Tdarr gpu

I have 2 nodes running well and want to add my main workstation as a node. But you can benefit from all of them in some way, if it's worth the Tdarr can strip those unwanted streams from your content, saving you additional space. VolSync Backups and Restores on Helm Platforms. You'll be specifying the file path in the Tdarr preset that I'm going to provide, but the file must be accessible and readable from the Tdarr node. Had some path translation issues which I have now resolved but now I get… Share. 2 Crucial 1TB (Raid 1 VM), 2x SSD 860 EVO 500gb (Raid1 QTS), 2x SSD 860 EVO 250GB (Cache), 2x M. After tweaking video stream bitrate to find a happy balance between quality and file size, then setting Tdarr to utilize different bitrates according to resolution (e. Intel i5 8500T I got about 210-230 fps total with two worker threads but it heavily depended on the source media. Sophie: server, no GPU, many CPUs. An advanced "Transcode: GPU:" option, where the user could specify "Total GPU transcodes", and "Per GPU transcodes", and then the Tdarr node could control the '-gpu <N>' flag in a plugin, tracking which GPUs are currently transcoding. External Service. Remove any unneeded foreign audio and subs. I found VAAPI to be simpler and you will need Mesa 20. Hi, yes this is possible. Anyone got any pointers? Does your TDarr compose have the device /dev/dri line? I think you can GPU encoding works in example, but not as a node. I suspect it might just be tdarr, since when I use lxc console to install the intel GPU tools with apt install intel-gpu-tools, and then run intel_gpu_top, it works just fine, displaying GPU activity being done on my plex lxc. Info Use the Worker limit control buttons on each node to startup and maintain the specified number of Workers. Describe the solution you'd like Couple possible solutions: When non-Tdarr processes are detected on the node, the node should either: Padre-two. I have a 1060 with 3gb vram. This is important and counter intuitive: Set GPU instances not CPU! Your CPU's QSV engine is considered a GPU to Tdarr. QNAP + TDarr + GPU Transcodes. Getting Started Tdarr V2 is a cross-platform, distributed transcoding system that is broken up into multiple modules. - Use cross-platform Tdarr Nodes which work together with Tdarr Server to process your files - GPU and CPU workers - Audio and video library management - Folder watcher - Worker stall detector - Load balancing between libraries/drives - Use HandBrake or FFmpeg - Tested on a 1,000,000 file dummy library - Library stats So I got Tdarr running this week and started attacking my library. - Use cross-platform Tdarr Nodes which work together with Tdarr Server to process your files - GPU and CPU workers - Audio and video library management - Folder watcher - Worker stall detector - Load balancing between libraries/drives - Use HandBrake or FFmpeg - Tested on a 1,000,000 file dummy library - Library stats A GPU can only help with re-encoding video. Set up directories with your Media, and ensure your permissions are correct. In the node options panel on the Tdarr tab, specify the nvidia node as nvenc and the intel node as qsv. The GPU is properly passing-through and I have nvidia-container-toolkit installed as well. click on the worker and increase the CPU or GPU transcode numbers. Hi All I am using a node with an AMD GPU the RX Vega 64 to be exact and after encoding I am noticing significant delay in scrubbing and what I feel is significant quality degradation the plugin I am using is as follows. But encoding with the GPU still fails with " [hevc_nvenc @ 0x55fecc549500] No NVENC capable devices found". I set the permissions of both to 755. As far as I know the intel has an integrated GPU that also supports hardware encoding, this is called QuickSync or in short qsv. Yeah, I think that it will end up being some interaction between Tdarr and the Nvidia runtime for the Docker container that causes Nvidia to lose track of available devices thus reporting NO_CUDA_DEVICE. This is important and counter intuitive: Set the hardware encoding type to vaapi and not qsv. 4. I have installed TDarr on windows to try it out. I do have another container using the GPU could that be I am new to Tdarr. The gpu is one of the upgrades. I used 48 copies of the jellyfish-60-mbps-hd-h264. May 11, 2022 · Even if I use the tdarr docker container and use the docker commands to specify each gpu it still doesn't work. Does not matter whether I use it in container station, and make a tdarr docker. Unzip it. Using extra Tdarr Nodes on multiple machines to increase transcoding resources is Hello, i did a little research about Tdarr and basically followed the great video of spaceinvaderone to set up: Unraid Server which has the Server and a Node running on a Windows 10/11. 