End of training
Browse files- .gitattributes +12 -0
- README.md +99 -0
- can_12_weights.safetensors +3 -0
- canola_12_1.png +3 -0
- canola_12_2.png +3 -0
- canola_12_35_1.png +3 -0
- canola_12_3_1.png +3 -0
- canola_12_45_1.png +3 -0
- canola_12_4_1.png +3 -0
- canola_12_5_1.png +3 -0
- canola_12_8_1.png +3 -0
- checkpoint-500/optimizer.bin +3 -0
- checkpoint-500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/scaler.pt +3 -0
- checkpoint-500/scheduler.bin +3 -0
- image_0.png +3 -0
- image_1.png +3 -0
- image_2.png +3 -0
- image_3.png +3 -0
- inference.py +16 -0
- log.txt +0 -0
- logs/dreambooth-sd3-lora/1743823161.0409586/events.out.tfevents.1743823161.g338.1131650.1 +3 -0
- logs/dreambooth-sd3-lora/1743823161.045078/hparams.yml +77 -0
- logs/dreambooth-sd3-lora/events.out.tfevents.1743823161.g338.1131650.0 +3 -0
- pytorch_lora_weights.safetensors +3 -0
- run-inference.sh +18 -0
- slurm-6020659.out +7 -0
- slurm-6020660.out +7 -0
- slurm-6020661.out +7 -0
- slurm-6021266.out +7 -0
- slurm-6021267.out +7 -0
- slurm-6021268.out +7 -0
- slurm-6021269.out +7 -0
- slurm-6021270.out +7 -0
.gitattributes
CHANGED
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@@ -33,3 +33,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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| 36 |
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canola_12_1.png filter=lfs diff=lfs merge=lfs -text
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canola_12_2.png filter=lfs diff=lfs merge=lfs -text
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canola_12_35_1.png filter=lfs diff=lfs merge=lfs -text
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canola_12_3_1.png filter=lfs diff=lfs merge=lfs -text
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canola_12_45_1.png filter=lfs diff=lfs merge=lfs -text
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canola_12_4_1.png filter=lfs diff=lfs merge=lfs -text
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canola_12_5_1.png filter=lfs diff=lfs merge=lfs -text
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canola_12_8_1.png filter=lfs diff=lfs merge=lfs -text
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image_0.png filter=lfs diff=lfs merge=lfs -text
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image_1.png filter=lfs diff=lfs merge=lfs -text
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image_2.png filter=lfs diff=lfs merge=lfs -text
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image_3.png filter=lfs diff=lfs merge=lfs -text
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README.md
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| 1 |
+
---
|
| 2 |
+
base_model: stabilityai/stable-diffusion-3-medium-diffusers
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| 3 |
+
library_name: diffusers
|
| 4 |
+
license: other
|
| 5 |
+
instance_prompt: a photo of a 17 day old canola plant with different sized leaves.
|
| 6 |
+
It is growing in a bright blue cup
|
| 7 |
+
widget:
|
| 8 |
+
- text: A photo of a 17 day old canola plant with different sized leaves. The leaves
|
| 9 |
+
are ruffled around the edges and spread beyond the cup. It is growing in nutrient-rich
|
| 10 |
+
soil in a smooth, bright blue cup on a bright blue background
|
| 11 |
+
output:
|
| 12 |
+
url: image_0.png
|
| 13 |
+
- text: A photo of a 17 day old canola plant with different sized leaves. The leaves
|
| 14 |
+
are ruffled around the edges and spread beyond the cup. It is growing in nutrient-rich
|
| 15 |
+
soil in a smooth, bright blue cup on a bright blue background
|
| 16 |
+
output:
|
| 17 |
+
url: image_1.png
|
| 18 |
+
- text: A photo of a 17 day old canola plant with different sized leaves. The leaves
|
| 19 |
+
are ruffled around the edges and spread beyond the cup. It is growing in nutrient-rich
|
| 20 |
+
soil in a smooth, bright blue cup on a bright blue background
|
| 21 |
+
output:
|
| 22 |
+
url: image_2.png
|
| 23 |
+
- text: A photo of a 17 day old canola plant with different sized leaves. The leaves
|
| 24 |
+
are ruffled around the edges and spread beyond the cup. It is growing in nutrient-rich
|
| 25 |
+
soil in a smooth, bright blue cup on a bright blue background
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| 26 |
+
output:
|
| 27 |
+
url: image_3.png
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| 28 |
+
tags:
|
| 29 |
+
- text-to-image
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| 30 |
+
- diffusers-training
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| 31 |
+
- diffusers
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| 32 |
+
- lora
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| 33 |
+
- template:sd-lora
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| 34 |
+
- sd3
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| 35 |
+
- sd3-diffusers
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| 36 |
+
---
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| 37 |
+
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| 38 |
+
<!-- This model card has been generated automatically according to the information the training script had access to. You
|
| 39 |
+
should probably proofread and complete it, then remove this comment. -->
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| 40 |
+
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| 41 |
+
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| 42 |
+
# SD3 DreamBooth LoRA - rdeinla/test-can-1-2
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| 43 |
+
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| 44 |
+
<Gallery />
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| 45 |
+
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| 46 |
+
## Model description
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| 47 |
+
|
| 48 |
+
These are rdeinla/test-can-1-2 DreamBooth LoRA weights for stabilityai/stable-diffusion-3-medium-diffusers.
