rdeinla commited on
Commit
3fa2f59
Β·
verified Β·
1 Parent(s): 3fcbfe4

End of training

Browse files
.gitattributes CHANGED
@@ -33,3 +33,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ canola_12_1.png filter=lfs diff=lfs merge=lfs -text
37
+ canola_12_2.png filter=lfs diff=lfs merge=lfs -text
38
+ canola_12_35_1.png filter=lfs diff=lfs merge=lfs -text
39
+ canola_12_3_1.png filter=lfs diff=lfs merge=lfs -text
40
+ canola_12_45_1.png filter=lfs diff=lfs merge=lfs -text
41
+ canola_12_4_1.png filter=lfs diff=lfs merge=lfs -text
42
+ canola_12_5_1.png filter=lfs diff=lfs merge=lfs -text
43
+ canola_12_8_1.png filter=lfs diff=lfs merge=lfs -text
44
+ image_0.png filter=lfs diff=lfs merge=lfs -text
45
+ image_1.png filter=lfs diff=lfs merge=lfs -text
46
+ image_2.png filter=lfs diff=lfs merge=lfs -text
47
+ image_3.png filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: stabilityai/stable-diffusion-3-medium-diffusers
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
26
+ output:
27
+ url: image_3.png
28
+ tags:
29
+ - text-to-image
30
+ - diffusers-training
31
+ - diffusers
32
+ - lora
33
+ - template:sd-lora
34
+ - sd3
35
+ - sd3-diffusers
36
+ ---
37
+
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. -->
40
+
41
+
42
+ # SD3 DreamBooth LoRA - rdeinla/test-can-1-2
43
+
44
+ <Gallery />
45
+
46
+ ## Model description
47
+
48
+ These are rdeinla/test-can-1-2 DreamBooth LoRA weights for stabilityai/stable-diffusion-3-medium-diffusers.
49
+
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).
51
+
52
+ Was LoRA for the text encoder enabled? False.
53
+
54
+ ## Trigger words
55
+
56
+ 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.
57
+
58
+ ## Download model
59
+
60
+ [Download the *.safetensors LoRA](rdeinla/test-can-1-2/tree/main) in the Files & versions tab.
61
+
62
+ ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
63
+
64
+ ```py
65
+ from diffusers import AutoPipelineForText2Image
66
+ import torch
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')
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]
70
+ ```
71
+
72
+ ### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
73
+
74
+ - **LoRA**: download **[`diffusers_lora_weights.safetensors` here πŸ’Ύ](/rdeinla/test-can-1-2/blob/main/diffusers_lora_weights.safetensors)**.
75
+ - Rename it and place it on your `models/Lora` folder.
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/).
77
+
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)
79
+
80
+ ## License
81
+
82
+ Please adhere to the licensing terms as described [here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE.md).
83
+
84
+
85
+ ## Intended uses & limitations
86
+
87
+ #### How to use
88
+
89
+ ```python
90
+ # TODO: add an example code snippet for running this diffusion pipeline
91
+ ```
92
+
93
+ #### Limitations and bias
94
+
95
+ [TODO: provide examples of latent issues and potential remediations]
96
+
97
+ ## Training details
98
+
99
+ [TODO: describe the data used to train the model]
can_12_weights.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:747b15dd1bf4bfb7ea45f6f0c02c7f746b72b81db1a75a85f27084fa01c0ca3e
3
+ size 4743176
canola_12_1.png ADDED

Git LFS Details

  • SHA256: df2fc06cd0bd75028caa15839dba952ba159f3e8ccd8748abb570e4d635b9453
  • Pointer size: 131 Bytes
  • Size of remote file: 905 kB
canola_12_2.png ADDED

Git LFS Details

  • SHA256: a4bb9dea623306261a46c97a53d05aa298c718df8186b1290f5c24d5cd128c41
  • Pointer size: 132 Bytes
  • Size of remote file: 1.05 MB
canola_12_35_1.png ADDED

Git LFS Details

  • SHA256: af181f81603e1caf8fd2c18099d878ec5df4a3250c0c0a456b43f28fe1a1966c
  • Pointer size: 132 Bytes
  • Size of remote file: 1.1 MB
canola_12_3_1.png ADDED

