How to use orig method in Slash

Best Python code snippet using slash

regress-311161.js

Source:regress-311161.js

1// |reftest| skip-if(!Object.prototype.toSource)2/* -*- indent-tabs-mode: nil; js-indent-level: 2 -*- */3/* This Source Code Form is subject to the terms of the Mozilla Public4 * License, v. 2.0. If a copy of the MPL was not distributed with this5 * file, You can obtain one at http://mozilla.org/MPL/2.0/. */6//-----------------------------------------------------------------------------7var BUGNUMBER = 311161;8var summary = 'toSource exposes random memory or crashes';9var actual = 'No Crash';10var expect = 'No Crash';11printBugNumber(BUGNUMBER);12printStatus (summary);13 14var commands =15 [{origCount:1, fun:(function anonymous() {allElements[2].style.background = "#fcd";})},16{origCount:2, fun:(function anonymous() {allElements[9].style.width = "20em";})},17{origCount:3, fun:(function anonymous() {allElements[4].style.width = "200%";})},18{origCount:4, fun:(function anonymous() {allElements[6].style.clear = "right";})},19{origCount:5, fun:(function anonymous() {allElements[8].style.visibility = "hidden";})},20{origCount:6, fun:(function anonymous() {allElements[1].style.overflow = "visible";})},21{origCount:7, fun:(function anonymous() {allElements[4].style.position = "fixed";})},22{origCount:8, fun:(function anonymous() {allElements[10].style.display = "-moz-inline-box";})},23{origCount:9, fun:(function anonymous() {allElements[10].style.overflow = "auto";})},24{origCount:10, fun:(function anonymous() {allElements[11].style.color = "red";})},25{origCount:11, fun:(function anonymous() {allElements[4].style.height = "2em";})},26{origCount:12, fun:(function anonymous() {allElements[9].style.height = "100px";})},27{origCount:13, fun:(function anonymous() {allElements[5].style['float'] = "none";})},28{origCount:14, fun:(function anonymous() {allElements[9].style.color = "blue";})},29{origCount:15, fun:(function anonymous() {allElements[2].style.clear = "right";})},30{origCount:16, fun:(function anonymous() {allElements[1].style.height = "auto";})},31{origCount:17, fun:(function anonymous() {allElements[0].style.overflow = "hidden";})},32{origCount:18, fun:(function anonymous() {allElements[4].style.display = "table-row-group";})},33{origCount:19, fun:(function anonymous() {allElements[4].style.overflow = "auto";})},34{origCount:20, fun:(function anonymous() {allElements[7].style.height = "100px";})},35{origCount:21, fun:(function anonymous() {allElements[5].style.color = "green";})},36{origCount:22, fun:(function anonymous() {allElements[3].style.display = "-moz-grid-group";})},37{origCount:23, fun:(function anonymous() {allElements[7].style['float'] = "none";})},38{origCount:24, fun:(function anonymous() {allElements[10].style.position = "static";})},39{origCount:25, fun:(function anonymous() {allElements[3].style['float'] = "none";})},40{origCount:26, fun:(function anonymous() {allElements[4].style['float'] = "none";})},41{origCount:27, fun:(function anonymous() {allElements[8].style['float'] = "none";})},42{origCount:28, fun:(function anonymous() {allElements[5].style.visibility = "collapse";})},43{origCount:29, fun:(function anonymous() {allElements[1].style.position = "static";})},44{origCount:30, fun:(function anonymous() {allElements[2].style.color = "black";})},45{origCount:31, fun:(function anonymous() {allElements[0].style.position = "fixed";})},46{origCount:32, fun:(function anonymous() {allElements[0].style.display = "table-row-group";})},47{origCount:33, fun:(function anonymous() {allElements[9].style.position = "relative";})},48{origCount:34, fun:(function anonymous() {allElements[5].style.position = "static";})},49{origCount:35, fun:(function anonymous() {allElements[6].style.background = "transparent";})},50{origCount:36, fun:(function anonymous() {allElements[6].style.color = "blue";})},51{origCount:37, fun:(function anonymous() {allElements[9].style.background = "url(http://www.google.com/images/logo_sm.gif)";})},52{origCount:38, fun:(function anonymous() {allElements[8].style.display = "-moz-grid";})},53{origCount:39, fun:(function anonymous() {allElements[9].style.color = "black";})},54{origCount:40, fun:(function anonymous() {allElements[4].style.position = "static";})},55{origCount:41, fun:(function anonymous() {allElements[10].style.height = "auto";})},56{origCount:42, fun:(function anonymous() {allElements[9].style.color = "green";})},57{origCount:43, fun:(function anonymous() {allElements[4].style.height = "auto";})},58{origCount:44, fun:(function anonymous() {allElements[2].style.clear = "both";})},59{origCount:45, fun:(function anonymous() {allElements[8].style.width = "1px";})},60{origCount:46, fun:(function anonymous() {allElements[2].style.visibility = "visible";})},61{origCount:47, fun:(function anonymous() {allElements[1].style.clear = "left";})},62{origCount:48, fun:(function anonymous() {allElements[11].style.overflow = "auto";})},63{origCount:49, fun:(function anonymous() {allElements[11].style['float'] = "left";})},64{origCount:50, fun:(function anonymous() {allElements[8].style['float'] = "left";})},65{origCount:51, fun:(function anonymous() {allElements[6].style.height = "10%";})},66{origCount:52, fun:(function anonymous() {allElements[11].style.display = "-moz-inline-box";})},67{origCount:53, fun:(function anonymous() {allElements[3].style.clear = "left";})},68{origCount:54, fun:(function anonymous() {allElements[11].style.visibility = "hidden";})},69{origCount:55, fun:(function anonymous() {allElements[4].style['float'] = "right";})},70{origCount:56, fun:(function anonymous() {allElements[0].style.width = "1px";})},71{origCount:57, fun:(function anonymous() {allElements[3].style.height = "200%";})},72{origCount:58, fun:(function anonymous() {allElements[7].style.height = "10%";})},73{origCount:59, fun:(function anonymous() {allElements[4].style.clear = "none";})},74{origCount:60, fun:(function anonymous() {allElements[11].style['float'] = "none";})},75{origCount:61, fun:(function anonymous() {allElements[9].style['float'] = "left";})},76{origCount:62, fun:(function anonymous() {allElements[4].style.overflow = "scroll";})},77{origCount:63, fun:(function anonymous() {allElements[12].style.height = "200%";})},78{origCount:64, fun:(function anonymous() {allElements[2].style.color = "green";})},79{origCount:65, fun:(function anonymous() {allElements[3].style['float'] = "none";})},80{origCount:66, fun:(function anonymous() {allElements[10].style.background = "transparent";})},81{origCount:67, fun:(function anonymous() {allElements[0].style.height = "auto";})},82{origCount:68, fun:(function anonymous() {allElements[6].style.clear = "left";})},83{origCount:69, fun:(function anonymous() {allElements[7].style.background = "url(http://www.google.com/images/logo_sm.gif)";})},84{origCount:70, fun:(function anonymous() {allElements[8].style.display = "-moz-popup";})},85{origCount:71, fun:(function anonymous() {allElements[2].style.height = "10%";})},86{origCount:72, fun:(function anonymous() {allElements[7].style.display = "table-cell";})},87{origCount:73, fun:(function anonymous() {allElements[3].style.background = "url(http://www.google.com/images/logo_sm.gif)";})},88{origCount:74, fun:(function anonymous() {allElements[8].style.color = "red";})},89{origCount:75, fun:(function anonymous() {allElements[1].style.overflow = "auto";})},90{origCount:76, fun:(function anonymous() {allElements[1].style.background = "#fcd";})},91{origCount:77, fun:(function anonymous() {allElements[0].style.color = "red";})},92{origCount:78, fun:(function anonymous() {allElements[4].style.background = "#fcd";})},93{origCount:79, fun:(function anonymous() {allElements[5].style.position = "static";})},94{origCount:80, fun:(function anonymous() {allElements[8].style.clear = "both";})},95{origCount:81, fun:(function anonymous() {allElements[7].style.clear = "both";})},96{origCount:82, fun:(function anonymous() {allElements[5].style.clear = "both";})},97{origCount:83, fun:(function anonymous() {allElements[10].style.display = "-moz-grid-group";})},98{origCount:84, fun:(function anonymous() {allElements[12].style.clear = "right";})},99{origCount:85, fun:(function anonymous() 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login.component.ts

Source:login.component.ts

1import { Component, QueryList, ViewChildren } from '@angular/core';2import {3 Auth,4 GoogleAuthProvider,5 signInAnonymously,6 signInWithPopup,7} from '@angular/fire/auth';8import { MatSnackBar } from '@angular/material/snack-bar';9import { Title } from '@angular/platform-browser';10import { Router } from '@angular/router';11import { Sentence } from 'functions/src/shared/types';12import { SentenceViewComponent } from '../read/sentence_view/sentence_view.component';13declare function gtag(a: string, b: string, c: any): any;14@Component({15 selector: 'app-login',16 templateUrl: './login.component.html',17 styleUrls: ['./login.component.scss'],18})19export class LoginComponent {20 sentences: Sentence[] = SampleSentences;21 @ViewChildren(SentenceViewComponent)22 sentenceViews: QueryList<SentenceViewComponent>;23 constructor(24 private auth: Auth,25 private router: Router,26 private snackBar: MatSnackBar,27 private titleService: Title28 ) {29 titleService.setTitle("Kani Reader Login");30 }31 login() {32 const provider = new GoogleAuthProvider();33 signInWithPopup(this.auth, provider)34 .then(() => {35 this.router.navigateByUrl('/home');36 gtag('event', 'conversion', { 'send_to': 'AW-1056918717/SVI0CIa1tZYDEL2Z_fcD' });37 })38 .catch((error) => {39 // Handle Errors here.40 const errorCode = error.code;41 const errorMessage = error.message;42 this.snackBar.open(43 'There was an error, please refresh. ' + error.code,44 '',45 { duration: 3000 }46 );47 });48 }49 loginAnonymously() {50 signInAnonymously(this.auth)51 .then(() => {52 this.router.navigateByUrl('/home');53 gtag('event', 'conversion', { 'send_to': 'AW-1056918717/SVI0CIa1tZYDEL2Z_fcD' });54 })55 .catch((error) => {56 const errorCode = error.code;57 const errorMessage = error.message;58 this.snackBar.open(59 'There was an error, please refresh. ' + error.code,60 '',61 { duration: 3000 }62 );63 });64 }65 select(sentence: Sentence) {66 this.sentenceViews.forEach((view) => {67 view.active = view.sentence === sentence;68 });69 }70}71const SampleSentences: Sentence[] = [72 {73 japanese: '「機動戦士ガンダム」は日本の有名なアニメです。',74 english: '"Mobile Suit Gundam" is a famous Japanese anime.',75 words: [76 {77 orig: '「',78 },79 {80 orig: '機動',81 dict: '機動',82 read: 'きどう',83 def: 'maneuver (usu. of military force)',84 kanji: [85 {86 kanji: '機',87 wkLevel: 20,88 wkDef: 'Machine',89 wkid: 1090,90 wkPron: 'き',91 jmDef:92 'loom, mechanism, machine, airplane, opportunity, potency, efficacy, occasion',93 jmOn: 'キ、 はた',94 },95 {96 kanji: '動',97 wkLevel: 12,98 wkDef: 'Move',99 wkid: 827,100 wkPron: 'どう',101 jmDef: 'move, motion, change, confusion, shift, shake',102 jmOn: 'ドウ、 うご.く、 うご.かす',103 },104 ],105 wkKanji: 20,106 },107 {108 orig: '戦士',109 dict: '戦士',110 read: 'せんし',111 def: 'soldier',112 kanji: [113 {114 kanji: '戦',115 wkLevel: 11,116 wkDef: 'War',117 wkid: 803,118 wkPron: 'せん',119 jmDef: 'war, battle, match',120 jmOn: 'セン、 いくさ、 たたか.う、 おのの.く、 そよ.ぐ、 わなな.く',121 },122 {123 kanji: '士',124 wkLevel: 13,125 wkDef: 'Samurai',126 wkid: 877,127 wkPron: 'し',128 jmDef: 'gentleman, scholar, samurai, samurai radical (no. 33)',129 jmOn: 'シ、 さむらい',130 },131 ],132 wkKanji: 13,133 },134 {135 orig: 'ガン',136 },137 {138 orig: 'ダム',139 },140 {141 orig: '」',142 },143 {144 orig: 'は',145 },146 {147 orig: '日本',148 dict: '日本',149 read: 'にっぽん',150 wk: '日本',151 wkid: 2570,152 wkRead: 'にほん',153 wkDef: 'Japan',154 wkLevel: 2,155 jlpt: 3,156 def: 'Japan',157 kanji: [158 {159 kanji: '日',160 wkLevel: 2,161 wkDef: 'Sun',162 wkid: 476,163 wkPron: 'にち, じつ',164 jmDef: 'day, sun, Japan, counter for days',165 jmOn: 'ニチ、 ジツ、 ひ、 -び、 -か',166 },167 {168 kanji: '本',169 wkLevel: 2,170 wkDef: 'Book',171 wkid: 487,172 wkPron: 'ほん',173 jmDef:174 'book, present, main, origin, true, real, counter for long cylindrical things',175 jmOn: 'ホン、 もと',176 },177 ],178 wkKanji: 2,179 },180 {181 orig: 'の',182 },183 {184 orig: '有名',185 dict: '有名',186 read: 'ゆうめい',187 wk: '有名',188 wkid: 2869,189 wkRead: 'ゆうめい',190 wkDef: 'Famous',191 wkLevel: 6,192 jlpt: 5,193 def: 'famous',194 kanji: [195 {196 kanji: '有',197 wkLevel: 6,198 wkDef: 'Have',199 wkid: 615,200 wkPron: 'ゆう, う',201 jmDef: 'possess, have, exist, happen, occur, approx',202 jmOn: 'ユウ、 ウ、 あ.る',203 },204 {205 kanji: '名',206 wkLevel: 4,207 wkDef: 'Name',208 wkid: 544,209 wkPron: 'めい, みょう',210 jmDef: 'name, noted, distinguished, reputation',211 jmOn: 'メイ、 ミョウ、 な、 -な',212 },213 ],214 wkKanji: 6,215 },216 {217 orig: 'な',218 },219 {220 orig: 'アニメ',221 },222 {223 orig: 'です',224 },225 {226 orig: '。',227 },228 ],229 level: 6,230 wkWord: '有名',231 },232 {233 japanese:234 'このアニメの主人公、アムロが乗って戦った「νガンダム」の像が福岡市にできます。',235 english:236 'A statue of "ν Gundam", in which Amuro, the main character of this animation, fought on board, can be created in Fukuoka City.',237 words: [238 {239 orig: 'この',240 },241 {242 orig: 'アニメ',243 },244 {245 orig: 'の',246 },247 {248 orig: '主人公',249 dict: '主人公',250 read: 'しゅじんこう',251 jlpt: 1,252 def: 'protagonist',253 kanji: [254 {255 kanji: '主',256 wkLevel: 4,257 wkDef: 'Master',258 wkid: 528,259 wkPron: 'しゅ',260 jmDef: 'lord, chief, master, main thing, principal',261 jmOn: 'シュ、 ス、 シュウ、 ぬし、 おも、 あるじ',262 },263 {264 kanji: '人',265 wkLevel: 1,266 wkDef: 'Person',267 wkid: 444,268 wkPron: 'にん, じん',269 jmDef: 'person',270 jmOn: 'ジン、 ニン、 ひと、 -り、 -と',271 },272 {273 kanji: '公',274 wkLevel: 3,275 wkDef: 'Public',276 wkid: 499,277 wkPron: 'こう',278 jmDef: 'public, prince, official, governmental',279 jmOn: 'コウ、 ク、 おおやけ',280 },281 ],282 wkKanji: 4,283 },284 {285 orig: '、',286 },287 {288 orig: 'アムロ',289 },290 {291 orig: 'が',292 },293 {294 orig: '乗っ',295 dict: '乗る',296 read: 'のっ',297 wk: '乗る',298 wkid: 3112,299 wkRead: 'のる',300 wkDef: 'To Ride',301 wkLevel: 9,302 jlpt: 5,303 def: 'power',304 kanji: [305 {306 kanji: '乗',307 wkLevel: 9,308 wkDef: 'Ride',309 wkid: 722,310 wkPron: 'の',311 jmDef:312 'ride, power, multiplication, record, counter for vehicles, board, mount, join',313 jmOn: 'ジョウ、 ショウ、 の.