20K episodes 2K Movies. Handbrake decoding is only cpu and encode is gpu or cpu. tdarr UI: Node Options should be set to Any (nvenc,qsv,vappi). Holds all media and the shared tdarr_cache folder Tiko: desktop: has a GPU. I have the following: Earth:apt list| grep nvidia-container. 3 participants. The other option is to leverage a main feature of Tdarr (using nodes) and buy a SFF PC with at least an 8th gen Intel CPU so you can use Quick Sync (e. Modern NVENC has come a long way and is obviously much faster than CPU transcoding. It's 5GB though due to all the extra drivers/dependencies I installed so will need to work on trimming it down before merging it with the main container. CNPG Backups and Restores on Helm Platforms. After looking at other docker containers that have nvidia transcoding included by default. Apr 16, 2022 · Tdarr is a distributed transcoding system that runs on on Windows, Mac, Linux, Arm, Docker, and even Unraid. \*\* \*\*With my i7 11700K, I have it set to Transcode 3 GPU, Health Check 6 GPU\*\* Plugin: I had trouble with numerous available plugins except Boosh1's. The following command will be used depending on what Node Hardware type is set in the Node Options on the Tdarr tab. I have installed the tdarr node using docker and it connects and the permissions all seem right. I got it running the internal node ok, and select my p2000 gpu when creating the container (gpu resources assigned to container station in I've just started using Tdarr on Windows 10, and was wondering if there is a suggested plugin for x265 conversion. Install the container toolkit. Then use hevc_vaapi as your encoder with ffmpeg. 1 or higher, but it also gives you the option to convert any current audio to AAC also. Im looking for a gpu that can handle (3 4k streams) or (6 1080p . It does this using 'Tdarr Nodes' which connect with a central server and pick up tasks so you can put all your spare devices to use. For this part of our guide, we take for granted that you have more than one PC, and they can "see" each other through your local network. Although they won't be using it at the same time I want it to be able to do so. 3. And audio/remux only tasks, your main bottleneck will be your disk speeds. I tried installing Tdarr server and node on the laptop (without using docker) but I can't do transcoding using the nvidia card. Yes that's right, make a second node. Are there any settings I can be utilizing to stop Tdarr from drawing so much power from my system? Set up is as follows. Haveagitgat/tdarr is a docker container that allows you to transcode and optimize your media files using plugins and workers. I'm running on my Thelio desktop running Ubuntu 22. 265 conversions (nothing else done except for codec change) and it would do about 150fps or so each with 3 conversions happening. Modern GPU transcoding is inferior to CPU transcoding in quality and compression. Currently there is only 1 setting for the workers, which is shared for both CPU and GPU. I just use the GPU to do a full inspection of the file post encode. Thorough health check performance testing on Intel N100 mini-PC CPU/GPU. Apr 10, 2020 · Right now the only solution is to run 2 instances of tdarr , 1 doing CPU transcoding and 1 doing GPU transcoding. If on Linux/macOS it's best to run the packages from a terminal so you can see the output. Edit: solved, forgot to enable gpu in the stack and disable cpu. 265 The updated codec uses a more efficient method for processing information, resulting in preserved quality while reducing storage capacity for files by ~50%. Make sure to follow the qsv unraid setup guide: https Jul 3, 2019 · Tadarr in docker in Container station. Windows 10 Intel(R) Core(TM) i7-2600 CPU @ 3. if you set Oct 6, 2019 · for moving to another folder its eaiser to setup a new library since your rip folder is not the same as your other media folder even though the output folder is the same. You can not do VAAPI transcoding on Linux without Mesa 20. And example would be a 32core system with 1 Health Check GPU Does thorough health checks using GPU. You can search, filter and manage your files from a web interface, and use the docker command line to run and update the container. I have tdarr running in Docker GPU transcoding and I've been noticing ffmpeg is using ~20% CPU per transcode, this seems high to me, can anyone else weigh in if this is to be expected or if something isn't quite right? CPU is a Celeron G4900 which doesn't break a sweat with 10+ PLEX transcodes. nfs, mounts, and paths are listed at the bottom. The issue is that there are different generations of the gpu between cpu generations which can cause issues. Single box doing server and node. I wanted to know the ideal number of concurrent worker sessions on my Tdarr (2. I recently added my windows PC with a Nvidia 3070 GPU as a node for Tdarr. Mrbucket101. 