RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 4 but got size 1 for tensor number 1 in the list.

[alexisrolland]

I am trying to use compel with batches of long prompts / negative prompts. Here is the code:

import torch
from diffusers import StableDiffusionPipeline
from compel import Compel

pipeline = StableDiffusionPipeline.from_pretrained("/model/path")
compel = Compel(tokenizer=pipeline.tokenizer, text_encoder=pipeline.text_encoder, truncate_long_prompts=False)

prompts = [
    "best quality, masterpiece, highres, 1girl,china dress,Beautiful face,upon_body, tyndall effect,photorealistic, dark studio, rim lighting, two tone lighting,(high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, volumetric lighting, candid, Photograph, high resolution, 4k, 8k, Bokeh",
    "best quality, masterpiece, highres, 1girl,china dress,Beautiful face,upon_body, tyndall effect,photorealistic, dark studio, rim lighting, two tone lighting,(high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, volumetric lighting, candid, Photograph, high resolution, 4k, 8k, Bokeh",
    "best quality, masterpiece, highres, 1girl,china dress,Beautiful face,upon_body, tyndall effect,photorealistic, dark studio, rim lighting, two tone lighting,(high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, volumetric lighting, candid, Photograph, high resolution, 4k, 8k, Bokeh",
    "best quality, masterpiece, highres, 1girl,china dress,Beautiful face,upon_body, tyndall effect,photorealistic, dark studio, rim lighting, two tone lighting,(high detailed skin:1.2), 8k uhd, dslr, soft lighting, high quality, volumetric lighting, candid, Photograph, high resolution, 4k, 8k, Bokeh"
]
negative_prompts = ["blur", "blur", "blur", "blur"]

prompt_embeds = compel(prompts)
negative_prompt_embeds = compel(negative_prompts)

[prompt_embeds, negative_prompt_embeds] = compel.pad_conditioning_tensors_to_same_length([prompt_embeds, negative_prompt_embeds])

The error returned by this last line is:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.10/site-packages/compel/compel.py", line 111, in pad_conditioning_tensors_to_same_length
    c = torch.cat([c, empty_z], dim=1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 4 but got size 1 for tensor number 1 in the list.

[damian0815]

ahh. seems like pad_conditioning_tensors_to_same_length doesn't support batching input like that. i'll take a look at fixing that for the next release. in the meantime you could manually unpack the 4x77x768 tensors returned by compel() to lists of 4 1x77x768 tensors ..?

[damian0815]

should be fixed with compel 1.0.2