る、 -の.り、 の.せる',314 },315 ],316 wkKanji: 9,317 },318 {319 orig: 'て',320 },321 {322 orig: '戦っ',323 dict: '戦う',324 read: 'たたかっ',325 wk: '戦う',326 wkid: 3578,327 wkRead: 'たたかう',328 wkDef: 'To Fight',329 wkLevel: 13,330 jlpt: 3,331 def: 'war',332 kanji: [333 {334 kanji: '戦',335 wkLevel: 11,336 wkDef: 'War',337 wkid: 803,338 wkPron: 'せん',339 jmDef: 'war, battle, match',340 jmOn: 'セン、 いくさ、 たたか.う、 おのの.く、 そよ.ぐ、 わなな.く',341 },342 ],343 wkKanji: 11,344 },345 {346 orig: 'た',347 },348 {349 orig: '「',350 },351 {352 orig: 'ν',353 },354 {355 orig: 'ガン',356 },357 {358 orig: 'ダム',359 },360 {361 orig: '」',362 },363 {364 orig: 'の',365 },366 {367 orig: '像',368 dict: '像',369 read: 'ぞう',370 jlpt: 1,371 def: 'image',372 kanji: [373 {374 kanji: '像',375 wkLevel: 13,376 wkDef: 'Statue',377 wkid: 890,378 wkPron: 'ぞう',379 jmDef: 'statue, picture, image, figure, portrait',380 jmOn: 'ゾウ',381 },382 ],383 wkKanji: 13,384 },385 {386 orig: 'が',387 },388 {389 orig: '福岡',390 dict: '福岡',391 read: 'ふくおか',392 def: 'Fukuoka (city, prefecture)',393 kanji: [394 {395 kanji: '福',396 wkLevel: 13,397 wkDef: 'Luck',398 wkid: 867,399 wkPron: 'ふく',400 jmDef: 'blessing, fortune, luck, wealth',401 jmOn: 'フク',402 },403 {404 kanji: '岡',405 wkLevel: 21,406 wkDef: 'Hill',407 wkid: 1137,408 wkPron: 'おか',409 jmDef: 'mount, hill, knoll',410 jmOn: 'コウ、 おか',411 },412 ],413 wkKanji: 21,414 },415 {416 orig: '市',417 dict: '市',418 read: 'し',419 wk: '市',420 wkid: 2635,421 wkRead: 'し',422 wkDef: 'City',423 wkLevel: 3,424 jlpt: 4,425 def: 'market',426 kanji: [427 {428 kanji: '市',429 wkLevel: 3,430 wkDef: 'City',431 wkid: 522,432 wkPron: 'し',433 jmDef: 'market, city, town',434 jmOn: 'シ、 いち',435 },436 ],437 wkKanji: 3,438 },439 {440 orig: 'に',441 },442 {443 orig: 'でき',444 },445 {446 orig: 'ます',447 },448 {449 orig: '。',450 },451 ],452 level: 13,453 wkWord: '戦う',454 },455 {456 japanese: '像の高さはアニメとだいたい同じ25mぐらいで、重さは80tです。',457 english:458 'The height of the statue is about 25m, which is about the same as the animation, and the weight is 80t.',459 words: [460 {461 orig: '像',462 dict: '像',463 read: 'ぞう',464 jlpt: 1,465 def: 'image',466 kanji: [467 {468 kanji: '像',469 wkLevel: 13,470 wkDef: 'Statue',471 wkid: 890,472 wkPron: 'ぞう',473 jmDef: 'statue, picture, image, figure, portrait',474 jmOn: 'ゾウ',475 },476 ],477 wkKanji: 13,478 },479 {480 orig: 'の',481 },482 {483 orig: '高',484 dict: '高い',485 read: 'たか',486 wk: '高い',487 wkid: 2968,488 wkRead: 'たかい',489 wkDef: 'Tall',490 wkLevel: 7,491 jlpt: 5,492 def: 'high',493 kanji: [494 {495 kanji: '高',496 wkLevel: 7,497 wkDef: 'Tall',498 wkid: 666,499 wkPron: 'こう',500 jmDef: 'tall, high, expensive',501 jmOn: 'コウ、 たか.い、 たか、 -だか、 たか.まる、 たか.める',502 },503 ],504 wkKanji: 7,505 },506 {507 orig: 'さ',508 },509 {510 orig: 'は',511 },512 {513 orig: 'アニメ',514 },515 {516 orig: 'と',517 },518 {519 orig: 'だいたい',520 },521 {522 orig: '同じ',523 dict: '同じ',524 read: 'おなじ',525 wk: '同じ',526 wkid: 2747,527 wkRead: 'おなじ',528 wkDef: 'Same',529 wkLevel: 5,530 jlpt: 5,531 def: 'same',532 kanji: [533 {534 kanji: '同',535 wkLevel: 5,536 wkDef: 'Same',537 wkid: 568,538 wkPron: 'どう',539 jmDef: 'same, agree, equal',540 jmOn: 'ドウ、 おな.じ',541 },542 ],543 wkKanji: 5,544 },545 {546 orig: '25',547 },548 {549 orig: 'm',550 },551 {552 orig: 'ぐらい',553 },554 {555 orig: 'で',556 },557 {558 orig: '、',559 },560 {561 orig: '重',562 dict: '重い',563 read: 'おも',564 wk: '重い',565 wkid: 3150,566 wkRead: 'おもい',567 wkDef: 'Heavy',568 wkLevel: 9,569 jlpt: 5,570 def: '-fold',571 kanji: [572 {573 kanji: '重',574 wkLevel: 9,575 wkDef: 'Heavy',576 wkid: 735,577 wkPron: 'じゅう',578 jmDef:579 'heavy, important, esteem, respect, heap up, pile up, nest of boxes, -fold',580 jmOn: 'ジュウ、 チョウ、 え、 おも.い、 おも.り、 おも.なう、 かさ.ねる、 かさ.なる、 おも',581 },582 ],583 wkKanji: 9,584 },585 {586 orig: 'さ',587 },588 {589 orig: 'は',590 },591 {592 orig: '80',593 },594 {595 orig: 't',596 },597 {598 orig: 'です',599 },600 {601 orig: '。',602 },603 ],604 level: 9,605 wkWord: '重い',606 },...