1+. 1. I was suprised at the results I got from a file that was 60 mins, 1080p, h264 and 3. 2 PCIe 970 500gb NVME (Raid1 Plex and Emby server) We would like to show you a description here but the site won’t allow us. This is unfortunate and seemingly a huge lack of support. You can even import your settings file from Handbrake. Apr 26, 2022 · No milestone. json files (except for the pathTranslators as those can't be set through env vars). --Update--. Then add an nvenc and a qsv plugin to the plugin stack, like: Tdarr_Plugin_MC93_Migz1FFMPEG. 264 to h. NVENC transcoding is roughly 6 times faster than CPU transcoding but the quality is a bit worse so depends on your needs with the 1660. mkv". I have a large video file I'm retranscofing. It's the tdarr_worker! How do I limit the CPU? For the specific worker. mkv" -map 0 -c copy -c:v libx265 "C:\Transcode\output. If you plan on using multiple nodes to access the presets file, you can put it on the share drive. I am new to tdarr and am experimenting with cpu and gpu transcoding. No video transcoding. When I got to some 1080p stuff, it was around 250-400FPS and again didn’t matter if I was doing 2 transcodes or 10, the 400fps would get divided up between the active transcodes. And yes I'm excited I've been reading up on it all excited today and i wasn't able to get it to work! I really appreciate the help!! How about transcoding a media library with Tdarr or Unmanic and wanting it to not take forever? Or anything else. My question is, can Tdarr be configured to show the GPU stats (mem and %)? Thanks! Well, I was just going to have a look at the source code on github, but, to my surprise, it's closed May 9, 2022 · Get started using Tdarr transcode automation for free with this link: https://tdarr. HP 290-p0043w). I've done it using NVIDIA and Intel iGPU. crf: the lower it is the better the quality but larger the file size. 14. 1. I just set up tdarr to encode my media files and I want to use my GPU (GTX 980 Ti) for hwacceleration now I set runtime: nvidia and gave all capabilities etc. On my system: 1 GPU Transcode and 2 GPU Health Checks. Put your spare hardware to use with Tdarr Nodes for Windows, Linux (including Linux arm) and macOS. With the solution posted it should work with any of the vaapi transcoding plugins. " Tdarr_Plugin_075a_Transcode_Customisable. So you need to update the i965-va-drivers apt package to 2. Before I put the second Nvidia card and I had my onboard video enabled for quick sync and it was gpu0 where as my RTX 3060 was GPU 1. Tdarr V2 is a distributed transcoding system for automating media library transcode/remux management and making sure your files are exactly how you need them to be in terms of codecs/streams/containers and so on. I'm not familiar with multi-gpu Tdarr setups, but worst case scenario in case it doesn't work, you could add the 30 series to an otherwise low-end build and the GPU will still be 90% of the cost to building the 2nd machine to use as an additional node. I converted my video collection using Tdarr to h265 and saved over 700 GB of disk space. Make sure your compose file tells tdarr to use your gpu. I must be just having a brain fart, but I don't see where I'm supposed to configure the number of workers for my single node. Nvidia Container Toolkit. Here's a typical ffmpeg command. Background: Usually I'll just leave a It's going to be a costly endeavor, either costing time or hardware. 04. Development. Here is what my file looks like. In order to use The worker will skip the plugins it can’t do, so a GPU worker will go straight to the GPU plugin. Accesses all of Sophie's file via NFS shares. 265) and I wouldn't mind the addition of (AV1). Setting Low FFmpeg/HandBrake process priority to on tends to help this issue. Transcode Media from H. CPU use seems high for GPU transcoding. Sorry you're still having issues. 0) causing the output files to be horrible, super small with tiny bit rates. I’m not sure about running two nodes and designating one per card, but out of curiosity. Windows will run them from a terminal automatically. I dont really want to do anything else other than reduce the filesize. It would do 3 h. Video Transcode Customisable ". I have set it to use the GPU (A GTX 980), with 0 CPU cores. I've also set that GPU workers CAN do CPU tasks. 