extract configs from global

LLaMA_LoRA.ipynb

@@ -279,21 +279,23 @@
     {
       "cell_type": "code",
       "source": [
-        "# @title Load the App (set config, prepare data dir, load base bodel)\n",
+        "# @title Load the App (set config, prepare data dir, load base model)\n",
         "\n",
         "# @markdown For a LLaMA-7B model, it will take about ~5m to load for the first execution,\n",
         "# @markdown including download. Subsequent executions will take about 2m to load.\n",
         "\n",
         "# Set Configs\n",
-        "from llama_lora.llama_lora.globals import Global\n",
-        "Global.default_base_model_name = Global.base_model_name = base_model\n",
-        "Global.base_model_choices = [base_model]\n",
+        "from llama_lora.llama_lora.config import Config, process_config\n",
+        "from llama_lora.llama_lora.globals import initialize_global\n",
+        "Config.default_base_model_name = base_model\n",
+        "Config.base_model_choices = [base_model]\n",
         "data_dir_realpath = !realpath ./data\n",
-        "Global.data_dir = data_dir_realpath[0]\n",
-        "Global.load_8bit = True\n",
+        "Config.data_dir = data_dir_realpath[0]\n",
+        "Config.load_8bit = True\n",
+        "process_config()\n",
+        "initialize_global()\n",
         "\n",
         "# Prepare Data Dir\n",
-        "import os\n",
         "from llama_lora.llama_lora.utils.data import init_data_dir\n",
         "init_data_dir()\n",
         "\n",

app.py

@@ -1,30 +1,30 @@
-import os
-import sys
+from typing import Union
 
 import fire
 import gradio as gr
 
-from llama_lora.globals import Global
+from llama_lora.config import Config, process_config
+from llama_lora.globals import initialize_global
 from llama_lora.models import prepare_base_model
-from llama_lora.ui.main_page import main_page, get_page_title, main_page_custom_css
 from llama_lora.utils.data import init_data_dir
-
+from llama_lora.ui.main_page import (
+    main_page, get_page_title, main_page_custom_css
+)
 
 
 def main(
-    base_model: str = "",
-    data_dir: str = "",
-    base_model_choices: str = "",
-    trust_remote_code: bool = False,
-    # Allows to listen on all interfaces by providing '0.0.0.0'.
+    base_model: Union[str, None] = None,
+    data_dir: Union[str, None] = None,
+    base_model_choices: Union[str, None] = None,
+    trust_remote_code: Union[bool, None] = None,
     server_name: str = "127.0.0.1",
     share: bool = False,
     skip_loading_base_model: bool = False,
-    load_8bit: bool = False,
-    ui_show_sys_info: bool = True,
-    ui_dev_mode: bool = False,
-    wandb_api_key: str = "",
-    wandb_project: str = "",
+    load_8bit: Union[bool, None] = None,
+    ui_show_sys_info: Union[bool, None] = None,
+    ui_dev_mode: Union[bool, None] = None,
+    wandb_api_key: Union[str, None] = None,
+    wandb_project: Union[str, None] = None,
 ):
     '''
     Start the LLaMA-LoRA Tuner UI.
@@ -41,51 +41,54 @@ def main(
     :param wandb_project: The default project name for Weights & Biases. Setting either this or `wandb_api_key` will enable Weights & Biases.
     '''
 
-    base_model = base_model or os.environ.get("LLAMA_LORA_BASE_MODEL", "")
-    data_dir = data_dir or os.environ.get("LLAMA_LORA_DATA_DIR", "")
-    assert (
-        base_model
-    ), "Please specify a --base_model, e.g. --base_model='decapoda-research/llama-7b-hf'"
+    if base_model is not None:
+        Config.default_base_model_name = base_model
 
-    assert (
-        data_dir
-    ), "Please specify a --data_dir, e.g. --data_dir='./data'"
+    if base_model_choices is not None:
+        Config.base_model_choices = base_model_choices
+
+    if trust_remote_code is not None:
+        Config.trust_remote_code = trust_remote_code
 