_tensor_grad.py

Source:_tensor_grad.py

1# Licensed to the Apache Software Foundation (ASF) under one2# or more contributor license agreements. See the NOTICE file3# distributed with this work for additional information4# regarding copyright ownership. The ASF licenses this file5# to you under the Apache License, Version 2.0 (the6# "License"); you may not use this file except in compliance7# with the License. You may obtain a copy of the License at8#9# http://www.apache.org/licenses/LICENSE-2.010#11# Unless required by applicable law or agreed to in writing,12# software distributed under the License is distributed on an13# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY14# KIND, either express or implied. See the License for the15# specific language governing permissions and limitations16# under the License.17#pylint: disable=invalid-name, unused-argument18"""Backend compiler related feature registration"""19from __future__ import absolute_import20from topi.nn.util import get_pad_tuple21from topi.util import get_const_tuple22from ..expr import Tuple, TupleGetItem, const23from . import nn as _nn24from .op import register_gradient25from .reduce import sum as _sum26from .tensor import (27 cos,28 exp,29 less,30 negative,31 ones_like,32 power,33 sin,34 zeros_like,35 equal,36 shape_of,37 log)38from .transform import (39 broadcast_to_like,40 collapse_sum_like,41 cast_like,42 reshape,43 reshape_like,44 strided_slice,45 take,46 tile,47 transpose,48 where,49 repeat,50 expand_dims,51 full_like52)53@register_gradient("log")54def log_grad(orig, grad):55 """Returns [grad * (1 / x)]"""56 x = orig.args[0]57 return [grad * ones_like(x) / x]58@register_gradient("tan")59def tan_grad(orig, grad):60 """Returns [grad / (cos^2(x))]"""61 x = orig.args[0]62 return [grad / (cos(x) * cos(x))]63@register_gradient("cos")64def cos_grad(orig, grad):65 """Returns [grad * (-sin(x))]"""66 x = orig.args[0]67 ones = ones_like(x)68 return [grad * (-ones * sin(x))]69@register_gradient("sin")70def sin_grad(orig, grad):71 """Returns [grad * cos(x)]"""72 x = orig.args[0]73 return [grad * cos(x)]74@register_gradient("atan")75def atan_grad(orig, grad):76 """Returns [grad * 1 / (1 + x ^ 2)]"""77 x = orig.args[0]78 a = const(2.0)79 return [grad * ones_like(x) / (ones_like(x) + power(x, a))]80@register_gradient("exp")81def exp_grad(orig, grad):82 """Returns [grad * exp(x)]"""83 return [grad * exp(orig.args[0])]84@register_gradient("sqrt")85def sqrt_grad(orig, grad):86 """Returns [grad * 0.5 * (x ^ -0.5)]"""87 a = const(0.5) # (TODO) type?88 return [grad * a * power(orig.args[0], negative(a))]89@register_gradient("sigmoid")90def sigmoid_grad(orig, grad):91 """Returns [grad * sigmoid(x) * (1 - sigmoid(x))]."""92 return [grad * orig * (ones_like(orig) - orig)]93@register_gradient("tanh")94def tanh_grad(orig, grad):95 """Returns grad * (1 - tanh(x) * tanh(x))."""96 return [grad * ones_like(orig) - orig * orig]97@register_gradient("nn.relu")98def relu_grad(orig, grad):99 """Returns grad * (select(x < 0, 0, 1))."""100 x = orig.args[0]101 zeros = zeros_like(x)102 ones = ones_like(x)103 return [where(less(x, zeros), zeros, ones * grad)]104@register_gradient("add")105def add_grad(orig, grad):106 """Returns [grad, grad]"""107 return [collapse_sum_like(grad, orig.args[0]),108 collapse_sum_like(grad, orig.args[1])]109@register_gradient("subtract")110def subtract_grad(orig, grad):111 """Returns [grad, -grad]"""112 return [collapse_sum_like(grad, orig.args[0]),113 collapse_sum_like(negative(grad), orig.args[1])]114@register_gradient("multiply")115def multiply_grad(orig, grad):116 """Returns [grad * y, grad * x]"""117 x, y = orig.args118 return [collapse_sum_like(grad * y, x),119 collapse_sum_like(grad * x, y)]120@register_gradient("divide")121def divide_grad(orig, grad):122 """Returns [grad / y, - grad * (x / y) / y]"""123 x, y = orig.args124 return [collapse_sum_like(grad / y, x),125 collapse_sum_like(- (grad * orig / y), y)]126@register_gradient("zeros")127def zeros_grad(orig, grad):128 """Returns []"""129 return []130@register_gradient("ones")131def ones_grad(orig, grad):132 """Returns []"""133 return []134@register_gradient("zeros_like")135def zeros_like_grad(orig, grad):136 """Returns [0]"""137 return [orig]138@register_gradient("ones_like")139def ones_like_grad(orig, grad):140 """Returns [0]"""141 return [zeros_like(orig.args[0])]142@register_gradient("collapse_sum_like")143def collapse_sum_like_grad(orig, grad):144 """Returns [broadcast_to_like(grad, x), 0]"""145 x, y = orig.args146 return [broadcast_to_like(grad, x), zeros_like(y)]147@register_gradient("abs")148def abs_grad(orig, grad):149 """Returns grad * (select(x < 0, -1, 1))."""150 x = orig.args[0]151 zeros = zeros_like(x)152 ones = ones_like(x)153 return [where(less(x, zeros), -ones * grad, ones * grad)]154@register_gradient("clip")155def clip_grad(orig, grad):156 """Returns grad * (select(x < min || max < x , 0, 1))."""157 x = orig.args[0]158 a_min = orig.attrs.get_int("a_min")159 a_max = orig.attrs.get_int("a_max")160 a_mins = broadcast_to_like(const(a_min), x)161 