Change current working directory to KoboldAI folder
This commit is contained in:
parent
48d07adb54
commit
2b8c46338e
16
aiserver.py
16
aiserver.py
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@ -10,6 +10,8 @@ import eventlet
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eventlet.monkey_patch(all=True, thread=False)
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eventlet.monkey_patch(all=True, thread=False)
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import os
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import os
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os.system("")
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os.system("")
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__file__ = os.path.dirname(os.path.realpath(__file__))
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os.chdir(__file__)
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os.environ['EVENTLET_THREADPOOL_SIZE'] = '1'
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os.environ['EVENTLET_THREADPOOL_SIZE'] = '1'
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os.environ['TOKENIZERS_PARALLELISM'] = 'false'
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os.environ['TOKENIZERS_PARALLELISM'] = 'false'
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from eventlet import tpool
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from eventlet import tpool
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@ -1024,7 +1026,7 @@ log.setLevel(logging.ERROR)
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print("{0}Initializing Flask... {1}".format(colors.PURPLE, colors.END), end="")
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print("{0}Initializing Flask... {1}".format(colors.PURPLE, colors.END), end="")
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from flask import Flask, render_template, Response, request, copy_current_request_context
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from flask import Flask, render_template, Response, request, copy_current_request_context
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from flask_socketio import SocketIO, emit
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from flask_socketio import SocketIO, emit
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app = Flask(__name__)
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app = Flask(__name__, root_path=os.getcwd())
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app.config['SECRET KEY'] = 'secret!'
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app.config['SECRET KEY'] = 'secret!'
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socketio = SocketIO(app, async_method="eventlet")
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socketio = SocketIO(app, async_method="eventlet")
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print("{0}OK!{1}".format(colors.GREEN, colors.END))
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print("{0}OK!{1}".format(colors.GREEN, colors.END))
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@ -1101,7 +1103,7 @@ if(not vars.use_colab_tpu and vars.model not in ["InferKit", "Colab", "OAI", "Go
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return lazy_load_callback
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return lazy_load_callback
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lazy_load_config_path = os.path.join(path.dirname(path.realpath(__file__)), "maps", vars.model_type + ".json")
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lazy_load_config_path = os.path.join("maps", vars.model_type + ".json")
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if(vars.lazy_load and "model_config" in globals() and os.path.isfile(lazy_load_config_path)):
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if(vars.lazy_load and "model_config" in globals() and os.path.isfile(lazy_load_config_path)):
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with open(lazy_load_config_path) as f:
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with open(lazy_load_config_path) as f:
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lazy_load_spec = json.load(f)
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lazy_load_spec = json.load(f)
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@ -2193,16 +2195,16 @@ vars.lua_state = lupa.LuaRuntime(unpack_returned_tuples=True)
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# Load bridge.lua
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# Load bridge.lua
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bridged = {
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bridged = {
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"corescript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "cores"),
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"corescript_path": "cores",
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"userscript_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
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"userscript_path": "userscripts",
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"config_path": os.path.join(os.path.dirname(os.path.realpath(__file__)), "userscripts"),
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"config_path": "userscripts",
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"lib_paths": vars.lua_state.table(os.path.join(os.path.dirname(os.path.realpath(__file__)), "lualibs"), os.path.join(os.path.dirname(os.path.realpath(__file__)), "extern", "lualibs")),
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"lib_paths": vars.lua_state.table("lualibs", os.path.join("extern", "lualibs")),
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"vars": vars,
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"vars": vars,
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}
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}
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for kwarg in _bridged:
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for kwarg in _bridged:
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bridged[kwarg] = _bridged[kwarg]
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bridged[kwarg] = _bridged[kwarg]
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try:
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try:
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vars.lua_kobold, vars.lua_koboldcore, vars.lua_koboldbridge = vars.lua_state.globals().dofile(os.path.join(os.path.dirname(os.path.realpath(__file__)), "bridge.lua"))(
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vars.lua_kobold, vars.lua_koboldcore, vars.lua_koboldbridge = vars.lua_state.globals().dofile("bridge.lua")(
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vars.lua_state.globals().python,
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vars.lua_state.globals().python,
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bridged,
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bridged,
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)
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)
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20
fileops.py
20
fileops.py
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@ -65,30 +65,30 @@ def getdirpath(dir, title):
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# Returns the path (as a string) to the given story by its name
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# Returns the path (as a string) to the given story by its name
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#==================================================================#
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#==================================================================#
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def storypath(name):
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def storypath(name):
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return path.join(path.dirname(path.realpath(__file__)), "stories", name + ".json")
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return path.join("stories", name + ".json")
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#==================================================================#
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#==================================================================#
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# Returns the path (as a string) to the given soft prompt by its filename
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# Returns the path (as a string) to the given soft prompt by its filename
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#==================================================================#
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#==================================================================#
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def sppath(filename):
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def sppath(filename):
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return path.join(path.dirname(path.realpath(__file__)), "softprompts", filename)
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return path.join("softprompts", filename)
