kilik128
commented
5 days ago got this log == =
2024-11-16 23:46:26.851310: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-11-16 23:46:27.087792: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-11-16 23:46:27.149776: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-11-16 23:46:27.525214: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-11-16 23:46:29.620736: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
Load default preset failed.
[Errno 2] No such file or directory: '/content/VistaDream/presets/default.json'
No presets found.
No presets found.
Total VRAM 15102 MB, total RAM 12979 MB
Set vram state to: NORMAL_VRAM
Always offload VRAM
Device: cuda:0 Tesla T4 : native
VAE dtype: torch.float32
Using pytorch cross attention
Refiner unloaded.
model_type EPS
UNet ADM Dimension 2816
Using pytorch attention in VAE
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
Using pytorch attention in VAE
extra {'cond_stage_model.clip_l.logit_scale', 'cond_stage_model.clip_l.text_projection'}
left over keys: dict_keys(['cond_stage_model.clip_l.transformer.text_model.embeddings.position_ids'])
Base model loaded: /content/VistaDream/tools/Fooocus/models/checkpoints/juggernautXL_v8Rundiffusion.safetensors
VAE loaded: None
Request to load LoRAs [] for model [/content/VistaDream/tools/Fooocus/models/checkpoints/juggernautXL_v8Rundiffusion.safetensors].
Fooocus V2 Expansion: Vocab with 642 words.
/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
return self.fget.get(instance, owner)()
Fooocus Expansion engine loaded for cuda:0, use_fp16 = True.
Requested to load SDXLClipModel
Requested to load GPT2LMHeadModel
Loading 2 new models
[Fooocus Model Management] Moving model(s) has taken 0.60 seconds
Started worker with PID 38384
Loading config tools/OneFormer/configs/ade20k/dinat/coco_pretrain_oneformer_dinat_large_bs16_160k_1280x1280.yaml with yaml.unsafe_load. Your machine may be at risk if the file contains malicious content.
Loading config tools/OneFormer/configs/ade20k/dinat/../Base-ADE20K-UnifiedSegmentation.yaml with yaml.unsafe_load. Your machine may be at risk if the file contains malicious content.
The checkpoint state_dict contains keys that are not used by the model:
text_encoder.positional_embedding
text_encoder.transformer.resblocks.0.attn.{in_proj_bias, in_proj_weight}
text_encoder.transformer.resblocks.0.attn.out_proj.{bias, weight}
text_encoder.transformer.resblocks.0.ln_1.{bias, weight}
text_encoder.transformer.resblocks.0.mlp.c_fc.{bias, weight}
text_encoder.transformer.resblocks.0.mlp.c_proj.{bias, weight}
text_encoder.transformer.resblocks.0.ln_2.{bias, weight}
text_encoder.transformer.resblocks.1.attn.{in_proj_bias, in_proj_weight}
text_encoder.transformer.resblocks.1.attn.out_proj.{bias, weight}
text_encoder.transformer.resblocks.1.ln_1.{bias, weight}
text_encoder.transformer.resblocks.1.mlp.c_fc.{bias, weight}
text_encoder.transformer.resblocks.1.mlp.c_proj.{bias, weight}
text_encoder.transformer.resblocks.1.ln_2.{bias, weight}
text_encoder.transformer.resblocks.2.attn.{in_proj_bias, in_proj_weight}
text_encoder.transformer.resblocks.2.attn.out_proj.{bias, weight}
text_encoder.transformer.resblocks.2.ln_1.{bias, weight}
text_encoder.transformer.resblocks.2.mlp.c_fc.{bias, weight}
text_encoder.transformer.resblocks.2.mlp.c_proj.{bias, weight}
text_encoder.transformer.resblocks.2.ln_2.{bias, weight}
text_encoder.transformer.resblocks.3.attn.{in_proj_bias, in_proj_weight}
text_encoder.transformer.resblocks.3.attn.out_proj.{bias, weight}
text_encoder.transformer.resblocks.3.ln_1.{bias, weight}
text_encoder.transformer.resblocks.3.mlp.c_fc.{bias, weight}
text_encoder.transformer.resblocks.3.mlp.c_proj.{bias, weight}
text_encoder.transformer.resblocks.3.ln_2.{bias, weight}
text_encoder.transformer.resblocks.4.attn.{in_proj_bias, in_proj_weight}
text_encoder.transformer.resblocks.4.attn.out_proj.{bias, weight}
text_encoder.transformer.resblocks.4.ln_1.{bias, weight}
text_encoder.transformer.resblocks.4.mlp.c_fc.{bias, weight}
text_encoder.transformer.resblocks.4.mlp.c_proj.{bias, weight}
text_encoder.transformer.resblocks.4.ln_2.{bias, weight}
text_encoder.transformer.resblocks.5.attn.{in_proj_bias, in_proj_weight}
text_encoder.transformer.resblocks.5.attn.out_proj.{bias, weight}
text_encoder.transformer.resblocks.5.ln_1.{bias, weight}
text_encoder.transformer.resblocks.5.mlp.c_fc.{bias, weight}
text_encoder.transformer.resblocks.5.mlp.c_proj.{bias, weight}
text_encoder.transformer.resblocks.5.ln_2.{bias, weight}
text_encoder.ln_final.{bias, weight}
text_encoder.token_embedding.weight
text_projector.layers.0.{bias, weight}
text_projector.layers.1.{bias, weight}
prompt_ctx.weight
backbone.levels.0.blocks.0.attn.rpb
backbone.levels.0.blocks.1.attn.rpb
backbone.levels.0.blocks.2.attn.rpb
backbone.levels.1.blocks.0.attn.rpb
backbone.levels.1.blocks.1.attn.rpb
backbone.levels.1.blocks.2.attn.rpb
backbone.levels.1.blocks.3.attn.rpb
backbone.levels.2.blocks.0.attn.rpb
backbone.levels.2.blocks.1.attn.rpb
backbone.levels.2.blocks.2.attn.rpb
backbone.levels.2.blocks.3.attn.rpb
backbone.levels.2.blocks.4.attn.rpb
backbone.levels.2.blocks.5.attn.rpb
backbone.levels.2.blocks.6.attn.rpb
backbone.levels.2.blocks.7.attn.rpb
backbone.levels.2.blocks.8.attn.rpb
backbone.levels.2.blocks.9.attn.rpb
backbone.levels.2.blocks.10.attn.rpb
backbone.levels.2.blocks.11.attn.rpb
backbone.levels.2.blocks.12.attn.rpb
backbone.levels.2.blocks.13.attn.rpb
backbone.levels.2.blocks.14.attn.rpb
backbone.levels.2.blocks.15.attn.rpb
backbone.levels.2.blocks.16.attn.rpb
backbone.levels.2.blocks.17.attn.rpb
backbone.levels.3.blocks.0.attn.rpb
backbone.levels.3.blocks.1.attn.rpb
backbone.levels.3.blocks.2.attn.rpb
backbone.levels.3.blocks.3.attn.rpb
backbone.levels.3.blocks.4.attn.rpb
/usr/local/lib/python3.10/dist-packages/transformers/models/llava/configuration_llava.py:100: FutureWarning: The vocab_size argument is deprecated and will be removed in v4.42, since it can be inferred from the text_config. Passing this argument has no effect
warnings.warn(
Loading checkpoint shards: 100% 4/4 [00:07<00:00, 1.94s/it]
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
GeoVectorMatrix
hey anyone as colab install ? thank's