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| 49 |
+
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| 50 |
+
The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
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| 51 |
+
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| 52 |
+
Was LoRA for the text encoder enabled? False.
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| 53 |
+
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| 54 |
+
## Trigger words
|
| 55 |
+
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| 56 |
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You should use `a photo of a 17 day old canola plant with different sized leaves. It is growing in a bright blue cup` to trigger the image generation.
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| 57 |
+
|
| 58 |
+
## Download model
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| 59 |
+
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| 60 |
+
[Download the *.safetensors LoRA](rdeinla/test-can-1-2/tree/main) in the Files & versions tab.
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| 61 |
+
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| 62 |
+
## Use it with the [𧨠diffusers library](https://github.com/huggingface/diffusers)
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| 63 |
+
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| 64 |
+
```py
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| 65 |
+
from diffusers import AutoPipelineForText2Image
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| 66 |
+
import torch
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| 67 |
+
pipeline = AutoPipelineForText2Image.from_pretrained(stabilityai/stable-diffusion-3-medium-diffusers, torch_dtype=torch.float16).to('cuda')
|
| 68 |
+
pipeline.load_lora_weights('rdeinla/test-can-1-2', weight_name='pytorch_lora_weights.safetensors')
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| 69 |
+
image = pipeline('A photo of a 17 day old canola plant with different sized leaves. The leaves are ruffled around the edges and spread beyond the cup. It is growing in nutrient-rich soil in a smooth, bright blue cup on a bright blue background').images[0]
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| 70 |
+
```
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| 71 |
+
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| 72 |
+
### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
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| 73 |
+
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| 74 |
+
- **LoRA**: download **[`diffusers_lora_weights.safetensors` here πΎ](/rdeinla/test-can-1-2/blob/main/diffusers_lora_weights.safetensors)**.
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| 75 |
+
- Rename it and place it on your `models/Lora` folder.
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| 76 |
+
- On AUTOMATIC1111, load the LoRA by adding `<lora:your_new_name:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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| 77 |
+
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| 78 |
+
For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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| 79 |
+
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| 80 |
+
## License
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| 81 |
+
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| 82 |
+
Please adhere to the licensing terms as described [here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE.md).
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+
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+
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## Intended uses & limitations
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+
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#### How to use
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+
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+
```python
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# TODO: add an example code snippet for running this diffusion pipeline
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```
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+
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+
#### Limitations and bias
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+
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[TODO: provide examples of latent issues and potential remediations]
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+
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## Training details
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| 98 |
+
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| 99 |
+
[TODO: describe the data used to train the model]
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can_12_weights.safetensors
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size 4743176
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canola_12_1.png
ADDED
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Git LFS Details
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canola_12_2.png
ADDED
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Git LFS Details
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canola_12_35_1.png
ADDED
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Git LFS Details
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canola_12_3_1.png
ADDED
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Git LFS Details
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canola_12_45_1.png
ADDED
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Git LFS Details
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canola_12_4_1.png
ADDED
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Git LFS Details
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canola_12_5_1.png
ADDED
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Git LFS Details
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canola_12_8_1.png
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Git LFS Details
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checkpoint-500/optimizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:46a5f791112faa751b6896e5107ae6101da510fc68ed84fc4ff4739720a25671
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| 3 |
+
size 37872780
