TyperError in VersatileDiffusionPipeline: get_down_block() got an unexpected keyword argument 'transformer_layers_per_block' #5998
Description
Describe the bug
I wan to use the VersatileDiffusionPipeline but I get an error when loading the model with from_pretrained().
TypeError Traceback (most recent call last)
[<ipython-input-7-2673c81923ce>](https://localhost:8080/#) in <cell line: 1>()
----> 1 vdm = diffusers.VersatileDiffusionPipeline.from_pretrained(
2 "shi-labs/versatile-diffusion",)
3
4 vdm.remove_unused_weights()
5 vdm = vdm.to("cuda")
5 frames
[/usr/local/lib/python3.10/dist-packages/diffusers/pipelines/pipeline_utils.py](https://localhost:8080/#) in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
1263 else:
1264 # load sub model
-> 1265 loaded_sub_model = load_sub_model(
1266 library_name=library_name,
1267 class_name=class_name,
[/usr/local/lib/python3.10/dist-packages/diffusers/pipelines/pipeline_utils.py](https://localhost:8080/#) in load_sub_model(library_name, class_name, importable_classes, pipelines, is_pipeline_module, pipeline_class, torch_dtype, provider, sess_options, device_map, max_memory, offload_folder, offload_state_dict, model_variants, name, from_flax, variant, low_cpu_mem_usage, cached_folder, revision)
518 # check if the module is in a subdirectory
519 if os.path.isdir(os.path.join(cached_folder, name)):
--> 520 loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
521 else:
522 # else load from the root directory
[/usr/local/lib/python3.10/dist-packages/diffusers/models/modeling_utils.py](https://localhost:8080/#) in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
879 }
880 else:
--> 881 model = cls.from_config(config, **unused_kwargs)
882
883 state_dict = load_state_dict(model_file, variant=variant)
[/usr/local/lib/python3.10/dist-packages/diffusers/configuration_utils.py](https://localhost:8080/#) in from_config(cls, config, return_unused_kwargs, **kwargs)
253
254 # Return model and optionally state and/or unused_kwargs
--> 255 model = cls(**init_dict)
256
257 # make sure to also save config parameters that might be used for compatible classes
[/usr/local/lib/python3.10/dist-packages/diffusers/configuration_utils.py](https://localhost:8080/#) in inner_init(self, *args, **kwargs)
643 new_kwargs = {**config_init_kwargs, **new_kwargs}
644 getattr(self, "register_to_config")(**new_kwargs)
--> 645 init(self, *args, **init_kwargs)
646
647 return inner_init
[/usr/local/lib/python3.10/dist-packages/diffusers/pipelines/versatile_diffusion/modeling_text_unet.py](https://localhost:8080/#) in __init__(self, sample_size, in_channels, out_channels, center_input_sample, flip_sin_to_cos, freq_shift, down_block_types, mid_block_type, up_block_types, only_cross_attention, block_out_channels, layers_per_block, downsample_padding, mid_block_scale_factor, dropout, act_fn, norm_num_groups, norm_eps, cross_attention_dim, transformer_layers_per_block, reverse_transformer_layers_per_block, encoder_hid_dim, encoder_hid_dim_type, attention_head_dim, num_attention_heads, dual_cross_attention, use_linear_projection, class_embed_type, addition_embed_type, addition_time_embed_dim, num_class_embeds, upcast_attention, resnet_time_scale_shift, resnet_skip_time_act, resnet_out_scale_factor, time_embedding_type, time_embedding_dim, time_embedding_act_fn, timestep_post_act, time_cond_proj_dim, conv_in_kernel, conv_out_kernel, projection_class_embeddings_input_dim, attention_type, class_embeddings_concat, mid_block_only_cross_attention, cross_attention_norm, addition_embed_type_num_heads)
648 is_final_block = i == len(block_out_channels) - 1
649
--> 650 down_block = get_down_block(
651 down_block_type,
652 num_layers=layers_per_block[i],
TypeError: get_down_block() got an unexpected keyword argument 'transformer_layers_per_block'
Reproduction
import diffusers
import torch
vdm = diffusers.VersatileDiffusionPipeline.from_pretrained(
"shi-labs/versatile-diffusion", torch_dtype=torch.float16)
Logs
No response
System Info
diffusers=0.24.0
torch=2.1.0+cu118
torchvision=0.16.0+cu118
Python 3.10.12