7, and have an Ubuntu VM running Docker. I set up two directories, one contains movie-type media, and the other contains show-type media. It didn’t matter if I had 3 GPU workers or 10, it was still the same “max fps” and then that got divided between the number of active transcodes. My tasks are audio/remux only. Getting multiple machines working together across a local network requires some configuration. The setup I've got is, the tdarr server is on my unraid where I have all my files, and the node is in my windows machine which has an RTX 2070 installed. All that toggle does is within Tdarr allow gpu workers to do cpu tasks, so you don’t have to mix workers and flood your staging area. All dockers freeze up and UI is unresponsive. I would like to see full support for AMD AMF and VAAPI added to ffmpeg and the docker container. I'm only doing a GPU x 2. I am having issues trying to get the GPU encoding working though, it looks like the GPU passthrough might Tdarr is just a fancy front end for ffmepg. I imagine that I could get a couple trans codes going without much trouble but that does not seem to be the case. Workers which are toggled 'Off' will finish their current item before closing down. It uses a server with one or more nodes to transcode videos into any format you like. To Reproduce. No problems all good. Open the Node Options. 2. I would not expect CPU usage to be this high per transcode, PLEX seems to be able to hardware transcode on this machine with about 5% CPU per transcode. Love tdarr Been using it for quite a while, saved many TB of space. Simply cut and paste the commands. CodeServer Addon. Sep 13, 2022 · The issue occurs when we are using long plugin lists and want one specific worker CPU or GPU to be the one getting started. I haven't found any plugins that will normalize the audio yet, but hopefully this gets you a good We would like to show you a description here but the site won’t allow us. codec_filter_code and codec_filter: you can It might not be a problem with your plugin setup If you are using Linux then you are best using AMF or VAAPI for doing HEVC with AMD GPU. Using GPU and iGPU (qsv) at the same time. 2160p @ 12. Was actually just troubleshooting some other issues tonight, but at least the iGPU is available. The main things I'm trying to get out of Tdarr, and what the above flow should do, is as follows: Reduce file size by converting all media to H265 MKV using NVENC. Now the rtx360 is gpu0 and the Quadro p2000 is gpu-1. I'm about 170+ files done out of 5,300 and it's getting about 2,200fps running 2 GPU transcodes at time. - Use cross-platform Tdarr Nodes which work together with Tdarr Server to process your files - GPU and CPU workers - Audio and video library management - Folder watcher - Worker stall detector - Load balancing between libraries/drives - Use HandBrake or FFmpeg - Tested on a 1,000,000 file dummy library - Library stats Run and Compose Run . Sophie runs as the tdarr server and runs tdarr_server and tdarr_node Tiko only runs tdarr_node. I know GPU transcoding isn’t the best but eh these aren’t important shows. No CPU for the transcoding or even the health check. 5 mbps), it is amazingly efficient compared to CPU, with the same end result. GPU activity is about 92-99%. For those of us with larger libraries of files, transcoding across multiple gpus without having to build multiple tdarr nodes would be great. Qnap TS-1277 1700 (48gb RAM) 8x10TB WD White,- Raid5, 2x M. Run /Tdarr_Updater (if on Linux/macOS you may need to give the file execution permissions by running chmod +x Tdarr_Updater) 2 Modules will be downloaded by the updater. (Meaning pulling the item from the queue and beginning the work) Example We want to at plugin 11 look at audio bi Adding Service. I would, for now recommend using this plugin. tdarr_aio Intel QSV (Quick Sync Video) GPU transcoding now possible. ago. Each Node can run multiple 'Tdarr Workers' in parallel to maximize the hardware usage % on that We would like to show you a description here but the site won’t allow us. Tdarr has been running for a few days, working hard to give me Configure a TDARR library. Tdarr may process the transcode using a "Transcode CPU" due to audio or subtitle elements in the video, but it is definitely utilizing the GPU for the video transcode. Tdarr works in a distributed manner where you can use multiple devices to process your library together. I encode my media (HVEC/h. NVidia GPUs are not being used. Make sure your nvidia drivers for your card is installed - nvidia-smi. I'm liking what I'm seeing. Nov 4, 2021 · When other applications use NVENC encoding while Tdarr is using NVEC, performance suffers on those other applications (notably Plex). Adding Storage. I gave up and run it in OMV under docker now. Run this command in the docker container console: apt install vainfo intel-media-va-driver-non-free. It