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checkpoint-500/pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e4ae7e43f457f19299682b7c3f36340059d24ae9d9121659ec10b3a1e4735ea1
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size 18825720
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checkpoint-500/random_states_0.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:afa4f0a4cd1713781e762818debbf68e357584e72ea936f1bff86a9d51ef21ab
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checkpoint-500/scaler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:18b984273ea2d45b7ffb1d047bb359d93111e41fcad70d16a1b453fd38f72636
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size 988
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checkpoint-500/scheduler.bin
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version https://git-lfs.github.com/spec/v1
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size 1000
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image_0.png
ADDED
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Git LFS Details
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image_1.png
ADDED
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Git LFS Details
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image_2.png
ADDED
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Git LFS Details
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image_3.png
ADDED
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Git LFS Details
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inference.py
ADDED
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+
import torch
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| 2 |
+
from diffusers import StableDiffusion3Pipeline
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| 3 |
+
from diffusers import AutoPipelineForText2Image
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| 4 |
+
from safetensors.torch import load_file
|
| 5 |
+
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| 6 |
+
torch.backends.cuda.enable_mem_efficient_sdp(False)
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| 7 |
+
torch.backends.cuda.enable_flash_sdp(False)
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| 8 |
+
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| 9 |
+
pipeline = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16).to('cuda')
|
| 10 |
+
|
| 11 |
+
pipeline.load_lora_weights("rdeinla/test-can-1-2", weight_name='pytorch_lora_weights.safetensors')
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| 12 |
+
|
| 13 |
+
image = pipeline("A photo of a young canola plant with medium-sized leaves. The leaves are ruffled around the edges and have prominent ridges. It is about 19 days old. It is growing in dark, nutrient-rich soil. It is contained within a smooth, bright blue cylindrical cup on a bright blue background",
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| 14 |
+
guidance_scale = 5.0, negative_prompt = "blurry").images[0]
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| 15 |
+
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| 16 |
+
image.save("canola_12_5_1.png")
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log.txt
ADDED
|
File without changes
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logs/dreambooth-sd3-lora/1743823161.0409586/events.out.tfevents.1743823161.g338.1131650.1
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:a7b580a6b11ab72f28851627e17b8fab0251be4dcc56bb7e0c3b539b327914bb
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| 3 |
+
size 3778
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logs/dreambooth-sd3-lora/1743823161.045078/hparams.yml
ADDED
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| 1 |
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adam_beta1: 0.9
|
| 2 |
+
adam_beta2: 0.999
|
| 3 |
+
adam_epsilon: 1.0e-08
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| 4 |
+
adam_weight_decay: 0.0001
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| 5 |
+
adam_weight_decay_text_encoder: 0.001
|
| 6 |
+
allow_tf32: false
|
| 7 |
+
cache_dir: null
|
| 8 |
+
cache_latents: false
|
| 9 |
+
caption_column: null
|
| 10 |
+
center_crop: false
|
| 11 |
+
checkpointing_steps: 500
|
| 12 |
+
checkpoints_total_limit: null
|
| 13 |
+
class_data_dir: null
|
| 14 |
+
class_prompt: null
|
| 15 |
+
dataloader_num_workers: 0
|
| 16 |
+
dataset_config_name: null
|
| 17 |
+
dataset_name: null
|
| 18 |
+
gradient_accumulation_steps: 1
|
| 19 |
+
gradient_checkpointing: false
|
| 20 |
+
hub_model_id: null
|
| 21 |
+
hub_token: null
|
| 22 |
+
image_column: image
|
| 23 |
+
instance_data_dir: /project/6085367/SharedData/diffusers/examples/dreambooth/Canola/10to19days/10to19-train
|
| 24 |
+
instance_prompt: a photo of a 17 day old canola plant with different sized leaves.
|
| 25 |
+
It is growing in a bright blue cup
|
| 26 |
+
learning_rate: 0.00045
|
| 27 |
+
local_rank: 0
|
| 28 |
+
logging_dir: logs
|
| 29 |
+
logit_mean: 0.0
|
| 30 |
+
logit_std: 1.0
|
| 31 |
+
lora_blocks: null
|
| 32 |
+
lora_layers: null
|
| 33 |
+
lr_num_cycles: 1
|
| 34 |
+
lr_power: 1.0
|
| 35 |
+
lr_scheduler: constant
|
| 36 |
+
lr_warmup_steps: 100
|
| 37 |
+
max_grad_norm: 1.0
|
| 38 |
+
max_sequence_length: 77
|
| 39 |
+
max_train_steps: 850
|
| 40 |
+
mixed_precision: fp16
|
| 41 |
+
mode_scale: 1.29
|
| 42 |
+
num_class_images: 100
|
| 43 |
+
num_train_epochs: 425
|
| 44 |
+
num_validation_images: 4
|
| 45 |
+
optimizer: AdamW
|
| 46 |
+
output_dir: /project/6085367/SharedData/diffusers/examples/dreambooth/trained-sd3-outputs/test-can-1-2
|
| 47 |
+
precondition_outputs: 1
|
| 48 |
+
pretrained_model_name_or_path: stabilityai/stable-diffusion-3-medium-diffusers
|
| 49 |
+
prior_generation_precision: null
|
| 50 |
+
prior_loss_weight: 1.0
|
| 51 |
+
prodigy_beta3: null
|
| 52 |
+
prodigy_decouple: true
|
| 53 |
+
prodigy_safeguard_warmup: true
|
| 54 |
+
prodigy_use_bias_correction: true
|
| 55 |
+
push_to_hub: true
|
| 56 |
+
random_flip: false
|
| 57 |
+
rank: 8
|
| 58 |
+
repeats: 1
|
| 59 |
+
report_to: tensorboard
|
| 60 |
+
resolution: 768
|
| 61 |
+
resume_from_checkpoint: null
|
| 62 |
+
revision: null
|
| 63 |
+
sample_batch_size: 4
|
| 64 |
+
scale_lr: false
|
| 65 |
+
seed: 42
|
| 66 |
+
text_encoder_lr: 5.0e-06
|
| 67 |
+
train_batch_size: 2
|
| 68 |
+
train_text_encoder: false
|
| 69 |
+
upcast_before_saving: false
|
| 70 |
+
use_8bit_adam: false
|
| 71 |
+
validation_epochs: 4
|
| 72 |
+
validation_prompt: A photo of a 17 day old canola plant with different sized leaves.
