I used Yolov8 to train my dataset with the CPU and it went great when I wanted to use GPU and train another dataset it's giving me NotImplementedError. i have set up cuda and pytroch and they are defined without any problems, How could I fix it. Please help me. Thank you
the code:
from ultralytics import YOLO
model = YOLO("yolov8m.yaml")
model.train(data="yolo_con.yaml", epochs=100)
my cuda version and Ultralytics:
2.3.0+cu121
12.1
3.11.4 (tags/v3.11.4:d2340ef, Jun 7 2023, 05:45:37) [MSC v.1934 64 bit (AMD64)]
Ultralytics YOLOv8.2.16 Python-3.11.4 torch-2.3.0+cu121 CUDA:0 (NVIDIA GeForce RTX 3070 Laptop GPU, 8192MiB)
Setup complete (16 CPUs, 15.7 GB RAM, 22.7/64.0 GB disk)
the error:
Ultralytics YOLOv8.2.16 Python-3.11.4 torch-2.3.0+cu121 CUDA:0 (NVIDIA GeForce RTX 3070 Laptop GPU, 8192MiB)
engine\trainer: task=detect, mode=train, model=yolov8m.yaml, data=yolo_con.yaml, epochs=100, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs\detect\train
WARNING:tensorflow:From c:\Users\eraha\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.
Overriding model.yaml nc=80 with nc=4
from n params module arguments
0 -1 1 1392 ultralytics.nn.modules.conv.Conv [3, 48, 3, 2]
1 -1 1 41664 ultralytics.nn.modules.conv.Conv [48, 96, 3, 2]
2 -1 2 111360 ultralytics.nn.modules.block.C2f [96, 96, 2, True]
3 -1 1 166272 ultralytics.nn.modules.conv.Conv [96, 192, 3, 2]
4 -1 4 813312 ultralytics.nn.modules.block.C2f [192, 192, 4, True]
5 -1 1 664320 ultralytics.nn.modules.conv.Conv [192, 384, 3, 2]
6 -1 4 3248640 ultralytics.nn.modules.block.C2f [384, 384, 4, True]
7 -1 1 1991808 ultralytics.nn.modules.conv.Conv [384, 576, 3, 2]
8 -1 2 3985920 ultralytics.nn.modules.block.C2f [576, 576, 2, True]
9 -1 1 831168 ultralytics.nn.modules.block.SPPF [576, 576, 5]
10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1]
12 -1 2 1993728 ultralytics.nn.modules.block.C2f [960, 384, 2]
13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1]
15 -1 2 517632 ultralytics.nn.modules.block.C2f [576, 192, 2]
16 -1 1 332160 ultralytics.nn.modules.conv.Conv [192, 192, 3, 2]
17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] ...TensorBoard: Start with 'tensorboard --logdir runs\detect\train', view at http://localhost:6006/
Freezing layer 'model.22.dfl.conv.weight'
AMP: running Automatic Mixed Precision (AMP) checks with YOLOv8n...
Downloading https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt to 'yolov8n.pt'...
Output is truncated. View as a scrollable element or open in a text editor. Adjust cell output settings...100%██████████ 6.23M/6.23M [00:02<00:00, 2.87MB/s]
NotImplementedError Traceback (most recent call last)
Cell In[3], line 5
1 from ultralytics import YOLO
3 model = YOLO("yolov8m.yaml")
-- 5 model.train(data="yolo_con.yaml", epochs=100)
File c:\Users\eraha\AppData\Local\Programs\Python\Python311\Lib\site-packages\ultralytics\engine\model.py:674, in Model.train(self, trainer, **kwargs)
671pass
673 self.trainer.hub_session = self.session # attach optional HUB session
674 self.trainer.train()
675 # Update model and cfg after training
676 if RANK in {-1, 0}:
File c:\Users\eraha\AppData\Local\Programs\Python\Python311\Lib\site-packages\ultralytics\engine\trainer.py:199, in BaseTrainer.train(self)
196ddp_cleanup(self, str(file))
198 else:
199self._do_train(world_size)
File c:\Users\eraha\AppData\Local\Programs\Python\Python311\Lib\site-packages\ultralytics\engine\trainer.py:313, in BaseTrainer._do_train(self, world_size)
311 if world_size > 1:
312self._setup_ddp(world_size)
313 self._setup_train(world_size)
315 nb = len(self.train_loader) # number of batches
316 nw = max(round(self.args.warmup_epochs * nb), 100) if self.args.warmup_epochs > 0 else -1 # warmup iterations...PythonTLSSnapshot: registered at ..\aten\src\ATen\core\PythonFallbackKernel.cpp:162 [backend fallback]
FuncTorchDynamicLayerFrontMode: registered at ..\aten\src\ATen\functorch\DynamicLayer.cpp:493 [backend fallback]
PreDispatch: registered at ..\aten\src\ATen\core\PythonFallbackKernel.cpp:166 [backend fallback]
PythonDispatcher: registered at ..\aten\src\ATen\core\PythonFallbackKernel.cpp:158 [backend fallback]
Output is truncated. View as a scrollable element or open in a text editor. Adjust cell output settings...

First and Foremost, apologies to the Discord_selfbots Moderation team as this is the 3rd cheddlatron post i have had to make due to reddit deleting the first, deleting the second posting a link to a pastebin for the first, and then suspending that account i wanted to use so that it was all kept within the Cheddlatron Name. (Praying this doesnt suspend my main as well.)
And now for release:
Cheddlatron is a Free Selfbot, designed by a few members of the old Selfbot community, including names such as: Gasai, Invicta, EW, etc. Alongside external help from selfbot developers such as Eintim, and Lightning.
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We aim to be as community based as we possibly can, so if you download and feel like its missing some features you would like, feel free to check out our discord server and suggest some features for the bot.
Below are some credits, for the help we have received during development, alongside a special thanks to our testers for the support they have given us throughout the lenghty development period.

