tweaks to documentation and call signature for advanced prompting

docs/features/PROMPTS.md

@@ -110,10 +110,15 @@ See the section below on "Prompt Blending" for more information about how this w
 
 ### Cross-Attention Control ('prompt2prompt')
 
-Generate an image with a given prompt and then paint over the image
-using the `prompt2prompt` syntax to substitute words in the original
-prompt for words in a new prompt. Based off [bloc97's
-colab](https://github.com/bloc97/CrossAttentionControl).
+Sometimes an image you generate is almost right, and you just want to
+change one detail without affecting the rest. You could use a photo editor and inpainting
+to overpaint the area, but that's a pain. Here's where `prompt2prompt`
+comes in handy.
+
+Generate an image with a given prompt, record the seed of the image,
+and then use the `prompt2prompt` syntax to substitute words in the
+original prompt for words in a new prompt. This works for `img2img` as well.
+
 
 * `a ("fluffy cat").swap("smiling dog") eating a hotdog`.
   * quotes optional: `a (fluffy cat).swap(smiling dog) eating a hotdog`.
@@ -125,6 +130,9 @@ colab](https://github.com/bloc97/CrossAttentionControl).
 * Convenience option `shape_freedom` (0-1) to specify how much "freedom" Stable Diffusion should have to change the shape of the subject being swapped. 
   * `a (cat).swap(dog, shape_freedom=0.5) eating a hotdog`.
 
+The `prompt2prompt` code is based off [bloc97's
+colab](https://github.com/bloc97/CrossAttentionControl).
+
 Note that `prompt2prompt` is not currently working with the runwayML
 inpainting model, and may never work due to the way this model is set
 up. If you attempt to use `prompt2prompt` you will get the original

ldm/invoke/conditioning.py

@@ -114,7 +114,7 @@ def get_uc_and_c_and_ec(prompt_string_uncleaned, model, log_tokens=False, skip_n
 
             conditioning = original_embeddings
             edited_conditioning = edited_embeddings
-            print('got edit_opcodes', edit_opcodes, 'options', edit_options)
+            print('>> got edit_opcodes', edit_opcodes, 'options', edit_options)
             cac_args = CrossAttentionControl.Arguments(
                 edited_conditioning = edited_conditioning,
                 edit_opcodes = edit_opcodes,

ldm/models/diffusion/shared_invokeai_diffusion.py

@@ -1,5 +1,5 @@
 from math import ceil
-from typing import Callable, Optional
+from typing import Callable, Optional, Union
 
 import torch
 
@@ -54,7 +54,7 @@ class InvokeAIDiffuserComponent:
         CrossAttentionControl.remove_cross_attention_control(self.model)
 
     def do_diffusion_step(self, x: torch.Tensor, sigma: torch.Tensor,
-                                   unconditioning: torch.Tensor, conditioning: torch.Tensor,
+                                   unconditioning: Union[torch.Tensor,dict], conditioning: Union[torch.Tensor,dict],
                                    unconditional_guidance_scale: float,
                                    step_index: int=None
                           ):