From 3d0070638fa5737e276f6a53f6bcd572c586f603 Mon Sep 17 00:00:00 2001 From: NeuralSamurAI <164533106+NeuralSamurAI@users.noreply.github.com> Date: Sun, 11 Aug 2024 00:07:29 -0400 Subject: [PATCH] Delete token_counter.py --- token_counter.py | 49 ------------------------------------------------ 1 file changed, 49 deletions(-) delete mode 100644 token_counter.py diff --git a/token_counter.py b/token_counter.py deleted file mode 100644 index aae7216..0000000 --- a/token_counter.py +++ /dev/null @@ -1,49 +0,0 @@ -from transformers import T5Tokenizer, CLIPTokenizer - -class TokenCounter: - @classmethod - def INPUT_TYPES(cls): - return { - "required": { - "text": ("STRING", {"multiline": True}), - "model": ("MODEL",), - }, - "optional": { - "use_clip": ("BOOLEAN", {"default": False}), - } - } - - RETURN_TYPES = ("INT", "INT") - RETURN_NAMES = ("t5_token_count", "clip_token_count") - FUNCTION = "count_tokens" - - CATEGORY = "utils" - - def count_tokens(self, text, model, use_clip=False): - if not isinstance(text, str): - raise ValueError("Input text must be a string") - - t5_tokenizer = self.get_t5_tokenizer(model) - t5_tokens = t5_tokenizer.encode(text) - t5_count = len(t5_tokens) - - if use_clip: - clip_tokenizer = self.get_clip_tokenizer(model) - clip_tokens = clip_tokenizer.encode(text) - clip_count = len(clip_tokens) - else: - clip_count = None - - return t5_count, clip_count - - def get_t5_tokenizer(self, model): - try: - return model.model.t5_tokenizer - except AttributeError: - return T5Tokenizer.from_pretrained("t5-xxl", local_files_only=True) - - def get_clip_tokenizer(self, model): - try: - return model.model.clip_tokenizer - except AttributeError: - return CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14", local_files_only=True)