For help with setup etc, Please refer to https://docs.cheddlatron.com/

For the official download please see https://cheddlatron.com

There may still be some unforseen bugs in the code or the bot itself, if there is, please report them to us in our discord server and we will try our best to get them fixed where possible / when possible.

Credits:

Cheddlar - Co-Dev.
Wraith - Co-Dev.
Linguini - Co-Dev.
EinWortspiel - Ex-Co-Dev. Retired but not forgotten o/
Lightning - Helping to setup an EmbedAPI in golang, for our Web Embed mode.
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Coquettte - Fire website design, alongside continuing to update it even after it was finished.

Tester Mentions:

Desync and Koshak, the original two testers who helped point out a multitude of a lot of bigger bugs.
tempname.exe, helping with a lot of the later features in terms of testing and finding some of the overlooked bugs we could not replicate but were able to fix.
EinWortspiel, Originally a developer then decided to leave the team due to being a lot busier in irl life so didn't want to take credit for progress he physically could not work on, and so he came back twice as strong as a tester and has hugely helped in implementing new fixes and a lot of bugs i made on different tools and utilities designed FOR Cheddlatron.
As Well as the rest of the tester team, for helping with testing, bug fixes, and doing stupid checks on shit i wasnt sure if worked or not.
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I have thought about this for a while. I feel horizontal grid expansions (similar to the ones given to general pool sync pairs on PokeMas Day) would be a nice power boost to older Master Fairs. I will list some grid tiles I would give to Master Fairs (and EX roles if they don't have them.) I will just list all of the Master Fairs without B-Moves.
Leon and Charizard:
Wanted to give him the Max Move tiles and skills that worked with his Max Moves, as well as powering up his coverage.

• Max Move power-up tiles
• Max Countdown 2
• Super Freebie 2
• G-Max Wildfire: Sun
• Maximum Super Powered 3
• +20 Atk, +20 Sp. Atk

Maxie and Groudon:
Archie and Maxie pretty much got the same buffs.

• Weather Sync Up 3
• Charging Sun (any level)
• Haymaker
• One with the Sun
• +20 Attack, +20 Speed

Archie and Kyogre:
Archie and Maxie pretty much got the same buffs.

• Weather Sync Up 3
• Raging Rain (any level)
• Brainpower
• Torrential Tenacity
• +20 Sp. Atk, +20 Speed

Anniversary Lillie (2021) and Lunala:
Wanted to make her nuke not garbage.

• Brainpower
• Super Powered 3
• Double Down 3
• Furious Brain
• +20 Sp. Atk, +20 Sp. Atk

Anniversary N (2021) and Reshiram:
More special attack and debuffs, plus AOE sync nuke!

• EX Role: Strike
• Double Drop
• Soften Up 1
• Power Play
• Grab Bag 9
• +20 Sp. Atk, +20 Sp Atk

Anniversary Steven (2021) and Rayquaza:
Hopefully this makes him better (It's still probably comically underpowered).

• EX Role: Sprint
• Sentry Entry 3
• Wise Entry 3
• X Attack: Berserker 1
• Super Powered 5
• +20 Attack, +20 Sp. Atk

Sygna Suit Lusamine and Dusk Mane Necrozma
I wanted to increase her super effective damage more.

• T-Move: Propulsion 9
• Double Down 5
• Weird World
• Recharging Strike 9
• +20 Sp. Atk, +20 Speed

Sygna Suit Cynthia (Renegade) and Giritina Altered Forme
Just self-sufficiency and Terrain Extension.

• Ghost Zone Extension 5
• T-Move: Ramp Up 2
• T-Move: Berserker 2
• Queue Cutter 4
• +20 Attack, +20 Sp. Atk

Sygna Suit Serena and Zygarde
I gave Serena some utility, as well as better gauge management and a stronger nuke.

• Mind Games 9
• Defense Crush 9
• Recharging Strike 9
• Haymaker
• +20 Attack, +20 Sp. Atk

Sygna Suit Ethan and Lugia
I wanted these buffs to keep the TM and Areoblast alternation gameplay.

• EX Role: Tech
• Aeroblast: Brain Gain 9
• Critical Strike 3
• Critical Speed 9
• Critastrophe 2
• +20 Sp. Atk, +20 Sp. Atk

Sygna Suit Lyra and Celebi
I put my bias against Lyra for this. Also, the new passive naming system sucks. It makes sync pair theory crafting so much harder.

• EX Role: Sprint
• Grassy Terrain Extension 5
• T-Move: Berserk Bunch 1
• T-Move: All Ramped Up 1
• P-Move on Grassy Terrain: Opp Team: Defense & Sp. Def ↓, Team Defense & Sp. Def ↑ (Basically Team Verdant Defense Drain but also lowering the opposing team's Sp. Def and raising the team's Sp. Def)
• +20 Defense, +20 Sp. Def

Sygna Suit Kris and Suicune
If they give her any other EX role besides Field, I will cry. Wanted to add to her survivability and SMUN stacking.

• EX Role: Field
• Flood Alert 5
• 1st Use Status P-Move: Team Defense ↑ 4
• Team Limited Special Boost 9
• T-Move: Team Hit and Heal
• +20 Defense, +20 Sp. Def

​
So, these are just some ideas for horizontal grid extensions. Feel free to share you thoughts in the comments.

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