Description
Hey!
I am enjoying this library a lot. When I try Interpolation though I am getting this
`
Scheduler loaded
Stable Diffusion txt2img loaded
Starting interpolation experiment
interpolation.yaml
Output folder generated at ./experiments/2024-10-14_13-25-39_txt2img_interpolation
Interpolating 2 prompts.
D:\BEdi\spacewalk\lib\site-packages\diffusers\pipelines\stable_diffusion\pipeline_stable_diffusion.py:283: FutureWarning: _encode_prompt() is deprecated and it will be removed in a future version. Use encode_prompt() instead. Also, be aware that the output format changed from a concatenated tensor to a tuple.
deprecate("_encode_prompt()", "1.0.0", deprecation_message, standard_warn=False)
Traceback (most recent call last):
File "D:\BEdi\spacewalk\Stable-Diffusion-Latent-Space-Explorer\run_sd_experiment.py", line 65, in
main()
File "D:\BEdi\spacewalk\Stable-Diffusion-Latent-Space-Explorer\run_sd_experiment.py", line 61, in main
run_sd_experiment(args.exp_config, exp_cfg, sd_model)
File "D:\BEdi\spacewalk\Stable-Diffusion-Latent-Space-Explorer\run_sd_experiment.py", line 42, in run_sd_experiment
experiments.run_interpolation(cfg_path, exp_cfg, sd_model)
File "D:\BEdi\spacewalk\Stable-Diffusion-Latent-Space-Explorer\experiments.py", line 227, in run_interpolation
prompt_embed_1 = sd_model.load_prompt(
File "D:\BEdi\spacewalk\Stable-Diffusion-Latent-Space-Explorer\models.py", line 252, in load_prompt
return self.encode_prompt(prompt)
File "D:\BEdi\spacewalk\lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "D:\BEdi\spacewalk\Stable-Diffusion-Latent-Space-Explorer\models.py", line 177, in encode_prompt
prompt_embed = self.sd_pipeline._encode_prompt(
File "D:\BEdi\spacewalk\lib\site-packages\diffusers\pipelines\stable_diffusion\pipeline_stable_diffusion.py", line 285, in _encode_prompt
prompt_embeds_tuple = self.encode_prompt(
File "D:\BEdi\spacewalk\lib\site-packages\diffusers\pipelines\stable_diffusion\pipeline_stable_diffusion.py", line 393, in encode_prompt
prompt_embeds = self.text_encoder(text_input_ids.to(device), attention_mask=attention_mask)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\transformers\models\clip\modeling_clip.py", line 997, in forward
return self.text_model(
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\transformers\models\clip\modeling_clip.py", line 901, in forward
encoder_outputs = self.encoder(
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\transformers\models\clip\modeling_clip.py", line 824, in forward
layer_outputs = encoder_layer(
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\transformers\models\clip\modeling_clip.py", line 559, in forward
hidden_states, attn_weights = self.self_attn(
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\transformers\models\clip\modeling_clip.py", line 475, in forward
query_states = self.q_proj(hidden_states)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
File "D:\BEdi\spacewalk\lib\site-packages\torch\nn\modules\linear.py", line 118, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 must have the same dtype, but got Half and Double`