a_maxs = broadcast_to_like(const(a_max), x)162 zeros = zeros_like(x)163 ones = ones_like(x)164 return [where(less(x, a_mins), zeros, where(less(a_maxs, x), zeros, ones * grad))]165@register_gradient("nn.max_pool2d")166def max_pool2d_grad(orig, grad):167 """Returns the gradient of max_pool2d."""168 attrs = orig.attrs169 pool_grad = _nn.max_pool2d_grad(grad, orig.args[0], pool_size=attrs.pool_size,170 strides=attrs.strides, padding=attrs.padding,171 layout=attrs.layout, ceil_mode=attrs.ceil_mode)172 return [pool_grad]173@register_gradient("nn.avg_pool2d")174def avg_pool2d_grad(orig, grad):175 """Returns the gradient of avg_pool2d."""176 attrs = orig.attrs177 pool_grad = _nn.avg_pool2d_grad(grad, orig.args[0], pool_size=attrs.pool_size,178 strides=attrs.strides, padding=attrs.padding,179 layout=attrs.layout, ceil_mode=attrs.ceil_mode,180 count_include_pad=attrs.count_include_pad)181 return [pool_grad]182@register_gradient("nn.global_avg_pool2d")183def global_avg_pool2d_grad(orig, grad):184 """Returns the gradient of global_avg_pool2d."""185 data = orig.args[0]186 shape = data.checked_type.shape187 layout = orig.attrs.layout188 # we assume NCHW or NHWC layout for now, but easy to add more189 assert layout in ["NCHW", "NHWC"]190 if layout == "NCHW":191 pool_size = shape[2], shape[3]192 elif layout == "NHWC":193 pool_size = shape[1], shape[2]194 pool_grad = _nn.avg_pool2d_grad(grad, data, pool_size=pool_size,195 strides=(1, 1), padding=(0, 0),196 layout=layout)197 return [pool_grad]198# not implemented, this is only for testing.199@register_gradient("concatenate")200def concatenate_grad(orig, grad):201 assert len(orig.args) == 1202 t = orig.args[0]203 x = TupleGetItem(t, 0)204 y = TupleGetItem(t, 1)205 # Assume only two element in tuple rn.206 # In the real implementation, concatenate_grad probably need to be implemented by an operator.207 return [Tuple([zeros_like(x), zeros_like(y)])]208@register_gradient("nn.conv2d")209def conv2d_grad(orig, grad):210 """Gradient of conv2d"""211 attrs = orig.attrs212 data, weight = orig.args213 data_shape = get_const_tuple(data.checked_type.shape)214 weight_shape = get_const_tuple(weight.checked_type.shape)215 _, _, grad_h, grad_w = get_const_tuple(orig.checked_type.shape)216 batch, in_channel, in_h, in_w = data_shape217 out_channel, _, filter_h, filter_w = weight_shape218 # infer output_padding219 fpad_top, fpad_left, fpad_bottom, fpad_right = get_pad_tuple(get_const_tuple(attrs.padding),220 (filter_h, filter_w))221 stride_h, stride_w = get_const_tuple(attrs.strides)222 dilation_h, dilation_w = get_const_tuple(attrs.dilation)223 out_h = (grad_h - 1) * stride_h - fpad_top - fpad_bottom + filter_h224 out_w = (grad_w - 1) * stride_w - fpad_left - fpad_right + filter_w225 output_padding = (in_h - out_h, in_w - out_w)226 assert attrs.data_layout == 'NCHW', 'only support NCHW data layout'227 assert attrs.kernel_layout == 'OIHW', 'only support OIHW kernel layout'228 assert attrs.out_layout in ['', 'NCHW'], 'only support NCHW output layout'229 backward_data = _nn.conv2d_transpose(grad, weight,230 strides=attrs.strides,231 padding=attrs.padding,232 dilation=attrs.dilation,233 groups=attrs.groups,234 output_padding=output_padding)235 grad = tile(grad, [1, in_channel // attrs.groups, 1, 1])236 grad = reshape(grad, [-1, 1, 0, 0]) # batch * oc * ic // groups, 1, oh, ow237 data = reshape(data, [1, -1, 0, 0]) # 1, batch * ic, ih, iw238 backward_weight = _nn.conv2d(data, grad,239 strides=attrs.dilation,240 padding=attrs.padding,241 dilation=attrs.strides,242 groups=in_channel * batch)243 # infer shape of backward_weight244 padded_weight_grad_h = (in_h - (grad_h - 1) * stride_h - 1 + fpad_top + fpad_bottom) \245 // dilation_h + 1246 padded_weight_grad_w = (in_w - (grad_w - 1) * stride_w - 1 + fpad_left + fpad_right) \247 // dilation_w + 1248 backward_weight = reshape(backward_weight,249 [batch, in_channel // attrs.groups, out_channel,250 padded_weight_grad_h, padded_weight_grad_w])251 backward_weight = _sum(backward_weight, axis=0)252 backward_weight = transpose(backward_weight, [1, 0, 2, 3])253 assert padded_weight_grad_h >= filter_h254 assert padded_weight_grad_w >= filter_w255 if padded_weight_grad_h > filter_h or padded_weight_grad_w > filter_w:256 backward_weight = strided_slice(backward_weight, begin=[0, 0, 0, 0],257 end=[None, None, filter_h, filter_w])258 return [backward_data, backward_weight]259def _get_reduce_axis(call):260 """Helper function that returns the reduce axis of the call as plain python ints."""261 x, axis = call.args[0], call.attrs.axis262 shape = x.checked_type.concrete_shape263 # should never exclude when axis is None264 assert not (axis is None and call.attrs.exclude)265 if axis is None:266 return None267 # convert to nonnegative integers and sort268 axis = sorted([ax if ax >= 0 else len(shape) + ax for ax in map(int, axis)])269 if call.attrs.exclude:270 axis = [ax for ax in range(len(shape)) if ax not in axis]271 return axis272def _unreduce_expand(x, axis):273 """Helper function that returns x expanded on the