|
| 73 |
+
The leaves are ruffled around the edges and spread beyond the cup. It is growing
|
| 74 |
+
in nutrient-rich soil in a smooth, bright blue cup on a bright blue background
|
| 75 |
+
variant: null
|
| 76 |
+
weighting_scheme: logit_normal
|
| 77 |
+
with_prior_preservation: false
|
logs/dreambooth-sd3-lora/events.out.tfevents.1743823161.g338.1131650.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0c6461e18e1371c6d4e0f1f951418410018bc5f77f972160d802e103462feb5e
|
| 3 |
+
size 468230219
|
pytorch_lora_weights.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:376fb497b2d9d0e3772133764cf114e2284a6c2de53fcd88dad203d8df22cd43
|
| 3 |
+
size 9437288
|
run-inference.sh
ADDED
|
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/sh
|
| 2 |
+
|
| 3 |
+
#SBATCH --nodes=1
|
| 4 |
+
#SBATCH --ntasks-per-node=4
|
| 5 |
+
#SBATCH --cpus-per-task=4
|
| 6 |
+
#SBATCH --mem=15GB
|
| 7 |
+
#SBATCH --time=0-10:00
|
| 8 |
+
#SBATCH --partition=livi
|
| 9 |
+
#SBATCH --mail-user=deinlar@myumanitoba.ca
|
| 10 |
+
#SBATCH --mail-type=END
|
| 11 |
+
#SBATCH --gpus=1
|
| 12 |
+
|
| 13 |
+
module load cuda/12.4.1 arch/avx2 gcc/13.2.0
|
| 14 |
+
module load python/3.11.11
|
| 15 |
+
|
| 16 |
+
source /project/6085367/SharedData/my_newvenv/bin/activate
|
| 17 |
+
|
| 18 |
+
python3 inference.py>log.txt
|
slurm-6020659.out
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
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|
|
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| 0 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 1 |
4%|β | 1/28 [00:02<00:56, 2.08s/it]
|
| 2 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 3 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 4 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 5 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 6 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 7 |
25%|βββ | 7/28 [00:12<00:39, 1.90s/it]
|
| 8 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 9 |
32%|ββββ | 9/28 [00:16<00:36, 1.92s/it]
|
| 10 |
36%|ββββ | 10/28 [00:18<00:34, 1.92s/it]
|
| 11 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 12 |
43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
|
| 13 |
46%|βββββ | 13/28 [00:24<00:28, 1.93s/it]
|
| 14 |
50%|βββββ | 14/28 [00:26<00:27, 1.93s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:34<00:19, 1.93s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:41<00:11, 1.94s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:43<00:09, 1.94s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.95s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.95s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 9 |
4%|β | 1/28 [00:02<00:56, 2.08s/it]
|
| 10 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 11 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 12 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
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| 13 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 14 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 15 |
25%|βββ | 7/28 [00:12<00:39, 1.90s/it]
|
| 16 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 17 |
32%|ββββ | 9/28 [00:16<00:36, 1.92s/it]
|
| 18 |
36%|ββββ | 10/28 [00:18<00:34, 1.92s/it]
|
| 19 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 20 |
43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
|
| 21 |
46%|βββββ | 13/28 [00:24<00:28, 1.93s/it]
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| 22 |
50%|βββββ | 14/28 [00:26<00:27, 1.93s/it]
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| 23 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
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| 24 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
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| 25 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
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| 26 |
64%|βββββββ | 18/28 [00:34<00:19, 1.93s/it]
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| 27 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 28 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 29 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 30 |
79%|ββββββββ | 22/28 [00:41<00:11, 1.94s/it]
|
| 31 |
82%|βββββββββ | 23/28 [00:43<00:09, 1.94s/it]
|
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86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 33 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 34 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.95s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.95s/it]
|
slurm-6020660.out
ADDED
|
@@ -0,0 +1,7 @@
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| 0 |
0%| | 0/28 [00:00<?, ?it/s]
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| 1 |
4%|β | 1/28 [00:02<00:56, 2.08s/it]
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| 2 |
7%|β | 2/28 [00:03<00:39, 1.53s/it]
|
| 3 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
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| 4 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 5 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 6 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
