main_log.txt

The following values were not passed to `accelerate launch` and had defaults used instead:
	`--dynamo_backend` was set to a value of `'no'`
To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.
A matching Triton is not available, some optimizations will not be enabled.
Error caught was: No module named 'triton'
09/05/2023 22:46:04 - INFO - __main__ - Distributed environment: MULTI_GPU  Backend: nccl
Num processes: 1
Process index: 0
Local process index: 0
Device: cuda:0

Mixed precision type: fp16

You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.
You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.
{'attention_type'} was not found in config. Values will be initialized to default values.
09/05/2023 22:46:17 - INFO - __main__ - Initializing t2iadapter weights from unet
Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 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'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.11.layer_norm1.bias', 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'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'logit_scale', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight']
- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
/admin/home/suraj/code/muse-experiments/ctrlnet/train_t2i_adapter.py:1331: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
  logger.warn(
09/05/2023 22:46:22 - WARNING - __main__ - xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details.
wandb: Currently logged in as: psuraj. Use `wandb login --relogin` to force relogin
wandb: wandb version 0.15.9 is available!  To upgrade, please run:
wandb:  $ pip install wandb --upgrade
wandb: Tracking run with wandb version 0.12.21
wandb: Run data is saved locally in /admin/home/suraj/code/muse-experiments/ctrlnet/wandb/run-20230905_224634-25abmfuh
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run worthy-wave-64
wandb: ⭐️ View project at https://wandb.ai/psuraj/sd_xl_train_t2iadapter
wandb: 🚀 View run at https://wandb.ai/psuraj/sd_xl_train_t2iadapter/runs/25abmfuh
09/05/2023 22:46:38 - INFO - __main__ - ***** Running training *****
09/05/2023 22:46:38 - INFO - __main__ -   Num batches each epoch = 187504
09/05/2023 22:46:38 - INFO - __main__ -   Num Epochs = 1
09/05/2023 22:46:38 - INFO - __main__ -   Instantaneous batch size per device = 16
09/05/2023 22:46:38 - INFO - __main__ -   Total train batch size (w. parallel, distributed & accumulation) = 16
09/05/2023 22:46:38 - INFO - __main__ -   Gradient Accumulation steps = 1
09/05/2023 22:46:38 - INFO - __main__ -   Total optimization steps = 10
Checkpoint 'latest' does not exist. Starting a new training run.

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Steps:  10% 1/10 [00:12<01:54, 12.70s/it, loss=0.041, lr=1e-5]09/05/2023 22:46:52 - INFO - torch.nn.parallel.distributed - Reducer buckets have been rebuilt in this iteration.

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Steps: 100% 10/10 [00:50<00:00,  4.35s/it, loss=0.0824, lr=1e-5]09/05/2023 22:47:29 - INFO - __main__ - Running validation... 


Loading pipeline components...:   0% 0/7 [00:00<?, ?it/s]Loaded scheduler as EulerDiscreteScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-xl-base-1.0.
Loaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of stabilityai/stable-diffusion-xl-base-1.0.
Loaded tokenizer_2 as CLIPTokenizer from `tokenizer_2` subfolder of stabilityai/stable-diffusion-xl-base-1.0.


Loading pipeline components...:  71% 5/7 [00:00<00:00, 37.36it/s]Loaded text_encoder_2 as CLIPTextModelWithProjection from `text_encoder_2` subfolder of stabilityai/stable-diffusion-xl-base-1.0.
Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of stabilityai/stable-diffusion-xl-base-1.0.

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