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#==================================================================#
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#==================================================================#
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# Returns the path (as a string) to the given username by its filename
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# Returns the path (as a string) to the given username by its filename
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#==================================================================#
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#==================================================================#
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def uspath(filename):
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def uspath(filename):
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return path.join(path.dirname(path.realpath(__file__)), "userscripts", filename)
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return path.join("userscripts", filename)
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#==================================================================#
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#==================================================================#
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# Returns an array of dicts containing story files in /stories
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# Returns an array of dicts containing story files in /stories
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#==================================================================#
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#==================================================================#
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def getstoryfiles():
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def getstoryfiles():
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list = []
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list = []
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for file in listdir(path.dirname(path.realpath(__file__))+"/stories"):
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for file in listdir("stories"):
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if file.endswith(".json"):
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if file.endswith(".json"):
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ob = {}
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ob = {}
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ob["name"] = file.replace(".json", "")
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ob["name"] = file.replace(".json", "")
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f = open(path.dirname(path.realpath(__file__))+"/stories/"+file, "r")
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f = open("stories/"+file, "r")
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try:
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try:
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js = json.load(f)
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js = json.load(f)
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except:
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except:
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@ -112,7 +112,7 @@ def checksp(filename: str, model_dimension: int) -> Tuple[Union[zipfile.ZipFile,
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if 'np' not in globals():
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if 'np' not in globals():
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import numpy as np
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import numpy as np
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try:
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try:
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z = zipfile.ZipFile(path.dirname(path.realpath(__file__))+"/softprompts/"+filename)
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z = zipfile.ZipFile("softprompts/"+filename)
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with z.open('tensor.npy') as f:
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with z.open('tensor.npy') as f:
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# Read only the header of the npy file, for efficiency reasons
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# Read only the header of the npy file, for efficiency reasons
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version: Tuple[int, int] = np.lib.format.read_magic(f)
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version: Tuple[int, int] = np.lib.format.read_magic(f)
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@ -140,8 +140,8 @@ def checksp(filename: str, model_dimension: int) -> Tuple[Union[zipfile.ZipFile,
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#==================================================================#
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#==================================================================#
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def getspfiles(model_dimension: int):
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def getspfiles(model_dimension: int):
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lst = []
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lst = []
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os.makedirs(path.dirname(path.realpath(__file__))+"/softprompts", exist_ok=True)
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os.makedirs("softprompts", exist_ok=True)
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for file in listdir(path.dirname(path.realpath(__file__))+"/softprompts"):
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for file in listdir("softprompts"):
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if not file.endswith(".zip"):
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if not file.endswith(".zip"):
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continue
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continue
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z, version, shape, fortran_order, dtype = checksp(file, model_dimension)
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z, version, shape, fortran_order, dtype = checksp(file, model_dimension)
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@ -174,8 +174,8 @@ def getspfiles(model_dimension: int):
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#==================================================================#
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#==================================================================#
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def getusfiles(long_desc=False):
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def getusfiles(long_desc=False):
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lst = []
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lst = []
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os.makedirs(path.dirname(path.realpath(__file__))+"/userscripts", exist_ok=True)
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os.makedirs("userscripts", exist_ok=True)
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for file in listdir(path.dirname(path.realpath(__file__))+"/userscripts"):
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for file in listdir("userscripts"):
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if file.endswith(".lua"):
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if file.endswith(".lua"):
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ob = {}
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ob = {}
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ob["filename"] = file
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ob["filename"] = file
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@ -822,7 +822,7 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
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# Try to convert HF config.json to MTJ config
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# Try to convert HF config.json to MTJ config
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if hf_checkpoint:
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if hf_checkpoint:
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spec_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "maps", vars.model_type + ".json")
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spec_path = os.path.join("maps", vars.model_type + ".json")
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if not os.path.isfile(spec_path):
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if not os.path.isfile(spec_path):
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raise NotImplementedError(f"Unsupported model type {repr(vars.model_type)}")
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raise NotImplementedError(f"Unsupported model type {repr(vars.model_type)}")
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with open(spec_path) as f:
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with open(spec_path) as f:
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