid_height:int, 
    grid_width:int, 
    probe_height:int, 
    probe_width:int,
    cascade:int) -> (tm.ivec4, tm.vec4):
    """Returns pixel indices and weights for interpolation"""

Sam-Izdat

import time

import math
import torch

import taichi as ti
import taichi.math as tm

import tinytex as ttex
from tinycio import fsio

Sam-Izdat

@classmethod
def normals_to_height(cls, 
normal_map:torch.Tensor, 
self_tiling:bool=False, 
rescaled:bool=False,
eps:float=torch.finfo(torch.float32).eps) -> (torch.Tensor, torch.Tensor):
"""
Compute height from normals. Frankot-Chellappa algorithm.

:param normal_map: Normal map tensor sized [N, C=3, H, W] or [C=3, H, W] 

Sam-Izdat

import random
import torch
import numpy as np

import typing
from typing import Union

from combomethod import combomethod

from tinycio import fsio

Sam-Izdat

import {g, tm} from './util';

let ready = false;
let setup = () => ti.addToKernelScope({
  g, tm,
  ColorTransform, TransferFunction,
  convert_to_xyz, convert_from_xyz, convert_color_space 
});

export class ColorTransform {

Sam-Izdat

import {g, tm} from './util';
import {ColorTransform, TransferFunction} from './colorspace';

let ready = false;
let setup = () => ti.addToKernelScope({
  tm,
  ColorTransform, TransferFunction,
  ToneMapping,
  tone_map,
  tone_map_hable, _hable_partial, 

Sam-Izdat

import numpy as np

# [ 32, 32 ]
# GGX_E[32-roughness][32-cos_theta]
GGX_E = np.array([
[0.9635857939720154, 0.995747983455658, 0.9983890056610107, 0.9992253184318542, 0.9995855093002319, 0.9996441006660461, 0.9998587369918823, 0.99983811378479, 0.9998855590820312, 0.9998201727867126, 0.9998736381530762, 0.9998807311058044, 0.9998859763145447, 0.9998285174369812, 0.9999691247940063, 0.9998969435691833, 0.9999278783798218, 0.9999445676803589, 0.999960720539093, 0.9999779462814331, 0.9999331831932068, 0.9999798536300659, 0.999980628490448, 0.9999813437461853, 0.9999666213989258, 0.9999518990516663, 0.999967634677887, 0.9999833106994629, 0.9999531507492065, 0.9999687671661377, 0.9999690651893616, 0.9999998807907104],
[0.9624530076980591, 0.9955804944038391, 0.9987631440162659, 0.9992542862892151, 0.9995307326316833, 0.9997747540473938, 0.9998279809951782, 0.999792218208313, 0.999916136264801, 0.9996671080589294, 0.9998441338539124, 0.9997889399528503, 0.9998522996902466, 0.9998584389686584, 0.9999077916145325, 0

Sam-Izdat

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