Git LFS Details

  • SHA256: 0ca5c8ff82fe41fea7c92a2b3c4303345c2ce252b0e4833253c0bd173155ce82
  • Pointer size: 132 Bytes
  • Size of remote file: 1.01 MB
canola_12_45_1.png ADDED

Git LFS Details

  • SHA256: fe1d5b299d4ece373eed245399d275dc5d89ed15950f2a0fcac96cdd1a57b502
  • Pointer size: 132 Bytes
  • Size of remote file: 1.1 MB
canola_12_4_1.png ADDED

Git LFS Details

  • SHA256: 5f2f539cdf22d9083e58ee1956237817b426c5190baa5b4b19589fd612852c06
  • Pointer size: 132 Bytes
  • Size of remote file: 1.07 MB
canola_12_5_1.png ADDED

Git LFS Details

  • SHA256: f574a9eb4f001a5d2b9adce2709e4729f39a35752fd13c30610e867954f28a4c
  • Pointer size: 132 Bytes
  • Size of remote file: 1.09 MB
canola_12_8_1.png ADDED

Git LFS Details

  • SHA256: 26b7c96e6b275709b434bd2bcf058742de882f8654969e333bd0c503351efcde
  • Pointer size: 132 Bytes
  • Size of remote file: 1.04 MB
checkpoint-500/optimizer.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:46a5f791112faa751b6896e5107ae6101da510fc68ed84fc4ff4739720a25671
3
+ size 37872780
checkpoint-500/pytorch_lora_weights.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e4ae7e43f457f19299682b7c3f36340059d24ae9d9121659ec10b3a1e4735ea1
3
+ size 18825720
checkpoint-500/random_states_0.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:afa4f0a4cd1713781e762818debbf68e357584e72ea936f1bff86a9d51ef21ab
3
+ size 14864
checkpoint-500/scaler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:18b984273ea2d45b7ffb1d047bb359d93111e41fcad70d16a1b453fd38f72636
3
+ size 988
checkpoint-500/scheduler.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e022c236c0a83a2ba601318153b5b4e6d5340e39a69ab58d42f304efbfb68a9d
3
+ size 1000
image_0.png ADDED

Git LFS Details

  • SHA256: 22a7487af8a1d190c015281526351a2dc9025caab308bb9442c47d100cf2a6ec
  • Pointer size: 132 Bytes
  • Size of remote file: 1 MB
image_1.png ADDED

Git LFS Details

  • SHA256: 2fe63bb3dcb36d987ba3dee52551de4c96305e1e36eaf468dbb2b00bf869daae
  • Pointer size: 131 Bytes
  • Size of remote file: 986 kB
image_2.png ADDED

Git LFS Details

  • SHA256: 8ac8aefe41f7f2247ee44fb31040fb2844a75e2a3270cd389279ff9372b98d0d
  • Pointer size: 132 Bytes
  • Size of remote file: 1.02 MB
image_3.png ADDED

Git LFS Details

  • SHA256: c0bfcd4453e82f6c937e0eea7bb2bc169b5091314a90cdbf478170ec0e89c756
  • Pointer size: 132 Bytes
  • Size of remote file: 1 MB
inference.py ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import torch
2
+ from diffusers import StableDiffusion3Pipeline
3
+ from diffusers import AutoPipelineForText2Image
4
+ from safetensors.torch import load_file
5
+
6
+ torch.backends.cuda.enable_mem_efficient_sdp(False)
7
+ torch.backends.cuda.enable_flash_sdp(False)
8
+
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')
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",
14
+ guidance_scale = 5.0, negative_prompt = "blurry").images[0]
15
+
16
+ image.save("canola_12_5_1.png")
log.txt ADDED
File without changes
logs/dreambooth-sd3-lora/1743823161.0409586/events.out.tfevents.1743823161.g338.1131650.1 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a7b580a6b11ab72f28851627e17b8fab0251be4dcc56bb7e0c3b539b327914bb
3
+ size 3778
logs/dreambooth-sd3-lora/1743823161.045078/hparams.yml ADDED
@@ -0,0 +1,77 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ adam_beta1: 0.9
2
+ adam_beta2: 0.999
3
+ adam_epsilon: 1.0e-08
4
+ adam_weight_decay: 0.0001
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 @@
 