reduced dimensions in axis."""274 # assume axis is sorted nonnegative ints275 for ax in axis:276 x = expand_dims(x, ax)277 return x278@register_gradient("max")279def max_grad(orig, grad):280 """Returns the gradient of max"""281 x, axis = orig.args[0], _get_reduce_axis(orig)282 shape = x.checked_type.concrete_shape283 repeated = orig284 if axis is None:285 repeated = full_like(x, repeated)286 else:287 # expand dims (if necessary) and repeat along each axis288 if not orig.attrs.keepdims:289 repeated = _unreduce_expand(repeated, axis)290 grad = _unreduce_expand(grad, axis)291 for ax in axis:292 repeated = repeat(repeated, shape[ax], ax)293 indicators = cast_like(equal(repeated, x), grad)294 num_selected = _sum(indicators, axis, keepdims=True)295 # spread error across all max weights296 return [indicators * grad / num_selected]297@register_gradient("nn.softmax")298def softmax_grad(orig, grad):299 """Gradient of softmax"""300 return [(grad - _sum(grad * orig, orig.attrs.axis, True)) * orig]301@register_gradient("nn.log_softmax")302def log_softmax_grad(orig, grad):303 """Gradient of log_softmax"""304 x = orig.args[0]305 sm = _nn.softmax(x, axis=orig.attrs.axis)306 grad = grad / sm307 return softmax_grad(sm, grad)308@register_gradient("nn.bias_add")309def bias_add_grad(orig, grad):310 """Returns gradient of bias_add"""311 data = orig.args[0]312 return [collapse_sum_like(grad, data),313 _sum(grad, orig.attrs.axis, keepdims=False, exclude=True)]314@register_gradient("nn.dense")315def dense_grad(orig, grad):316 """Returns [grad' @ weight, data @ grad']"""317 data, weight = orig.args318 return [collapse_sum_like(transpose(grad) * weight, data),319 collapse_sum_like(data * transpose(grad), weight)]320@register_gradient("reshape")321def reshape_grad(orig, grad):322 """Gradient of reshape"""323 return [reshape_like(grad, orig.args[0])]324@register_gradient("cast")325def cast_grad(orig, grad):326 x = orig.args[0]327 return [cast_like(grad, x)]328@register_gradient("nn.batch_flatten")329def batch_flatten_grad(orig, grad):330 """Returns grad reshaped to data dims"""331 data = orig.args[0]332 return [reshape_like(grad, data)]333@register_gradient("transpose")334def transpose_grad(orig, grad):335 """Returns grad transposed over the complement of original transpose axes"""336 orig_axes = orig.attrs.axes337 if orig_axes:338 dims = len(orig_axes)339 new_axes = [0] * dims340 for i in range(dims):341 new_axes[int(orig_axes[i])] = i342 else:343 new_axes = None344 return [transpose(grad, axes=new_axes)]345@register_gradient("negative")346def negative_grad(orig, grad):347 """Returns -grad"""348 return [-grad]349@register_gradient("sum")350def sum_grad(orig, grad):351 """Returns grad broadcasted to data dims"""352 data, axis = orig.args[0], _get_reduce_axis(orig)353 if not orig.attrs.keepdims:354 if axis is None:355 axis = list(range(len(data.checked_type.concrete_shape)))356 grad = _unreduce_expand(grad, axis)357 return [broadcast_to_like(grad, data)]358@register_gradient("nn.cross_entropy")359def cross_entropy_grad(orig, grad):360 x, y = orig.args361 shape = shape_of(x)362 batch_size = take(shape, const(0, dtype='int32'), axis=0)363 grad = grad / batch_size.astype('float32')364 return [-grad * y / x, -grad * log(x)]365@register_gradient("nn.cross_entropy_with_logits")366def cross_entropy_with_logits_grad(orig, grad):367 x, y = orig.args368 shape = shape_of(x)369 batch_size = take(shape, const(0, dtype='int32'), axis=0)370 grad = grad / batch_size.astype('float32')...

fs_utils.py

Source:fs_utils.py

1import sys2import shutil3import os4import pathlib5import magic6import tarfile7import subprocess8import time9from PIL import Image10from hachoir.parser import createParser11from hachoir.metadata import extractMetadata12from .exceptions import NotSupportedExtractionArchive13from bot import aria2, LOGGER, DOWNLOAD_DIR, get_client, TG_SPLIT_SIZE14VIDEO_SUFFIXES = ("M4V", "MP4", "MOV", "FLV", "WMV", "3GP", "MPG", "WEBM", "MKV", "AVI")15def clean_download(path: str):16 if os.path.exists(path):17 LOGGER.info(f"Cleaning Download: {path}")18 shutil.rmtree(path)19def start_cleanup():20 try:21 shutil.rmtree(DOWNLOAD_DIR)22 except FileNotFoundError:23 pass24def clean_all():25 aria2.remove_all(True)26 get_client().torrents_delete(torrent_hashes="all", delete_files=True)27 get_client().auth_log_out()28 try:29 shutil.rmtree(DOWNLOAD_DIR)30 except FileNotFoundError:31 pass32def exit_clean_up(signal, frame):33 try:34 LOGGER.info("Please wait, while we clean up the downloads and stop running downloads")35 clean_all()36 sys.exit(0)37 except KeyboardInterrupt:38 LOGGER.warning("Force Exiting before the cleanup finishes!")39 sys.exit(1)40def get_path_size(path):41 if os.path.isfile(path):42 return os.path.getsize(path)43 total_size = 044 for root, dirs, files in os.walk(path):45 for f in files:46 abs_path = os.path.join(root, f)47 total_size += os.path.getsize(abs_path)48 return total_size49def tar(org_path):50 tar_path = org_path + ".tar"51 path = pathlib.PurePath(org_path)52 LOGGER.info(f'Tar: orig_path: {org_path}, tar_path: {tar_path}')53 tar = tarfile.open(tar_path, "w")54 tar.add(org_path, arcname=path.name)55 tar.close()56 return tar_path57def get_base_name(orig_path: str):58 if orig_path.endswith(".tar.bz2"):59 return orig_path.replace(".tar.bz2", "")60 elif orig_path.endswith(".tar.gz"):61 return orig_path.replace(".tar.gz", "")62 elif orig_path.endswith(".bz2"):63 return orig_path.replace(".bz2", "")64 elif orig_path.endswith(".gz"):65 return orig_path.replace(".gz", "")66 elif orig_path.endswith(".tar.xz"):67 return orig_path.replace(".tar.xz", "")68 elif orig_path.endswith(".tar"):69 return orig_path.replace(".tar", "")70 elif orig_path.endswith(".tbz2"):71 return orig_path.replace("tbz2", "")72 elif orig_path.endswith(".tgz"):73 return orig_path.replace(".tgz", "")74 elif orig_path.endswith(".zip"):75 return orig_path.replace(".zip", "")76 elif orig_path.endswith(".7z"):77 return orig_path.replace(".7z", "")78 elif orig_path.endswith(".Z"):79 return orig_path.replace(".Z", "")80 elif orig_path.endswith(".rar"):81 return orig_path.replace(".rar", "")82 elif orig_path.endswith(".iso"):83 return orig_path.replace(".iso", "")84 elif orig_path.endswith(".wim"):85 return orig_path.replace(".wim", "")86 elif orig_path.endswith(".cab"):87 return orig_path.replace(".cab", "")88 elif orig_path.endswith(".apm"):89 return orig_path.replace(".apm", "")90 elif orig_path.endswith(".arj"):91 return orig_path.replace(".arj", "")92 elif orig_path.endswith(".chm"):93 return orig_path.replace(".chm", "")94 elif orig_path.endswith(".cpio"):95 return orig_path.replace(".cpio", "")96 elif orig_path.endswith(".cramfs"):97 return orig_path.replace(".cramfs", "")98 elif orig_path.endswith(".deb"):99 return orig_path.replace(".deb", "")100 elif orig_path.endswith(".dmg"):101 return orig_path.replace(".dmg", "")102 elif orig_path.endswith(".fat"):103 return orig_path.replace(".fat", "")104 elif orig_path.endswith(".hfs"):105 return orig_path.replace(".hfs", "")106 elif orig_path.endswith(".lzh"):107 return orig_path.replace(".lzh", "")108 elif orig_path.endswith(".lzma"):109 return orig_path.replace(".lzma", "")110 elif orig_path.endswith(".lzma2"):111 return orig_path.replace(".lzma2", "")112 elif orig_path.endswith(".mbr"):113 return orig_path.replace(".mbr", "")114 elif orig_path.endswith(".msi"):115 return orig_path.replace(".msi", "")116 elif orig_path.endswith(".mslz"):117 return orig_path.replace(".mslz", "")118 elif orig_path.endswith(".nsis"):119 return orig_path.replace(".nsis", "")120 elif orig_path.endswith(".ntfs"):121 return orig_path.replace(".ntfs", "")122 elif orig_path.endswith(".rpm"):123 return orig_path.replace(".rpm", "")124 elif orig_path.endswith(".squashfs"):125 return orig_path.replace(".squashfs", "")126 elif orig_path.endswith(".udf"):127 return orig_path.replace(".udf", "")128 elif orig_path.endswith(".vhd"):129 return orig_path.replace(".vhd", "")130 elif orig_path.endswith(".xar"):131 return orig_path.replace(".xar", "")132 else:133 raise NotSupportedExtractionArchive('File format not supported for extraction')134def get_mime_type(file_path):135 mime = magic.Magic(mime=True)136 mime_type = mime.from_file(file_path)137 mime_type = mime_type or "text/plain"138 return mime_type139def take_ss(video_file):140 des_dir = 'Thumbnails'141 if not os.path.exists(des_dir):142 os.mkdir(des_dir)143 des_dir = os.path.join(des_dir, f"{time.time()}.jpg")144 metadata = extractMetadata(createParser(video_file))145 duration = metadata.get('duration').seconds if metadata.has("duration") else 5146 duration = int(duration) / 2147 subprocess.run(["ffmpeg", "-hide_banner", "-loglevel", "error", "-ss", str(duration),148 "-i", video_file, "-vframes", "1", des_dir])149 if not os.path.lexists(des_dir):150 return None151 Image.open(des_dir).convert("RGB").save(des_dir)152 img = Image.open(des_dir)153 img.resize((480, 320))154 img.save(des_dir, "JPEG")155 return des_dir156def split(path, size, file, dirpath, split_size, start_time=0, i=1):157 if file.upper().endswith(VIDEO_SUFFIXES):158 base_name, extension = os.path.splitext(file)159 metadata = extractMetadata(createParser(path))160 total_duration = metadata.get('duration').seconds - 8161 split_size = split_size - 3000000162 while start_time < total_duration:163 parted_name = "{}.part{}{}".format(str(base_name), str(i).zfill(3), str(extension))164 out_path = os.path.join(dirpath, parted_name)165 subprocess.run(["ffmpeg", "-hide_banner", "-loglevel", "error", "-i", 166 path, "-ss", str(start_time), "-fs", str(split_size),167 "-strict", "-2", "-c", "copy", out_path])168 out_size = get_path_size(out_path)169 if out_size > TG_SPLIT_SIZE:170 dif = out_size - TG_SPLIT_SIZE171 split_size = split_size - dif + 2000000172 os.remove(out_path)173 return split(path, size, file, dirpath, split_size, start_time, i)174 metadata = extractMetadata(createParser(out_path))175 start_time = start_time + metadata.get('duration').seconds - 5176 i = i + 1177 else:178 out_path = os.path.join(dirpath, file + ".")...

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