-    Global.default_base_model_name = Global.base_model_name = base_model
+    if data_dir is not None:
+        Config.data_dir = data_dir
 
-    if base_model_choices:
-        base_model_choices = base_model_choices.split(',')
-        base_model_choices = [name.strip() for name in base_model_choices]
-        Global.base_model_choices = base_model_choices
+    if load_8bit is not None:
+        Config.load_8bit = load_8bit
 
-    if base_model not in Global.base_model_choices:
-        Global.base_model_choices = [base_model] + Global.base_model_choices
+    if wandb_api_key is not None:
+        Config.wandb_api_key = wandb_api_key
 
-    Global.trust_remote_code = trust_remote_code
+    if wandb_project is not None:
+        Config.default_wandb_project = wandb_project
 
-    Global.data_dir = os.path.abspath(data_dir)
-    Global.load_8bit = load_8bit
+    if ui_dev_mode is not None:
+        Config.ui_dev_mode = ui_dev_mode
 
-    if len(wandb_api_key) > 0:
-        Global.enable_wandb = True
-        Global.wandb_api_key = wandb_api_key
-    if len(wandb_project) > 0:
-        Global.enable_wandb = True
-        Global.wandb_project = wandb_project
+    if ui_show_sys_info is not None:
+        Config.ui_show_sys_info = ui_show_sys_info
 
-    Global.ui_dev_mode = ui_dev_mode
-    Global.ui_show_sys_info = ui_show_sys_info
+    process_config()
+    initialize_global()
+
+    assert (
+        Config.default_base_model_name
+    ), "Please specify a --base_model, e.g. --base_model='decapoda-research/llama-7b-hf'"
+
+    assert (
+        Config.data_dir
+    ), "Please specify a --data_dir, e.g. --data_dir='./data'"
 
-    os.makedirs(data_dir, exist_ok=True)
     init_data_dir()
 
-    if (not skip_loading_base_model) and (not ui_dev_mode):
-        prepare_base_model(base_model)
+    if (not skip_loading_base_model) and (not Config.ui_dev_mode):
+        prepare_base_model(Config.default_base_model_name)
 
     with gr.Blocks(title=get_page_title(), css=main_page_custom_css()) as demo:
         main_page()
 
-    demo.queue(concurrency_count=1).launch(server_name=server_name, share=share)
+    demo.queue(concurrency_count=1).launch(
+        server_name=server_name, share=share)
 
 
 if __name__ == "__main__":

llama_lora/config.py

@@ -0,0 +1,47 @@
+import os
+from typing import List, Union
+
+
+class Config:
+    """
+    Stores the application configuration. This is a singleton class.
+    """
+
+    data_dir: str = ""
+    load_8bit: bool = False
+
+    default_base_model_name: str = ""
+    base_model_choices: Union[List[str], str] = []
+
+    trust_remote_code: bool = False
+
+    # WandB
+    enable_wandb: Union[bool, None] = False
+    wandb_api_key: Union[str, None] = None
+    default_wandb_project: str = "llama-lora-tuner"
+
+    # UI related
+    ui_title: str = "LLaMA-LoRA Tuner"
+    ui_emoji: str = "🦙🎛️"
+    ui_subtitle: str = "Toolkit for evaluating and fine-tuning LLaMA models with low-rank adaptation (LoRA)."
+    ui_show_sys_info: bool = True
+    ui_dev_mode: bool = False
+    ui_dev_mode_title_prefix: str = "[UI DEV MODE] "
+
+
+def process_config():
+    Config.data_dir = os.path.abspath(Config.data_dir)
+
+    if isinstance(Config.base_model_choices, str):
+        base_model_choices = Config.base_model_choices.split(',')
+        base_model_choices = [name.strip() for name in base_model_choices]
+        Config.base_model_choices = base_model_choices
+
+    if Config.default_base_model_name not in Config.base_model_choices:
+        Config.base_model_choices = [Config.default_base_model_name] + Config.base_model_choices
+
+    if Config.enable_wandb is None:
+        if Config.wandb_api_key and len(Config.wandb_api_key) > 0:
+            Config.enable_wandb = True
+        if Config.default_wandb_project and len(Config.default_wandb_project) > 0:
+            Config.enable_wandb = True

llama_lora/globals.py

@@ -8,23 +8,21 @@ from typing import Any, Dict, List, Optional, Tuple, Union
 from numba import cuda
 import nvidia_smi
 