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| 7 |
25%|βββ | 7/28 [00:12<00:39, 1.90s/it]
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29%|βββ | 8/28 [00:14<00:38, 1.92s/it]
|
| 9 |
32%|ββββ | 9/28 [00:16<00:36, 1.92s/it]
|
| 10 |
36%|ββββ | 10/28 [00:18<00:34, 1.93s/it]
|
| 11 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 12 |
43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
|
| 13 |
46%|βββββ | 13/28 [00:24<00:29, 1.94s/it]
|
| 14 |
50%|βββββ | 14/28 [00:26<00:27, 1.94s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:34<00:19, 1.94s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:36<00:17, 1.95s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:44<00:09, 1.95s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.95s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
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0%| | 0/28 [00:00<?, ?it/s]
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4%|β | 1/28 [00:02<00:56, 2.08s/it]
|
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7%|β | 2/28 [00:03<00:39, 1.53s/it]
|
| 11 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
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| 12 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
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| 13 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
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21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
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25%|βββ | 7/28 [00:12<00:39, 1.90s/it]
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| 16 |
29%|βββ | 8/28 [00:14<00:38, 1.92s/it]
|
| 17 |
32%|ββββ | 9/28 [00:16<00:36, 1.92s/it]
|
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36%|ββββ | 10/28 [00:18<00:34, 1.93s/it]
|
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39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
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43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
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| 21 |
46%|βββββ | 13/28 [00:24<00:29, 1.94s/it]
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50%|βββββ | 14/28 [00:26<00:27, 1.94s/it]
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54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
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57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
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61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
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64%|βββββββ | 18/28 [00:34<00:19, 1.94s/it]
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| 27 |
68%|βββββββ | 19/28 [00:36<00:17, 1.95s/it]
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71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
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75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
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79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
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82%|βββββββββ | 23/28 [00:44<00:09, 1.95s/it]
|
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86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
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89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
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93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.95s/it]
|
slurm-6020661.out
ADDED
|
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| 0 |
0%| | 0/28 [00:00<?, ?it/s]
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4%|β | 1/28 [00:02<00:56, 2.11s/it]
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7%|β | 2/28 [00:03<00:40, 1.54s/it]
|
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11%|β | 3/28 [00:05<00:43, 1.73s/it]
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| 4 |
14%|ββ | 4/28 [00:07<00:43, 1.81s/it]
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| 5 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 6 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 7 |
25%|βββ | 7/28 [00:12<00:39, 1.89s/it]
|
| 8 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 9 |
32%|ββββ | 9/28 [00:16<00:36, 1.91s/it]
|
| 10 |
36%|ββββ | 10/28 [00:18<00:34, 1.92s/it]
|
| 11 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 12 |
43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
|
| 13 |
46%|βββββ | 13/28 [00:24<00:29, 1.94s/it]
|
| 14 |
50%|βββββ | 14/28 [00:26<00:27, 1.94s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:34<00:19, 1.94s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:43<00:09, 1.94s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.95s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.95s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.95s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.95s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 9 |
4%|β | 1/28 [00:02<00:56, 2.11s/it]
|
| 10 |
