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AUTOMATIC 2023-01-07 07:48:44 +03:00
parent 08066676a4
commit 1740c33547
1 changed files with 16 additions and 5 deletions
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21
modules/sd_hijack_clip.py
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@ -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