+from .config import Config
 from .utils.lru_cache import LRUCache
 from .utils.model_lru_cache import ModelLRUCache
 from .lib.finetune import train
 
 
 class Global:
-    version = None
+    """
+    A singleton class holding global states.
+    """
 
-    data_dir: str = ""
-    load_8bit: bool = False
+    version: Union[str, None] = None
 
-    default_base_model_name: str = ""
     base_model_name: str = ""
     tokenizer_name = None
-    base_model_choices: List[str] = []
-
-    trust_remote_code = False
 
     # Functions
     train_fn: Any = train
@@ -48,18 +46,15 @@ class Global:
     gpu_total_cores = None  # GPU total cores
     gpu_total_memory = None
 
-    # WandB
-    enable_wandb = False
-    wandb_api_key = None
-    default_wandb_project = "llama-lora-tuner"
 
-    # UI related
-    ui_title: str = "LLaMA-LoRA Tuner"
-    ui_emoji: str = "🦙🎛️"
-    ui_subtitle: str = "Toolkit for evaluating and fine-tuning LLaMA models with low-rank adaptation (LoRA)."
-    ui_show_sys_info: bool = True
-    ui_dev_mode: bool = False
-    ui_dev_mode_title_prefix: str = "[UI DEV MODE] "
+def initialize_global():
+    Global.base_model_name = Config.default_base_model_name
+    commit_hash = get_git_commit_hash()
+
+    if commit_hash:
+        Global.version = commit_hash[:8]
+
+    load_gpu_info()
 
 
 def get_package_dir():
@@ -85,12 +80,6 @@ def get_git_commit_hash():
         print(f"Cannot get git commit hash: {e}")
 
 
-commit_hash = get_git_commit_hash()
-
-if commit_hash:
-    Global.version = commit_hash[:8]
-
-
 def load_gpu_info():
     print("")
     try:
@@ -154,5 +143,3 @@ def load_gpu_info():
         print(f"Notice: cannot get GPU info: {e}")
 
     print("")
-
-load_gpu_info()

llama_lora/models.py

@@ -11,12 +11,13 @@ from transformers import (
 )
 from peft import PeftModel
 
+from .config import Config
 from .globals import Global
 from .lib.get_device import get_device
 
 
 def get_new_base_model(base_model_name):
-    if Global.ui_dev_mode:
+    if Config.ui_dev_mode:
         return
 
     if Global.new_base_model_that_is_ready_to_be_used:
@@ -79,14 +80,14 @@ def _get_model_from_pretrained(model_class, model_name, from_tf=False, force_dow
     if device == "cuda":
         return model_class.from_pretrained(
             model_name,
-            load_in_8bit=Global.load_8bit,
+            load_in_8bit=Config.load_8bit,
             torch_dtype=torch.float16,
             # device_map="auto",
             # ? https://github.com/tloen/alpaca-lora/issues/21
             device_map={'': 0},
             from_tf=from_tf,
             force_download=force_download,
-            trust_remote_code=Global.trust_remote_code
+            trust_remote_code=Config.trust_remote_code
         )
     elif device == "mps":
         return model_class.from_pretrained(
@@ -95,7 +96,7 @@ def _get_model_from_pretrained(model_class, model_name, from_tf=False, force_dow
             torch_dtype=torch.float16,
             from_tf=from_tf,
             force_download=force_download,
-            trust_remote_code=Global.trust_remote_code
+            trust_remote_code=Config.trust_remote_code
         )
     else:
         return model_class.from_pretrained(
@@ -104,12 +105,12 @@ def _get_model_from_pretrained(model_class, model_name, from_tf=False, force_dow
             low_cpu_mem_usage=True,
             from_tf=from_tf,
             force_download=force_download,
-            trust_remote_code=Global.trust_remote_code
+            trust_remote_code=Config.trust_remote_code
         )
 