has a RTX3090 as main GPU and an Intel i7-11700 CPU. This solved my issues getting Tdarr GPU encoding working on my 10th We would like to show you a description here but the site won’t allow us. I only have on worker running on the same windows machine as the server node. I find it works quiet well. If you cancel an item, the Worker will move onto the next item in the queue. GPU works. You can really fine tune which files get processed and which done. QSV should now work if you use the tdarr_aio qsv tag container. no underscores (just for the name section). I run all my raw blu-ray mkvs through the same 2 stage CPU encoding as normal. Configure a TDARR GPU worker. • 2 yr. I'm new to using Tdarr, just started today with it. I'm using Windows 10, Intel 11th gen i7, and Intel Arc A770 LE. Screenshots. You'll notice very little CPU usage on FFmpeg . No crazy options, just using Handbrakes "HQ 1080p30 Surround" preset. Encoding using AMD GPU. Mar 31, 2023 · It’s a bit tricky because the complexity of tdarr first time configuration… I ended using a plugin called “Boosh-transcode using QSV GPU &FFMPEG”, but that might be the reason that caused it problems until I installed the private intel drivers. Reply. If you have an Nvidia GPU on your system, you can use the hevc_nvenc to transcode 5-10 times faster, although note that the quality isn't quite as good as when using CPU based Jul 18, 2020 · The right params just need to be passed along: -hevc_amf in this case. But then your gpu cannot be used for QTS. I have tdarr running in the background 24/7. From what I have read ffmpeg prefers to use gpu0. Nope. I can assure you QSV works, I have a 10th & 11th gen working on windows & unraid respectively. Members Online Setting up Intel Arc a380 as GPU transcoder in unraid Docker tdarr if it behaved more like a GPU pipeline 36 stars 0 forks Branches Tags Activity. Setting up VPN. 0 using the focal distribution. What I'm looking for is a plugin that converts the original file as-is, so reducing the size, but keeping the original quality. mkv test file per round. I've just setup tdarr following some of spaceinvader one's great videos, and it seems to be working perfectl. May 6, 2022 · To transcode into hevc using FFmpeg, use the libx265 encoder, for example: ffmpeg -i "C:\Transcode\input. 01) server's internal node, so I did a bit of testing. 1 or higher to do HEVC with VAAPI. A high end dedicated GPU isn't required. its also a way to segment your data so see how your rip transcodes are doing. I have added a few pictures of my settings in the Transcode options tab. Hey all - just been setting up TDarr inside a container on my 653D and wondering if anyones already gone thru this? I have GPU based health checks working, but none of the transcodes seem to work (not even CPU based). js, you can rename it to something else but make sure you follow the naming format and change the id inside the plugin, settings are from line 20 - line 27. Or various other unspecified use cases that this GPU might excel at? A GPU isn't required. Set GPU instances, not CPU. Place the presets file somewhere the Tdarr node can see it. If you're using the unraid server for Plex, then obviously adding the dedicated GPU has the advantage of being used for tdarr not using GPU. . However, that's a bit more complicated to set up. Star Notifications You must be signed in to change notification settings. You can run Tdarr using only a single machine. i got a dockerized tdarr and tdarr-node running on a machine that has a GPU with h264 (but no hevc) encoding. It’s still perfectly fine for a majority of use cases, unless you want optimal quality and compression. Today, we’ll set up the Docker and Windows version of Tdarr using a GPU to regain up to 50% of your disk space back. • 1 yr. If using Docker, please still read the previous page of instructions as the configurations will be the same except you'll be setting the variables through env vars instead of the Config. Share. i just can't get GPU encoding to work, ALTHO it works somehow. Tdarr V2 is a cross-platform conditional based transcoding application for automating media library transcode/remux management in order to process your media files as required. Ffmpeg on windows worker fairly straightforward and used my 1070ti. Scenario 2 (3 days into array being up) iowait skyrockets to 50-70% of CPU making CPU 100% and freezing everything. Jul 21, 2023 · Tdarr is best when using all the CPU and GPU power of all PCs on your local network for re-encoding your files. For example, you can set rules for the required codecs, containers, languages etc that your media should have which helps keeps things organized and can increase I