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Code Issues Projects Releases Wiki Activity

Fix vscode artifacting

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Henk
2023-02-18 18:47:15 +01:00
parent a9a724e38c
commit aa6ce9088b
1 changed files with 0 additions and 14 deletions
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14
aiserver.py
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@@ -1792,7 +1792,6 @@ def get_layer_count(model, directory=""):
model_config = AutoConfig.from_pretrained(koboldai_vars.custmodpth.replace('/', '_'), revision=args.revision, cache_dir="cache") model_config = AutoConfig.from_pretrained(koboldai_vars.custmodpth.replace('/', '_'), revision=args.revision, cache_dir="cache")
else: else:
model_config = AutoConfig.from_pretrained(model, revision=args.revision, cache_dir="cache") model_config = AutoConfig.from_pretrained(model, revision=args.revision, cache_dir="cache")
model_config = AutoConfig.from_pretrained(model, revision=args.revision, cache_dir="cache")
try: try:
if ((utils.HAS_ACCELERATE and model_config.model_type != 'gpt2') or model_config.model_type in ("gpt_neo", "gptj", "xglm", "opt")) and not koboldai_vars.nobreakmodel: if ((utils.HAS_ACCELERATE and model_config.model_type != 'gpt2') or model_config.model_type in ("gpt_neo", "gptj", "xglm", "opt")) and not koboldai_vars.nobreakmodel:
return utils.num_layers(model_config) return utils.num_layers(model_config)
@@ -3130,7 +3129,6 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
tokenizer = GPT2Tokenizer.from_pretrained(koboldai_vars.custmodpth, revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained(koboldai_vars.custmodpth, revision=args.revision, cache_dir="cache")
except Exception as e: except Exception as e:
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=args.revision, cache_dir="cache", **lowmem) model = AutoModelForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=args.revision, cache_dir="cache", **lowmem)
except Exception as e: except Exception as e:
@@ -3148,7 +3146,6 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
tokenizer = GPT2Tokenizer.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=args.revision, cache_dir="cache")
except Exception as e: except Exception as e:
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=args.revision, cache_dir="cache", **lowmem) model = AutoModelForCausalLM.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=args.revision, cache_dir="cache", **lowmem)
except Exception as e: except Exception as e:
@@ -3179,7 +3176,6 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
tokenizer = GPT2Tokenizer.from_pretrained(koboldai_vars.model, revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained(koboldai_vars.model, revision=args.revision, cache_dir="cache")
except Exception as e: except Exception as e:
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained(koboldai_vars.model, revision=args.revision, cache_dir="cache", **lowmem) model = AutoModelForCausalLM.from_pretrained(koboldai_vars.model, revision=args.revision, cache_dir="cache", **lowmem)
except Exception as e: except Exception as e:
@@ -3264,7 +3260,6 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
else: else:
from transformers import GPT2Tokenizer from transformers import GPT2Tokenizer
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
else: else:
from transformers import PreTrainedModel from transformers import PreTrainedModel
from transformers import modeling_utils from transformers import modeling_utils
@@ -3678,7 +3673,6 @@ def lua_decode(tokens):
from transformers import GPT2Tokenizer from transformers import GPT2Tokenizer
global tokenizer global tokenizer
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
return utils.decodenewlines(tokenizer.decode(tokens)) return utils.decodenewlines(tokenizer.decode(tokens))
#==================================================================# #==================================================================#
@@ -3691,7 +3685,6 @@ def lua_encode(string):
from transformers import GPT2Tokenizer from transformers import GPT2Tokenizer
global tokenizer global tokenizer
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
return tokenizer.encode(utils.encodenewlines(string), max_length=int(4e9), truncation=True) return tokenizer.encode(utils.encodenewlines(string), max_length=int(4e9), truncation=True)
#==================================================================# #==================================================================#
@@ -4850,24 +4843,18 @@ def actionsubmit(data, actionmode=0, force_submit=False, force_prompt_gen=False,
if(os.path.isdir(tokenizer_id)): if(os.path.isdir(tokenizer_id)):
try: try:
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache")
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache")
except: except:
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache", use_fast=False) tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache", use_fast=False)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache", use_fast=False)
elif(os.path.isdir("models/{}".format(tokenizer_id.replace('/', '_')))): elif(os.path.isdir("models/{}".format(tokenizer_id.replace('/', '_')))):
try: try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=args.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=args.revision, cache_dir="cache")
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=args.revision, cache_dir="cache")
except: except:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=args.revision, cache_dir="cache", use_fast=False) tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=args.revision, cache_dir="cache", use_fast=False)
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(tokenizer_id.replace('/', '_')), revision=args.revision, cache_dir="cache", use_fast=False)
else: else:
try: try:
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache")
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache")
except: except:
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache", use_fast=False) tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache", use_fast=False)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_id, revision=args.revision, cache_dir="cache", use_fast=False)
except: except:
logger.warning(f"Unknown tokenizer {repr(tokenizer_id)}") logger.warning(f"Unknown tokenizer {repr(tokenizer_id)}")
koboldai_vars.api_tokenizer_id = tokenizer_id koboldai_vars.api_tokenizer_id = tokenizer_id
@@ -5243,7 +5230,6 @@ def calcsubmitbudget(actionlen, winfo, mem, anotetxt, actions, submission=None,
from transformers import GPT2Tokenizer from transformers import GPT2Tokenizer
global tokenizer global tokenizer
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache") tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=args.revision, cache_dir="cache")
lnheader = len(tokenizer._koboldai_header) lnheader = len(tokenizer._koboldai_header)