 
 def get_tokenizer(base_model_name):
-    if Global.ui_dev_mode:
+    if Config.ui_dev_mode:
         return
 
     loaded_tokenizer = Global.loaded_tokenizers.get(base_model_name)
@@ -119,13 +120,13 @@ def get_tokenizer(base_model_name):
     try:
         tokenizer = AutoTokenizer.from_pretrained(
             base_model_name,
-            trust_remote_code=Global.trust_remote_code
+            trust_remote_code=Config.trust_remote_code
         )
     except Exception as e:
         if 'LLaMATokenizer' in str(e):
             tokenizer = LlamaTokenizer.from_pretrained(
                 base_model_name,
-                trust_remote_code=Global.trust_remote_code
+                trust_remote_code=Config.trust_remote_code
             )
         else:
             raise e
@@ -138,7 +139,7 @@ def get_tokenizer(base_model_name):
 def get_model(
         base_model_name,
         peft_model_name=None):
-    if Global.ui_dev_mode:
+    if Config.ui_dev_mode:
         return
 
     if peft_model_name == "None":
@@ -156,7 +157,7 @@ def get_model(
 
     if peft_model_name:
         lora_models_directory_path = os.path.join(
-            Global.data_dir, "lora_models")
+            Config.data_dir, "lora_models")
         possible_lora_model_path = os.path.join(
             lora_models_directory_path, peft_model_name)
         if os.path.isdir(possible_lora_model_path):
@@ -211,7 +212,7 @@ def get_model(
         model.config.bos_token_id = 1
         model.config.eos_token_id = 2
 
-    if not Global.load_8bit:
+    if not Config.load_8bit:
         model.half()  # seems to fix bugs for some users.
 
     model.eval()
@@ -224,7 +225,7 @@ def get_model(
     return model
 
 
-def prepare_base_model(base_model_name=Global.default_base_model_name):
+def prepare_base_model(base_model_name=Config.default_base_model_name):
     Global.new_base_model_that_is_ready_to_be_used = get_new_base_model(
         base_model_name)
     Global.name_of_new_base_model_that_is_ready_to_be_used = base_model_name

llama_lora/ui/finetune_ui.py

@@ -11,6 +11,7 @@ from random_word import RandomWords
 from transformers import TrainerCallback
 from huggingface_hub import try_to_load_from_cache, snapshot_download
 
+from ..config import Config
 from ..globals import Global
 from ..models import (
     get_new_base_model, get_tokenizer,
@@ -240,9 +241,9 @@ def refresh_dataset_items_count(
 
         trace = traceback.format_exc()
         traces = [s.strip() for s in re.split("\n * File ", trace)]
-        templates_path = os.path.join(Global.data_dir, "templates")
+        templates_path = os.path.join(Config.data_dir, "templates")
         traces_to_show = [s for s in traces if os.path.join(
-            Global.data_dir, "templates") in s]
+            Config.data_dir, "templates") in s]
         traces_to_show = [re.sub(" *\n *", ": ", s) for s in traces_to_show]
         if len(traces_to_show) > 0:
             update_message = gr.Markdown.update(
@@ -323,7 +324,7 @@ def do_train(
             continue_from_checkpoint = None
         if continue_from_model:
             resume_from_model_path = os.path.join(
-                Global.data_dir, "lora_models", continue_from_model)
+                Config.data_dir, "lora_models", continue_from_model)
             resume_from_checkpoint_param = resume_from_model_path
             if continue_from_checkpoint:
                 resume_from_checkpoint_param = os.path.join(
@@ -360,7 +361,7 @@ def do_train(
                         raise ValueError(
                             f"Unable to continue from model {continue_from_model}. Continuation is only possible from models stored locally in the data directory. Please ensure that the file '{will_be_resume_from_checkpoint_file}' exists.")
 