7%|β | 2/28 [00:03<00:40, 1.54s/it]
|
| 11 |
11%|β | 3/28 [00:05<00:43, 1.73s/it]
|
| 12 |
14%|ββ | 4/28 [00:07<00:43, 1.81s/it]
|
| 13 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 14 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 15 |
25%|βββ | 7/28 [00:12<00:39, 1.89s/it]
|
| 16 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 17 |
32%|ββββ | 9/28 [00:16<00:36, 1.91s/it]
|
| 18 |
36%|ββββ | 10/28 [00:18<00:34, 1.92s/it]
|
| 19 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 20 |
43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
|
| 21 |
46%|βββββ | 13/28 [00:24<00:29, 1.94s/it]
|
| 22 |
50%|βββββ | 14/28 [00:26<00:27, 1.94s/it]
|
| 23 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 24 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 25 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 26 |
64%|βββββββ | 18/28 [00:34<00:19, 1.94s/it]
|
| 27 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 28 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 29 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 30 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 31 |
82%|βββββββββ | 23/28 [00:43<00:09, 1.94s/it]
|
| 32 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.95s/it]
|
| 33 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.95s/it]
|
| 34 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.95s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.95s/it]
|
slurm-6021266.out
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 0 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 1 |
4%|β | 1/28 [00:04<01:52, 4.16s/it]
|
| 2 |
7%|β | 2/28 [00:05<01:02, 2.39s/it]
|
| 3 |
11%|β | 3/28 [00:07<00:54, 2.18s/it]
|
| 4 |
14%|ββ | 4/28 [00:09<00:50, 2.08s/it]
|
| 5 |
18%|ββ | 5/28 [00:11<00:46, 2.03s/it]
|
| 6 |
21%|βββ | 6/28 [00:13<00:43, 1.99s/it]
|
| 7 |
25%|βββ | 7/28 [00:14<00:41, 1.97s/it]
|
| 8 |
29%|βββ | 8/28 [00:16<00:39, 1.96s/it]
|
| 9 |
32%|ββββ | 9/28 [00:18<00:37, 1.95s/it]
|
| 10 |
36%|ββββ | 10/28 [00:20<00:35, 1.95s/it]
|
| 11 |
39%|ββββ | 11/28 [00:22<00:32, 1.94s/it]
|
| 12 |
43%|βββββ | 12/28 [00:24<00:31, 1.94s/it]
|
| 13 |
46%|βββββ | 13/28 [00:26<00:29, 1.94s/it]
|
| 14 |
50%|βββββ | 14/28 [00:28<00:27, 1.94s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:30<00:25, 1.94s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:32<00:23, 1.94s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:34<00:21, 1.94s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:36<00:19, 1.95s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:38<00:17, 1.94s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:40<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:42<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:44<00:11, 1.94s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:46<00:09, 1.94s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:47<00:07, 1.95s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:49<00:05, 1.96s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:51<00:03, 1.96s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:53<00:01, 1.95s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 9 |
4%|β | 1/28 [00:04<01:52, 4.16s/it]
|
| 10 |
7%|β | 2/28 [00:05<01:02, 2.39s/it]
|
| 11 |
11%|β | 3/28 [00:07<00:54, 2.18s/it]
|
| 12 |
14%|ββ | 4/28 [00:09<00:50, 2.08s/it]
|
| 13 |
18%|ββ | 5/28 [00:11<00:46, 2.03s/it]
|
| 14 |
21%|βββ | 6/28 [00:13<00:43, 1.99s/it]
|
| 15 |
25%|βββ | 7/28 [00:14<00:41, 1.97s/it]
|
| 16 |
29%|βββ | 8/28 [00:16<00:39, 1.96s/it]
|
| 17 |
32%|ββββ | 9/28 [00:18<00:37, 1.95s/it]
|
| 18 |
36%|ββββ | 10/28 [00:20<00:35, 1.95s/it]
|
| 19 |
39%|ββββ | 11/28 [00:22<00:32, 1.94s/it]
|
| 20 |
43%|βββββ | 12/28 [00:24<00:31, 1.94s/it]
|
| 21 |
46%|βββββ | 13/28 [00:26<00:29, 1.94s/it]
|
| 22 |
50%|βββββ | 14/28 [00:28<00:27, 1.94s/it]
|
| 23 |
54%|ββββββ | 15/28 [00:30<00:25, 1.94s/it]
|
| 24 |
57%|ββββββ | 16/28 [00:32<00:23, 1.94s/it]
|
| 25 |
61%|ββββββ | 17/28 [00:34<00:21, 1.94s/it]
|
| 26 |
64%|βββββββ | 18/28 [00:36<00:19, 1.95s/it]
|
| 27 |
68%|βββββββ | 19/28 [00:38<00:17, 1.94s/it]
|
| 28 |
71%|ββββββββ | 20/28 [00:40<00:15, 1.94s/it]
|
| 29 |
75%|ββββββββ | 21/28 [00:42<00:13, 1.94s/it]
|
| 30 |
79%|ββββββββ | 22/28 [00:44<00:11, 1.94s/it]
|
| 31 |
82%|βββββββββ | 23/28 [00:46<00:09, 1.94s/it]
|
| 32 |
86%|βββββββββ | 24/28 [00:47<00:07, 1.95s/it]
|
| 33 |
89%|βββββββββ | 25/28 [00:49<00:05, 1.96s/it]
|
| 34 |
93%|ββββββββββ| 26/28 [00:51<00:03, 1.96s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:53<00:01, 1.95s/it]
|
slurm-6021267.out
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 0 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 1 |
4%|β | 1/28 [00:02<00:56, 2.09s/it]
|
| 2 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 3 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 4 |
14%|ββ | 4/28 [00:07<00:43, 1.81s/it]
|
| 5 |
18%|ββ | 5/28 [00:09<00:42, 1.87s/it]
|
| 6 |
21%|βββ | 6/28 [00:11<00:41, 1.90s/it]
|
| 7 |
25%|βββ | 7/28 [00:12<00:40, 1.91s/it]
|
| 8 |
29%|βββ | 8/28 [00:14<00:38, 1.92s/it]
|
| 9 |
32%|ββββ | 9/28 [00:16<00:36, 1.93s/it]
|
| 10 |
