From adc52fb8821a496bc8d78235bf10466b39df03e0 Mon Sep 17 00:00:00 2001
From: Volpeon <git@volpeon.ink>
Date: Sun, 1 Jan 2023 19:19:52 +0100
Subject: Updates

---
 models/clip/embeddings.py | 11 +++++++
 models/clip/tokenizer.py  | 76 +++++++++++++++++++++++++++++++++++++----------
 2 files changed, 71 insertions(+), 16 deletions(-)

(limited to 'models/clip')

diff --git a/models/clip/embeddings.py b/models/clip/embeddings.py
index f90e7c2..8602142 100644
--- a/models/clip/embeddings.py
+++ b/models/clip/embeddings.py
@@ -120,3 +120,14 @@ def patch_managed_embeddings(text_encoder: CLIPTextModel) -> ManagedCLIPTextEmbe
     text_embeddings = ManagedCLIPTextEmbeddings(text_encoder.config, text_encoder.text_model.embeddings)
     text_encoder.text_model.embeddings = text_embeddings
     return text_embeddings
+
+
+def unpatch_managed_embeddings(text_encoder: CLIPTextModel) -> CLIPTextEmbeddings:
+    text_encoder.text_model.embeddings.make_permanent()
+
+    text_embeddings = CLIPTextEmbeddings(text_encoder.config)
+    text_embeddings.token_embedding = text_encoder.text_model.embeddings.token_embedding
+    text_embeddings.position_embedding = text_encoder.text_model.embeddings.position_embedding
+    text_encoder.text_model.embeddings = text_embeddings
+
+    return text_embeddings
diff --git a/models/clip/tokenizer.py b/models/clip/tokenizer.py
index 37d69a9..ed9774e 100644
--- a/models/clip/tokenizer.py
+++ b/models/clip/tokenizer.py
@@ -1,11 +1,54 @@
 import copy
-from typing import NamedTuple, Union
+from typing import NamedTuple, Union, Literal
 
 import numpy as np
 
 from transformers import CLIPTokenizer
 
 
+def shuffle_all(tokens: list[int]):
+    if len(tokens) >= 2:
+        tokens = copy.copy(tokens)
+        np.random.shuffle(tokens)
+    return tokens
+
+
+def shuffle_leading(tokens: list[int]):
+    if len(tokens) >= 3:
+        subtokens = tokens[:-1]
+        np.random.shuffle(subtokens)
+        tokens = subtokens + tokens[-1:]
+    return tokens
+
+
+def shuffle_trailing(tokens: list[int]):
+    if len(tokens) >= 3:
+        subtokens = tokens[1:]
+        np.random.shuffle(subtokens)
+        tokens = tokens[:1] + subtokens
+    return tokens
+
+
+def shuffle_between(tokens: list[int]):
+    if len(tokens) >= 4:
+        subtokens = tokens[1:-1]
+        np.random.shuffle(subtokens)
+        tokens = tokens[:1] + subtokens + tokens[-1:]
+    return tokens
+
+
+def shuffle_none(tokens: list[int]):
+    return tokens
+
+
+def shuffle_auto(tokens: list[int]):
+    if len(tokens) >= 4:
+        return shuffle_between(tokens)
+    if len(tokens) >= 3:
+        return shuffle_trailing(tokens)
+    return shuffle_all(tokens)
+
+
 class MultiCLIPTokenizerItem(NamedTuple):
     token: str
     ids: list[int]
@@ -15,10 +58,21 @@ class MultiCLIPTokenizer(CLIPTokenizer):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.token_map: dict[int, list[int]] = {}
-        self.vector_shuffle = False
-
-    def set_use_vector_shuffle(self, enable: bool):
-        self.vector_shuffle = enable
+        self.vector_shuffle = shuffle_none
+
+    def set_use_vector_shuffle(self, algorithm: Union[bool, Literal["all", "trailing", "leading", "between", "off"]]):
+        if algorithm == "leading":
+            self.vector_shuffle = shuffle_leading
+        elif algorithm == "trailing":
+            self.vector_shuffle = shuffle_trailing
+        elif algorithm == "between":
+            self.vector_shuffle = shuffle_between
+        elif algorithm == "auto":
+            self.vector_shuffle = shuffle_auto
+        elif algorithm == True or algorithm == "all":
+            self.vector_shuffle = shuffle_all
+        else:
+            self.vector_shuffle = shuffle_none
 
     def add_multi_tokens(self, new_tokens: Union[str, list[str]], num_vectors: Union[int, list[int]] = 1) -> MultiCLIPTokenizerItem:
         if isinstance(new_tokens, list):
@@ -47,17 +101,7 @@ class MultiCLIPTokenizer(CLIPTokenizer):
         return MultiCLIPTokenizerItem(new_tokens, ids)
 
     def expand_id(self, id: int):
-        if id in self.token_map:
-            tokens = self.token_map[id]
-
-            if self.vector_shuffle and len(tokens) > 2:
-                subtokens = tokens[1:-1]
-                np.random.shuffle(subtokens)
-                tokens = tokens[:1] + subtokens + tokens[-1:]
-
-            return tokens
-        else:
-            return [id]
+        return self.vector_shuffle(self.token_map[id]) if id in self.token_map else [id]
 
     def expand_ids(self, ids: list[int]):
         return [
-- 
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