-        output_dir = os.path.join(Global.data_dir, "lora_models", model_name)
+        output_dir = os.path.join(Config.data_dir, "lora_models", model_name)
         if os.path.exists(output_dir):
             if (not os.path.isdir(output_dir)) or os.path.exists(os.path.join(output_dir, 'adapter_config.json')):
                 raise ValueError(
@@ -399,7 +400,7 @@ def do_train(
                 progress_detail += f", Loss: {last_loss:.4f}"
             return f"Training... ({progress_detail})"
 
-        if Global.ui_dev_mode:
+        if Config.ui_dev_mode:
             Global.should_stop_training = False
 
             message = f"""Currently in UI dev mode, not doing the actual training.
@@ -575,8 +576,8 @@ Train data (first 10):
             additional_training_arguments=additional_training_arguments,
             additional_lora_config=additional_lora_config,
             callbacks=training_callbacks,
-            wandb_api_key=Global.wandb_api_key,
-            wandb_project=Global.default_wandb_project if Global.enable_wandb else None,
+            wandb_api_key=Config.wandb_api_key,
+            wandb_project=Config.default_wandb_project if Config.enable_wandb else None,
             wandb_group=wandb_group,
             wandb_run_name=model_name,
             wandb_tags=wandb_tags
@@ -605,7 +606,7 @@ def do_abort_training():
 def handle_continue_from_model_change(model_name):
     try:
         lora_models_directory_path = os.path.join(
-            Global.data_dir, "lora_models")
+            Config.data_dir, "lora_models")
         lora_model_directory_path = os.path.join(
             lora_models_directory_path, model_name)
         all_files = os.listdir(lora_model_directory_path)
@@ -651,7 +652,7 @@ def handle_load_params_from_model(
     unknown_keys = []
     try:
         lora_models_directory_path = os.path.join(
-            Global.data_dir, "lora_models")
+            Config.data_dir, "lora_models")
         lora_model_directory_path = os.path.join(
             lora_models_directory_path, model_name)
 

llama_lora/ui/inference_ui.py

@@ -7,6 +7,7 @@ import torch
 import transformers
 from transformers import GenerationConfig
 
+from ..config import Config
 from ..globals import Global
 from ..models import get_model, get_tokenizer, get_device
 from ..lib.inference import generate
@@ -101,7 +102,7 @@ def do_inference(
                 'generation_config': generation_config.to_dict(),
             })
 
-        if Global.ui_dev_mode:
+        if Config.ui_dev_mode:
             message = f"Hi, I’m currently in UI-development mode and do not have access to resources to process your request. However, this behavior is similar to what will actually happen, so you can try and see how it will work!\n\nBase model: {base_model_name}\nLoRA model: {lora_model_name}\n\nThe following is your prompt:\n\n{prompt}"
             print(message)
 
@@ -318,7 +319,7 @@ def update_prompt_preview(prompt_template,
 
 
 def inference_ui():
-    flagging_dir = os.path.join(Global.data_dir, "flagging", "inference")
+    flagging_dir = os.path.join(Config.data_dir, "flagging", "inference")
     if not os.path.exists(flagging_dir):
         os.makedirs(flagging_dir)
 

llama_lora/ui/main_page.py

@@ -1,5 +1,6 @@
 import gradio as gr
 
+from ..config import Config
 from ..globals import Global
 
 from .inference_ui import inference_ui
@@ -21,7 +22,7 @@ def main_page():
                 gr.Markdown(
                     f"""
                     <h1 class="app_title_text">{title}</h1> <wbr />
-                    <h2 class="app_subtitle_text">{Global.ui_subtitle}</h2>
+                    <h2 class="app_subtitle_text">{Config.ui_subtitle}</h2>
                     """,
                     elem_id="page_title",
                 )
@@ -29,7 +30,7 @@ def main_page():
                     global_base_model_select = gr.Dropdown(
                         label="Base Model",
                         elem_id="global_base_model_select",
-                        choices=Global.base_model_choices,
+                        choices=Config.base_model_choices,
                         value=lambda: Global.base_model_name,
                         allow_custom_value=True,
                     )
@@ -146,11 +147,11 @@ def main_page():
 