36%|ββββ | 10/28 [00:18<00:34, 1.93s/it]
|
| 11 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 12 |
43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
|
| 13 |
46%|βββββ | 13/28 [00:24<00:28, 1.93s/it]
|
| 14 |
50%|βββββ | 14/28 [00:26<00:27, 1.93s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:34<00:19, 1.95s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:44<00:09, 1.94s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 9 |
4%|β | 1/28 [00:02<00:56, 2.09s/it]
|
| 10 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 11 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 12 |
14%|ββ | 4/28 [00:07<00:43, 1.81s/it]
|
| 13 |
18%|ββ | 5/28 [00:09<00:42, 1.87s/it]
|
| 14 |
21%|βββ | 6/28 [00:11<00:41, 1.90s/it]
|
| 15 |
25%|βββ | 7/28 [00:12<00:40, 1.91s/it]
|
| 16 |
29%|βββ | 8/28 [00:14<00:38, 1.92s/it]
|
| 17 |
32%|ββββ | 9/28 [00:16<00:36, 1.93s/it]
|
| 18 |
36%|ββββ | 10/28 [00:18<00:34, 1.93s/it]
|
| 19 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 20 |
43%|βββββ | 12/28 [00:22<00:30, 1.93s/it]
|
| 21 |
46%|βββββ | 13/28 [00:24<00:28, 1.93s/it]
|
| 22 |
50%|βββββ | 14/28 [00:26<00:27, 1.93s/it]
|
| 23 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 24 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 25 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 26 |
64%|βββββββ | 18/28 [00:34<00:19, 1.95s/it]
|
| 27 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 28 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 29 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 30 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 31 |
82%|βββββββββ | 23/28 [00:44<00:09, 1.94s/it]
|
| 32 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 33 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 34 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|
slurm-6021268.out
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 0 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 1 |
4%|β | 1/28 [00:02<00:55, 2.07s/it]
|
| 2 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 3 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 4 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 5 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 6 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 7 |
25%|βββ | 7/28 [00:12<00:40, 1.91s/it]
|
| 8 |
29%|βββ | 8/28 [00:14<00:38, 1.93s/it]
|
| 9 |
32%|ββββ | 9/28 [00:16<00:36, 1.94s/it]
|
| 10 |
36%|ββββ | 10/28 [00:18<00:34, 1.94s/it]
|
| 11 |
39%|ββββ | 11/28 [00:20<00:32, 1.94s/it]
|
| 12 |
43%|βββββ | 12/28 [00:22<00:30, 1.94s/it]
|
| 13 |
46%|βββββ | 13/28 [00:24<00:29, 1.94s/it]
|
| 14 |
50%|βββββ | 14/28 [00:26<00:27, 1.94s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:34<00:19, 1.94s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.95s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:44<00:09, 1.95s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 9 |
4%|β | 1/28 [00:02<00:55, 2.07s/it]
|
| 10 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 11 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 12 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 13 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 14 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 15 |
25%|βββ | 7/28 [00:12<00:40, 1.91s/it]
|
| 16 |
29%|βββ | 8/28 [00:14<00:38, 1.93s/it]
|
| 17 |
32%|ββββ | 9/28 [00:16<00:36, 1.94s/it]
|
| 18 |
36%|ββββ | 10/28 [00:18<00:34, 1.94s/it]
|
| 19 |
39%|ββββ | 11/28 [00:20<00:32, 1.94s/it]
|
| 20 |
43%|βββββ | 12/28 [00:22<00:30, 1.94s/it]
|
| 21 |
46%|βββββ | 13/28 [00:24<00:29, 1.94s/it]
|
| 22 |
50%|βββββ | 14/28 [00:26<00:27, 1.94s/it]
|
| 23 |
54%|ββββββ | 15/28 [00:28<00:25, 1.94s/it]
|
| 24 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 25 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 26 |
64%|βββββββ | 18/28 [00:34<00:19, 1.94s/it]
|
| 27 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 28 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 29 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 30 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.95s/it]
|
| 31 |
82%|βββββββββ | 23/28 [00:44<00:09, 1.95s/it]
|
| 32 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 33 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 34 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|
slurm-6021269.out
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 0 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 1 |
4%|β | 1/28 [00:02<00:56, 2.08s/it]
|
| 2 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 3 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 4 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 5 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 6 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 7 |
25%|βββ | 7/28 [00:12<00:39, 1.90s/it]
|
| 8 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 9 |
32%|ββββ | 9/28 [00:16<00:36, 1.92s/it]
|
| 10 |
36%|ββββ | 10/28 [00:18<00:34, 1.93s/it]
|
| 11 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 12 |
43%|βββββ | 12/28 [00:22<00:31, 1.94s/it]
|
| 13 |
46%|βββββ | 13/28 [00:24<00:29, 1.95s/it]
