diff options
| -rw-r--r-- | modules/sd_hijack_clip.py | 21 |
1 files changed, 16 insertions, 5 deletions
diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py index 16aef76a..5520c9b2 100644 --- a/modules/sd_hijack_clip.py +++ b/modules/sd_hijack_clip.py @@ -3,7 +3,7 @@ from collections import namedtuple import torch
-from modules import prompt_parser, devices
+from modules import prompt_parser, devices, sd_hijack
from modules.shared import opts
@@ -22,14 +22,24 @@ class PromptChunk: PromptChunkFix = namedtuple('PromptChunkFix', ['offset', 'embedding'])
-"""This is a marker showing that textual inversion embedding's vectors have to placed at offset in the prompt chunk"""
+"""An object of this type is a marker showing that textual inversion embedding's vectors have to placed at offset in the prompt
+chunk. Thos objects are found in PromptChunk.fixes and, are placed into FrozenCLIPEmbedderWithCustomWordsBase.hijack.fixes, and finally
+are applied by sd_hijack.EmbeddingsWithFixes's forward function."""
class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
+ """A pytorch module that is a wrapper for FrozenCLIPEmbedder module. it enhances FrozenCLIPEmbedder, making it possible to
+ have unlimited prompt length and assign weights to tokens in prompt.
+ """
+
def __init__(self, wrapped, hijack):
super().__init__()
+
self.wrapped = wrapped
- self.hijack = hijack
+ """Original FrozenCLIPEmbedder module; can also be FrozenOpenCLIPEmbedder or xlmr.BertSeriesModelWithTransformation,
+ depending on model."""
+
+ self.hijack: sd_hijack.StableDiffusionModelHijack = hijack
self.chunk_length = 75
def empty_chunk(self):
@@ -55,7 +65,8 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): converts a batch of token ids (in python lists) into a single tensor with numeric respresentation of those tokens;
All python lists with tokens are assumed to have same length, usually 77.
if input is a list with B elements and each element has T tokens, expected output shape is (B, T, C), where C depends on
- model - can be 768 and 1024
+ model - can be 768 and 1024.
+ Among other things, this call will read self.hijack.fixes, apply it to its inputs, and clear it (setting it to None).
"""
raise NotImplementedError
@@ -113,7 +124,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): last_comma = len(chunk.tokens)
# this is when we are at the end of alloted 75 tokens for the current chunk, and the current token is not a comma. opts.comma_padding_backtrack
- # is a setting that specifies that is there is a comma nearby, the text after comma should be moved out of this chunk and into the next.
+ # is a setting that specifies that if there is a comma nearby, the text after the comma should be moved out of this chunk and into the next.
elif opts.comma_padding_backtrack != 0 and len(chunk.tokens) == self.chunk_length and last_comma != -1 and len(chunk.tokens) - last_comma <= opts.comma_padding_backtrack:
break_location = last_comma + 1
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