diff --git a/aiserver.py b/aiserver.py index f1461070..7e21dfe9 100644 --- a/aiserver.py +++ b/aiserver.py @@ -67,6 +67,17 @@ def new_init(self, *args, **kwargs): self.ncols = 99 tqdm.__init__ = new_init +# Fix some issues with the OPT tokenizer +from transformers import PreTrainedTokenizerBase +old_pretrainedtokenizerbase_from_pretrained = PreTrainedTokenizerBase.from_pretrained.__func__ +@classmethod +def new_pretrainedtokenizerbase_from_pretrained(cls, *args, **kwargs): + tokenizer = old_pretrainedtokenizerbase_from_pretrained(cls, *args, **kwargs) + tokenizer._koboldai_header = tokenizer.encode("") + tokenizer.add_bos_token = False + tokenizer.add_prefix_space = False + return tokenizer +PreTrainedTokenizerBase.from_pretrained = new_pretrainedtokenizerbase_from_pretrained #==================================================================# # Variables & Storage @@ -1697,6 +1708,9 @@ if(not vars.use_colab_tpu and vars.model not in ["InferKit", "Colab", "OAI", "Go # Then save the pytorch_model-#####-of-#####.bin files for filename in filenames: shutil.move(transformers.file_utils.get_from_cache(transformers.file_utils.hf_bucket_url(vars.model, filename, revision=vars.revision), cache_dir="cache", local_files_only=True), os.path.join("models/{}".format(vars.model.replace('/', '_')), filename)) + # If the model has a tokenizer_config.json, preserve the original file instead of using the one output by tokenizer.save_pretrained (using the file output by tokenizer.save_pretrained can break OPT-350M in transformers 4.20.0) + if(os.path.isfile(os.path.join("models/{}".format(vars.model.replace('/', '_')), "tokenizer_config.json"))): + shutil.move(transformers.file_utils.get_from_cache(transformers.file_utils.hf_bucket_url(vars.model, "tokenizer_config.json", revision=vars.revision), cache_dir="cache", local_files_only=True), os.path.join("models/{}".format(vars.model.replace('/', '_')), "tokenizer_config.json")) shutil.rmtree("cache/") if(vars.hascuda): @@ -3326,24 +3340,26 @@ def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None, global tokenizer tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache") + lnheader = len(tokenizer._koboldai_header) + # Calculate token budget prompttkns = tokenizer.encode(utils.encodenewlines(vars.comregex_ai.sub('', vars.prompt)), max_length=int(2e9), truncation=True) lnprompt = len(prompttkns) memtokens = tokenizer.encode(utils.encodenewlines(mem), max_length=int(2e9), truncation=True) lnmem = len(memtokens) - if(lnmem > vars.max_length - lnsp - vars.genamt - budget_deduction): + if(lnmem > vars.max_length - lnheader - lnsp - vars.genamt - budget_deduction): raise OverflowError("The memory in your story is too long. Please either write a shorter memory text or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt.") witokens = tokenizer.encode(utils.encodenewlines(winfo), max_length=int(2e9), truncation=True) lnwi = len(witokens) - if(lnmem + lnwi > vars.max_length - lnsp - vars.genamt - budget_deduction): + if(lnmem + lnwi > vars.max_length - lnheader - lnsp - vars.genamt - budget_deduction): raise OverflowError("The current active world info keys take up too many tokens. Please either write shorter world info, decrease World Info Depth or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt.") if(anotetxt != ""): anotetkns = tokenizer.encode(utils.encodenewlines(anotetxt), max_length=int(2e9), truncation=True) lnanote = len(anotetkns) - if(lnmem + lnwi + lnanote > vars.max_length - lnsp - vars.genamt - budget_deduction): + if(lnmem + lnwi + lnanote > vars.max_length - lnheader - lnsp - vars.genamt - budget_deduction): raise OverflowError("The author's note in your story is too long. Please either write a shorter author's note or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt.") if(vars.useprompt): @@ -3354,14 +3370,14 @@ def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None, lnsubmission = len(tokenizer.encode(utils.encodenewlines(vars.comregex_ai.sub('', submission)), max_length=int(2e9), truncation=True)) if submission is not None else 0 maybe_lnprompt = lnprompt if vars.useprompt and actionlen > 0 else 0 - if(lnmem + lnwi + lnanote + maybe_lnprompt + lnsubmission > vars.max_length - lnsp - vars.genamt - budget_deduction): + if(lnmem + lnwi + lnanote + maybe_lnprompt + lnsubmission > vars.max_length - lnheader - lnsp - vars.genamt - budget_deduction): raise OverflowError("Your submission is too long. Please either write a shorter submission or increase the Max Tokens setting. If you are using a soft prompt, additionally consider using a smaller soft prompt. If you are using the Always Add Prompt setting, turning it off may help.") assert budget >= 0 if(actionlen == 0): # First/Prompt action - tokens = memtokens + witokens + anotetkns + prompttkns + tokens = tokenizer._koboldai_header + memtokens + witokens + anotetkns + prompttkns assert len(tokens) <= vars.max_length - lnsp - vars.genamt - budget_deduction ln = len(tokens) + lnsp return tokens, ln+1, ln+vars.genamt @@ -3409,12 +3425,12 @@ def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None, # Did we get to add the A.N.? If not, do it here if(anotetxt != ""): if((not anoteadded) or forceanote): - tokens = memtokens + witokens + anotetkns + prompttkns + tokens + tokens = tokenizer._koboldai_header + memtokens + witokens + anotetkns + prompttkns + tokens else: - tokens = memtokens + witokens + prompttkns + tokens + tokens = tokenizer._koboldai_header + memtokens + witokens + prompttkns + tokens else: # Prepend Memory, WI, and Prompt before action tokens - tokens = memtokens + witokens + prompttkns + tokens + tokens = tokenizer._koboldai_header + memtokens + witokens + prompttkns + tokens # Send completed bundle to generator assert len(tokens) <= vars.max_length - lnsp - vars.genamt - budget_deduction