|
| 14 |
50%|βββββ | 14/28 [00:26<00:27, 1.95s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:28<00:25, 1.95s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:30<00:23, 1.95s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:32<00:21, 1.95s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:34<00:19, 1.95s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:36<00:17, 1.95s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:44<00:09, 1.94s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.95s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.95s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 9 |
4%|β | 1/28 [00:02<00:56, 2.08s/it]
|
| 10 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 11 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 12 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 13 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 14 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 15 |
25%|βββ | 7/28 [00:12<00:39, 1.90s/it]
|
| 16 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 17 |
32%|ββββ | 9/28 [00:16<00:36, 1.92s/it]
|
| 18 |
36%|ββββ | 10/28 [00:18<00:34, 1.93s/it]
|
| 19 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 20 |
43%|βββββ | 12/28 [00:22<00:31, 1.94s/it]
|
| 21 |
46%|βββββ | 13/28 [00:24<00:29, 1.95s/it]
|
| 22 |
50%|βββββ | 14/28 [00:26<00:27, 1.95s/it]
|
| 23 |
54%|ββββββ | 15/28 [00:28<00:25, 1.95s/it]
|
| 24 |
57%|ββββββ | 16/28 [00:30<00:23, 1.95s/it]
|
| 25 |
61%|ββββββ | 17/28 [00:32<00:21, 1.95s/it]
|
| 26 |
64%|βββββββ | 18/28 [00:34<00:19, 1.95s/it]
|
| 27 |
68%|βββββββ | 19/28 [00:36<00:17, 1.95s/it]
|
| 28 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 29 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 30 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 31 |
82%|βββββββββ | 23/28 [00:44<00:09, 1.94s/it]
|
| 32 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.95s/it]
|
| 33 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.95s/it]
|
| 34 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|
slurm-6021270.out
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 0 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 1 |
4%|β | 1/28 [00:02<00:55, 2.07s/it]
|
| 2 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 3 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 4 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 5 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 6 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 7 |
25%|βββ | 7/28 [00:12<00:39, 1.89s/it]
|
| 8 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 9 |
32%|ββββ | 9/28 [00:16<00:36, 1.91s/it]
|
| 10 |
36%|ββββ | 10/28 [00:18<00:34, 1.92s/it]
|
| 11 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 12 |
43%|βββββ | 12/28 [00:22<00:31, 1.94s/it]
|
| 13 |
46%|βββββ | 13/28 [00:24<00:29, 1.95s/it]
|
| 14 |
50%|βββββ | 14/28 [00:26<00:27, 1.95s/it]
|
| 15 |
54%|ββββββ | 15/28 [00:28<00:25, 1.95s/it]
|
| 16 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 17 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 18 |
64%|βββββββ | 18/28 [00:34<00:19, 1.95s/it]
|
| 19 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 20 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 21 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 22 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 23 |
82%|βββββββββ | 23/28 [00:43<00:09, 1.94s/it]
|
| 24 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 25 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 26 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 27 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|
|
|
|
| 1 |
+
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
|
| 8 |
0%| | 0/28 [00:00<?, ?it/s]
|
| 9 |
4%|β | 1/28 [00:02<00:55, 2.07s/it]
|
| 10 |
7%|β | 2/28 [00:03<00:39, 1.52s/it]
|
| 11 |
11%|β | 3/28 [00:05<00:42, 1.71s/it]
|
| 12 |
14%|ββ | 4/28 [00:07<00:43, 1.80s/it]
|
| 13 |
18%|ββ | 5/28 [00:09<00:42, 1.85s/it]
|
| 14 |
21%|βββ | 6/28 [00:10<00:41, 1.88s/it]
|
| 15 |
25%|βββ | 7/28 [00:12<00:39, 1.89s/it]
|
| 16 |
29%|βββ | 8/28 [00:14<00:38, 1.91s/it]
|
| 17 |
32%|ββββ | 9/28 [00:16<00:36, 1.91s/it]
|
| 18 |
36%|ββββ | 10/28 [00:18<00:34, 1.92s/it]
|
| 19 |
39%|ββββ | 11/28 [00:20<00:32, 1.93s/it]
|
| 20 |
43%|βββββ | 12/28 [00:22<00:31, 1.94s/it]
|
| 21 |
46%|βββββ | 13/28 [00:24<00:29, 1.95s/it]
|
| 22 |
50%|βββββ | 14/28 [00:26<00:27, 1.95s/it]
|
| 23 |
54%|ββββββ | 15/28 [00:28<00:25, 1.95s/it]
|
| 24 |
57%|ββββββ | 16/28 [00:30<00:23, 1.94s/it]
|
| 25 |
61%|ββββββ | 17/28 [00:32<00:21, 1.94s/it]
|
| 26 |
64%|βββββββ | 18/28 [00:34<00:19, 1.95s/it]
|
| 27 |
68%|βββββββ | 19/28 [00:36<00:17, 1.94s/it]
|
| 28 |
71%|ββββββββ | 20/28 [00:38<00:15, 1.94s/it]
|
| 29 |
75%|ββββββββ | 21/28 [00:40<00:13, 1.94s/it]
|
| 30 |
79%|ββββββββ | 22/28 [00:42<00:11, 1.94s/it]
|
| 31 |
82%|βββββββββ | 23/28 [00:43<00:09, 1.94s/it]
|
| 32 |
86%|βββββββββ | 24/28 [00:45<00:07, 1.94s/it]
|
| 33 |
89%|βββββββββ | 25/28 [00:47<00:05, 1.94s/it]
|
| 34 |
93%|ββββββββββ| 26/28 [00:49<00:03, 1.94s/it]
|
| 35 |
96%|ββββββββββ| 27/28 [00:51<00:01, 1.94s/it]
|