think that is the only way to access the nvidia card, otherwise the integrated video card is used. 3GB: Unless you are talking about Intel chips with QuickSync, a pure GPU transcode is going to be faster. We would like to show you a description here but the site won’t allow us. Expected behavior. All my media is on a fairly idle 10core/256GB TruNAS Scale Tdarr uses GPU to transcode 4 episodes at a time from x264 to x265. No branches or pull requests. if i start an ffmpeg command directly in a tdarr-node image (overriding the cmd) then hardware encoding works. Of course you will need to change the environment variables and point to the correct 6K subscribers in the Tdarr community. Start GPU transcoding, observe top on node. Tdarr failing to use GPU encoding cannot figure it out. I have the server and node running on a dedicated Windows 11 computer with a nvidia gtx 1050ti card. When I run the example hardware encoding container, everything responds as you'd hope: Current reviews talk about a lot of flaws with Intels new graphics cards especially regarding the driver, but also faster transcoding speed with higher quality in comparison to Nvidia (see Tomshardware, Computerbase (german )) I'm thinking about buying one, but right now it seems like a fifty-fifty chance that it would even work at all. 264 to H. Node not using GPU. I have a Windows PC as Tdarr server and node. Should be able to find one on eBay for under $150. Tdarr_Plugin_bsh1_Boosh_FFMPEG_QSV_HEVC. Sample videos are rendering well with no artifacts. Linking Charts Internally. Describe the bug. I currently have AMD Ryzen 5 7600 CPU and a AMD Radeon RX 7900 XTX GPU and 32GB of ram. 40GHz 24gb ram Goes through each frame of the file with FFmpeg, available for CPU/GPU workers. I changed the variable of " NVIDIA_VISIBLE_DEVICES" to "NVIDIA VISIBLE DEVICES". Container station can be chosen as default 'user' of your GPU. There are whole papers written on the subject. There need to be some changes to the Jellyfin docker. “However I ran into a bug in the version that comes with the Tdarr container at the time of writing (2. This would allow a user to have: X workers for GPU transcoding and Y workers for GPU transcoding. A dedicated GPU isn't required. All drivers updated, all options for gpu checked, using the plugins that specify gpu but it is still resorting to my cpu. Describe alternatives you've considered As for the AAC audio, try the plugin " Tdarr_Plugin_MC93_Migz5ConvertAudio " this allows you to create a stereo audio channel for all content that contains 5. I'm fine transcoding from H265 because that can be done on my GPU without a problem. Nvidia nvenc encoding is roughly 3 times as fast as Intel iGPUs. io/download/ Gpu is much faster but the output size and quality might not be as good/small as cpu. \*\*Beyond that, follow general tdarr setup guidelines. And 6 jellyfin users. copy this to your Plugins/Local/ and rename it to 1111_Transcode_Standard. Any files not already encoded as HEVC are then transcoded to HEVC using AMF. While it chugs through I am noticing a massive CPU draw on my system. Describe the bug Starting a tdarr_node in a Docker container on my desktop. GPU encoding for me is 4x faster and much less heat and fan noise than CPU. Maybe I'm missing something or doing something wrong but after looking On the main Tdarr tab, in the "Server Overview" and Nodes section (if you click on "MainNode" default name), it shows the current OS memory and OS CPU stats. Tdarr V2 is a distributed transcoding system for automating media library transcode/remux management and… Distributed. I only have GPU health check nodes enabled (on the N100-based system) and I do not have GPU nodes can do CPU tasks enabled. Hey there! I have a Quadro P400 installed in my server, am running ESXi 6. It's not that I'm not experienced, but for some reason, I cannot get it to see/use the nvidia drivers that ARE installed. Award. Hey Fam, so I have Tdarr server and node installed on a windows pc AMD ryzen 5 3600 with a gtx1660ti, and a Here's what worked for me running in a docker on Unraid: Make sure in the Node Options for your QSV tdarr node you have the hardware encoding type set to "vaapi" and NOT "qsv". g. ClusterTool. Does that plugin use handbrake or ffmpeg. To Reproduce Docker Container is run as: #!/bin/bash serverIP=<IP of Tdarr_server> nodeIP=<IP of node> host=$ (hostname) mediaFold Aug 17, 2021 · tehniemer commented on Aug 17, 2021. The Unraid server is quite old hardware, the node is running on a ZBook with a Nvidia P500 so i thought i could use the laptops GPU for the Transcoding. Haveagitgat/tdarr is compatible with various operating systems and media formats. tn ue fl xg ck iv if va im aa