feat: upload berrynew dataset and logs

logs/20230521140616/wandb/debug.log

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logs/20230521140616/wandb/run-20230521_140805-bqip7r0k/files/config.yaml

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logs/20230521140616/wandb/run-20230521_140805-bqip7r0k/files/output.log

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+
+epoch 1/10
+saving checkpoint: /content/LoRA/output/berrynew-000001.safetensors
+generating sample images at step / サンプル画像生成 ステップ: 158
+prompt: masterpiece, best quality, 1girl, a woman in a pink dress holding a bottle of perfume
+negative_prompt: (worst quality, low quality:1.4)
+height: 768
+width: 512
+sample_steps: 28
+scale: 7
+
+
+
+
+
+
+
+ 96% 53/55 [00:15<00:00,  3.43it/s]
+prompt: masterpiece, best quality, 1girl, a woman in a plaid shirt and shorts
+negative_prompt: (worst quality, low quality:1.4)
+height: 768
+width: 512
+sample_steps: 28
+100% 55/55 [00:16<00:00,  3.42it/s]
+
+
+Traceback (most recent call last):]
+  File "/content/kohya-trainer/train_network.py", line 782, in <module>
+    train(args)
+  File "/content/kohya-trainer/train_network.py", line 700, in train
+    train_util.sample_images(accelerator, args, epoch + 1, global_step, accelerator.device, vae, tokenizer, text_encoder, unet)
+  File "/content/kohya-trainer/library/train_util.py", line 3450, in sample_images
+    image = pipeline(
+  File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
+    return func(*args, **kwargs)
+  File "/content/kohya-trainer/library/lpw_stable_diffusion.py", line 863, in __call__
+    latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample
+  File "/usr/local/lib/python3.10/dist-packages/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py", line 225, in step
+    step_index = self.index_for_timestep(timestep)
+  File "/usr/local/lib/python3.10/dist-packages/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py", line 84, in index_for_timestep
+    indices = (self.timesteps == timestep).nonzero()
+KeyboardInterrupt
+╭───────────────────── Traceback (most recent call last) ──────────────────────╮
+│ /content/kohya-trainer/train_network.py:782 in <module>                      │
+│                                                                              │
+│   779 │   args = parser.parse_args()                                         │
+│   780 │   args = train_util.read_config_from_file(args, parser)              │
+│   781 │                                                                      │
+│ ❱ 782 │   train(args)                                                        │
+│   783                                                                        │
+│                                                                              │
+│ /content/kohya-trainer/train_network.py:700 in train                         │
+│                                                                              │
+│   697 │   │   │   │   if args.save_state:                                    │
+│   698 │   │   │   │   │   train_util.save_and_remove_state_on_epoch_end(args │
+│   699 │   │                                                                  │
+│ ❱ 700 │   │   train_util.sample_images(accelerator, args, epoch + 1, global_ │
+│   701 │   │                                                                  │
+│   702 │   │   # end of epoch                                                 │
+│   703                                                                        │
+│                                                                              │
+│ /content/kohya-trainer/library/train_util.py:3450 in sample_images           │
+│                                                                              │
+│   3447 │   │   │   │   print(f"width: {width}")                              │
+│   3448 │   │   │   │   print(f"sample_steps: {sample_steps}")                │
+│   3449 │   │   │   │   print(f"scale: {scale}")                              │
+│ ❱ 3450 │   │   │   │   image = pipeline(                                     │
+│   3451 │   │   │   │   │   prompt=prompt,                                    │
+│   3452 │   │   │   │   │   height=height,                                    │
+│   3453 │   │   │   │   │   width=width,                                      │
+│                                                                              │
+│ /usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py:115 in    │
+│ decorate_context                                                             │
+│                                                                              │
+│   112 │   @functools.wraps(func)                                             │
+│   113 │   def decorate_context(*args, **kwargs):                             │
+│   114 │   │   with ctx_factory():                                            │
+│ ❱ 115 │   │   │   return func(*args, **kwargs)                               │
+│   116 │                                                                      │
+│   117 │   return decorate_context                                            │
+│   118                                                                        │
+│                                                                              │
+│ /content/kohya-trainer/library/lpw_stable_diffusion.py:863 in __call__       │
+│                                                                              │
+│    860 │   │   │   │   noise_pred = noise_pred_uncond + guidance_scale * (no │
+│    861 │   │   │                                                             │
+│    862 │   │   │   # compute the previous noisy sample x_t -> x_t-1          │
+│ ❱  863 │   │   │   latents = self.scheduler.step(noise_pred, t, latents, **e │
+│    864 │   │   │                                                             │
+│    865 │   │   │   if mask is not None:                                      │
+│    866 │   │   │   │   # masking                                             │
+│                                                                              │
+│ /usr/local/lib/python3.10/dist-packages/diffusers/schedulers/scheduling_k_dp │
+│ m_2_ancestral_discrete.py:225 in step                                        │
+│                                                                              │
+│   222 │   │   │   [`~schedulers.scheduling_utils.SchedulerOutput`] if `retur │
+│   223 │   │   │   returning a tuple, the first element is the sample tensor. │
+│   224 │   │   """                                                            │
+│ ❱ 225 │   │   step_index = self.index_for_timestep(timestep)                 │
+│   226 │   │                                                                  │
+│   227 │   │   if self.state_in_first_order:                                  │
+│   228 │   │   │   sigma = self.sigmas[step_index]                            │
+│                                                                              │
+│ /usr/local/lib/python3.10/dist-packages/diffusers/schedulers/scheduling_k_dp │
+│ m_2_ancestral_discrete.py:84 in index_for_timestep                           │
+│                                                                              │
+│    81 │   │   self.set_timesteps(num_train_timesteps, None, num_train_timest │
+│    82 │                                                                      │
+│    83 │   def index_for_timestep(self, timestep):                            │
+│ ❱  84 │   │   indices = (self.timesteps == timestep).nonzero()               │
+│    85 │   │   if self.state_in_first_order:                                  │
+│    86 │   │   │   pos = -1                                                   │
+│    87 │   │   else:                                                          │
+╰──────────────────────────────────────────────────────────────────────────────╯
+KeyboardInterrupt