 
 
 
 
 
 
0
  0%| | 0/28 [00:00<?, ?it/s]
1
  4%|β–Ž | 1/28 [00:02<00:56, 2.08s/it]
2
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
3
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
4
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.90s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.92s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.92s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:28, 1.93s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.93s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.93s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:41<00:11, 1.94s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:43<00:09, 1.94s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.95s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:56, 2.08s/it]
10
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
11
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
12
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.90s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.92s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.92s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:28, 1.93s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.93s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.93s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:41<00:11, 1.94s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:43<00:09, 1.94s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.95s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 27/28 [00:51<00:01, 1.95s/it]
slurm-6020660.out ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
0
  0%| | 0/28 [00:00<?, ?it/s]
1
  4%|β–Ž | 1/28 [00:02<00:56, 2.08s/it]
2
  7%|β–‹ | 2/28 [00:03<00:39, 1.53s/it]
3
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
4
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.90s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.92s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.92s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.93s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.94s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.94s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.94s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.95s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.95s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:56, 2.08s/it]
10
  7%|β–‹ | 2/28 [00:03<00:39, 1.53s/it]
11
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
12
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.90s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.92s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.92s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.93s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.94s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.94s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.94s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.95s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.95s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 27/28 [00:51<00:01, 1.95s/it]
slurm-6020661.out ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
0
  0%| | 0/28 [00:00<?, ?it/s]
1
  4%|β–Ž | 1/28 [00:02<00:56, 2.11s/it]
2
  7%|β–‹ | 2/28 [00:03<00:40, 1.54s/it]
3
  11%|β–ˆ | 3/28 [00:05<00:43, 1.73s/it]
4
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.81s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.89s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.91s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.92s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.94s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.94s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.94s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:43<00:09, 1.94s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.95s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.95s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.95s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:56, 2.11s/it]
10
  7%|β–‹ | 2/28 [00:03<00:40, 1.54s/it]
11
  11%|β–ˆ | 3/28 [00:05<00:43, 1.73s/it]
12
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.81s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.89s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.91s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.92s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.94s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.94s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.94s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:43<00:09, 1.94s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.95s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.95s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.95s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:04<01:52, 4.16s/it]
2
  7%|β–‹ | 2/28 [00:05<01:02, 2.39s/it]
3
  11%|β–ˆ | 3/28 [00:07<00:54, 2.18s/it]
4
  14%|β–ˆβ– | 4/28 [00:09<00:50, 2.08s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:11<00:46, 2.03s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:13<00:43, 1.99s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:14<00:41, 1.97s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:16<00:39, 1.96s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:18<00:37, 1.95s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:20<00:35, 1.95s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:22<00:32, 1.94s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:24<00:31, 1.94s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:26<00:29, 1.94s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:28<00:27, 1.94s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:30<00:25, 1.94s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:32<00:23, 1.94s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:34<00:21, 1.94s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:36<00:19, 1.95s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:38<00:17, 1.94s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:40<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:42<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:44<00:11, 1.94s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:46<00:09, 1.94s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:47<00:07, 1.95s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:49<00:05, 1.96s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:51<00:03, 1.96s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:04<01:52, 4.16s/it]
10
  7%|β–‹ | 2/28 [00:05<01:02, 2.39s/it]
11
  11%|β–ˆ | 3/28 [00:07<00:54, 2.18s/it]
12
  14%|β–ˆβ– | 4/28 [00:09<00:50, 2.08s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:11<00:46, 2.03s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:13<00:43, 1.99s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:14<00:41, 1.97s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:16<00:39, 1.96s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:18<00:37, 1.95s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:20<00:35, 1.95s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:22<00:32, 1.94s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:24<00:31, 1.94s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:26<00:29, 1.94s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:28<00:27, 1.94s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:30<00:25, 1.94s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:32<00:23, 1.94s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:34<00:21, 1.94s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:36<00:19, 1.95s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:38<00:17, 1.94s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:40<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:42<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:44<00:11, 1.94s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:46<00:09, 1.94s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:47<00:07, 1.95s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:49<00:05, 1.96s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:51<00:03, 1.96s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:56, 2.09s/it]
2
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
3
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
4