logs/20230521140616/wandb/run-20230521_140805-bqip7r0k/files/requirements.txt

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+epoch 1/10
+Traceback (most recent call last):
+  File "/content/kohya-trainer/train_network.py", line 782, in <module>
+    train(args)
+  File "/content/kohya-trainer/train_network.py", line 628, in train
+    accelerator.backward(loss)
+  File "/usr/local/lib/python3.10/dist-packages/accelerate/accelerator.py", line 1314, in backward
+    self.scaler.scale(loss).backward(**kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/_tensor.py", line 487, in backward
+    torch.autograd.backward(
+  File "/usr/local/lib/python3.10/dist-packages/torch/autograd/__init__.py", line 200, in backward
+    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+KeyboardInterrupt
+╭───────────────────── Traceback (most recent call last) ──────────────────────╮
+│ /content/kohya-trainer/train_network.py:782 in <module>                      │
+│                                                                              │
+│   779 │   args = parser.parse_args()                                         │
+│   780 │   args = train_util.read_config_from_file(args, parser)              │
+│   781 │                                                                      │
+│ ❱ 782 │   train(args)                                                        │
+│   783                                                                        │
+│                                                                              │
+│ /content/kohya-trainer/train_network.py:628 in train                         │
+│                                                                              │
+│   625 │   │   │   │                                                          │
+│   626 │   │   │   │   loss = loss.mean()  # 平均なのでbatch_sizeで割る必要な │
+│   627 │   │   │   │                                                          │
+│ ❱ 628 │   │   │   │   accelerator.backward(loss)                             │
+│   629 │   │   │   │   if accelerator.sync_gradients and args.max_grad_norm ! │
+│   630 │   │   │   │   │   params_to_clip = network.get_trainable_params()    │
+│   631 │   │   │   │   │   accelerator.clip_grad_norm_(params_to_clip, args.m │
+│                                                                              │
+│ /usr/local/lib/python3.10/dist-packages/accelerate/accelerator.py:1314 in    │
+│ backward                                                                     │
+│                                                                              │
+│   1311 │   │   elif self.distributed_type == DistributedType.MEGATRON_LM:    │
+│   1312 │   │   │   return                                                    │
+│   1313 │   │   elif self.scaler is not None:                                 │
+│ ❱ 1314 │   │   │   self.scaler.scale(loss).backward(**kwargs)                │
+│   1315 │   │   else:                                                         │
+│   1316 │   │   │   loss.backward(**kwargs)                                   │
+│   1317                                                                       │
+│                                                                              │
+│ /usr/local/lib/python3.10/dist-packages/torch/_tensor.py:487 in backward     │
+│                                                                              │
+│    484 │   │   │   │   create_graph=create_graph,                            │
+│    485 │   │   │   │   inputs=inputs,                                        │
+│    486 │   │   │   )                                                         │
+│ ❱  487 │   │   torch.autograd.backward(                                      │
+│    488 │   │   │   self, gradient, retain_graph, create_graph, inputs=inputs │
+│    489 │   │   )                                                             │
+│    490                                                                       │
+│                                                                              │
+│ /usr/local/lib/python3.10/dist-packages/torch/autograd/__init__.py:200 in    │
+│ backward                                                                     │
+│                                                                              │
+│   197 │   # The reason we repeat same the comment below is that              │
+│   198 │   # some Python versions print out the first line of a multi-line fu │
+│   199 │   # calls in the traceback and some print out the last line          │
+│ ❱ 200 │   Variable._execution_engine.run_backward(  # Calls into the C++ eng │
+│   201 │   │   tensors, grad_tensors_, retain_graph, create_graph, inputs,    │
+│   202 │   │   allow_unreachable=True, accumulate_grad=True)  # Calls into th │
+│   203                                                                        │
+╰──────────────────────────────────────────────────────────────────────────────╯
+KeyboardInterrupt

logs/20230521141042/wandb/run-20230521_141208-kge1g833/files/requirements.txt

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logs/20230521141042/wandb/run-20230521_141208-kge1g833/files/wandb-metadata.json

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+
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+
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+100% 55/55 [00:16<00:00,  3.34it/s]

logs/20230521141315/wandb/run-20230521_141446-gcrcagn3/files/requirements.txt

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logs/20230521141315/wandb/run-20230521_141446-gcrcagn3/files/wandb-metadata.json

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logs/20230521141315/wandb/run-20230521_141446-gcrcagn3/logs/debug.log

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