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.81s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.87s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:11<00:41, 1.90s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:40, 1.91s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.92s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.93s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.93s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:28, 1.93s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.93s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.95s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.94s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:56, 2.09s/it]
10
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
11
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
12
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.81s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.87s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:11<00:41, 1.90s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:40, 1.91s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.92s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.93s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.93s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.93s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:28, 1.93s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.93s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.95s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.94s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:55, 2.07s/it]
2
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
3
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
4
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:40, 1.91s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.93s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.94s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.94s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.94s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.94s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.94s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.94s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.94s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.95s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.95s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:55, 2.07s/it]
10
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
11
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
12
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:40, 1.91s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.93s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.94s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.94s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.94s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:30, 1.94s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.94s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.94s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.94s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.94s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.95s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.95s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:56, 2.08s/it]
2
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
3
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
4
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.90s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.92s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.93s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:31, 1.94s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.95s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.95s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.95s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.95s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.95s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.95s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.95s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.94s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.95s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.95s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:56, 2.08s/it]
10
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
11
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
12
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.90s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.92s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.93s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:31, 1.94s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.95s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.95s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.95s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.95s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.95s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.95s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.95s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:44<00:09, 1.94s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.95s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.95s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:55, 2.07s/it]
2
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
3
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
4
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
5
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
6
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
7
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.89s/it]
8
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
9
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.91s/it]
10
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.92s/it]
11
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
12
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:31, 1.94s/it]
13
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.95s/it]
14
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.95s/it]
15
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.95s/it]
16
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
17
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
18
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.95s/it]
19
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
20
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
21
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
22
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
23
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:43<00:09, 1.94s/it]
24
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
25
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
26
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
27
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 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–Ž | 1/28 [00:02<00:55, 2.07s/it]
10
  7%|β–‹ | 2/28 [00:03<00:39, 1.52s/it]
11
  11%|β–ˆ | 3/28 [00:05<00:42, 1.71s/it]
12
  14%|β–ˆβ– | 4/28 [00:07<00:43, 1.80s/it]
13
  18%|β–ˆβ–Š | 5/28 [00:09<00:42, 1.85s/it]
14
  21%|β–ˆβ–ˆβ– | 6/28 [00:10<00:41, 1.88s/it]
15
  25%|β–ˆβ–ˆβ–Œ | 7/28 [00:12<00:39, 1.89s/it]
16
  29%|β–ˆβ–ˆβ–Š | 8/28 [00:14<00:38, 1.91s/it]
17
  32%|β–ˆβ–ˆβ–ˆβ– | 9/28 [00:16<00:36, 1.91s/it]
18
  36%|β–ˆβ–ˆβ–ˆβ–Œ | 10/28 [00:18<00:34, 1.92s/it]
19
  39%|β–ˆβ–ˆβ–ˆβ–‰ | 11/28 [00:20<00:32, 1.93s/it]
20
  43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 12/28 [00:22<00:31, 1.94s/it]
21
  46%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 13/28 [00:24<00:29, 1.95s/it]
22
  50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 14/28 [00:26<00:27, 1.95s/it]
23
  54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 15/28 [00:28<00:25, 1.95s/it]
24
  57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 16/28 [00:30<00:23, 1.94s/it]
25
  61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 17/28 [00:32<00:21, 1.94s/it]
26
  64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 18/28 [00:34<00:19, 1.95s/it]
27
  68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 19/28 [00:36<00:17, 1.94s/it]
28
  71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 20/28 [00:38<00:15, 1.94s/it]
29
  75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/28 [00:40<00:13, 1.94s/it]
30
  79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 22/28 [00:42<00:11, 1.94s/it]
31
  82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/28 [00:43<00:09, 1.94s/it]
32
  86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/28 [00:45<00:07, 1.94s/it]
33
  89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 25/28 [00:47<00:05, 1.94s/it]
34
  93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 26/28 [00:49<00:03, 1.94s/it]
35
  96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 27/28 [00:51<00:01, 1.94s/it]