 
 def get_page_title():
-    title = Global.ui_title
-    if (Global.ui_dev_mode):
-        title = Global.ui_dev_mode_title_prefix + title
-    if (Global.ui_emoji):
-        title = f"{Global.ui_emoji} {title}"
+    title = Config.ui_title
+    if (Config.ui_dev_mode):
+        title = Config.ui_dev_mode_title_prefix + title
+    if (Config.ui_emoji):
+        title = f"{Config.ui_emoji} {title}"
     return title
 
 
@@ -953,8 +954,8 @@ def get_foot_info():
         info.append(f"Base model: `{Global.base_model_name}`")
     if Global.tokenizer_name and Global.tokenizer_name != Global.base_model_name:
         info.append(f"Tokenizer: `{Global.tokenizer_name}`")
-    if Global.ui_show_sys_info:
-        info.append(f"Data dir: `{Global.data_dir}`")
+    if Config.ui_show_sys_info:
+        info.append(f"Data dir: `{Config.data_dir}`")
     return f"""\
         <small>{"&nbsp;&nbsp;·&nbsp;&nbsp;".join(info)}</small>
         """

llama_lora/ui/tokenizer_ui.py

@@ -2,6 +2,7 @@ import gradio as gr
 import time
 import json
 
+from ..config import Config
 from ..globals import Global
 from ..models import get_tokenizer
 
@@ -12,7 +13,7 @@ def handle_decode(encoded_tokens_json):
 
     try:
         encoded_tokens = json.loads(encoded_tokens_json)
-        if Global.ui_dev_mode:
+        if Config.ui_dev_mode:
             return f"Not actually decoding tokens in UI dev mode.", gr.Markdown.update("", visible=False)
         tokenizer = get_tokenizer(tokenizer_name)
         decoded_tokens = tokenizer.decode(encoded_tokens)
@@ -26,7 +27,7 @@ def handle_encode(decoded_tokens):
     tokenizer_name = Global.tokenizer_name or Global.base_model_name
 
     try:
-        if Global.ui_dev_mode:
+        if Config.ui_dev_mode:
             return f"[\"Not actually encoding tokens in UI dev mode.\"]", gr.Markdown.update("", visible=False)
         tokenizer = get_tokenizer(tokenizer_name)
         result = tokenizer(decoded_tokens)

llama_lora/utils/data.py

@@ -3,20 +3,22 @@ import shutil
 import fnmatch
 import json
 
+from ..config import Config
 from ..globals import Global
 
 
 def init_data_dir():
+    os.makedirs(Config.data_dir, exist_ok=True)
     current_file_path = os.path.abspath(__file__)
     parent_directory_path = os.path.dirname(current_file_path)
     project_dir_path = os.path.abspath(
         os.path.join(parent_directory_path, "..", ".."))
     copy_sample_data_if_not_exists(os.path.join(project_dir_path, "templates"),
-                                   os.path.join(Global.data_dir, "templates"))
+                                   os.path.join(Config.data_dir, "templates"))
     copy_sample_data_if_not_exists(os.path.join(project_dir_path, "datasets"),
-                                   os.path.join(Global.data_dir, "datasets"))
+                                   os.path.join(Config.data_dir, "datasets"))
     copy_sample_data_if_not_exists(os.path.join(project_dir_path, "lora_models"),
-                                   os.path.join(Global.data_dir, "lora_models"))
+                                   os.path.join(Config.data_dir, "lora_models"))
 
 
 def copy_sample_data_if_not_exists(source, destination):
@@ -28,28 +30,28 @@ def copy_sample_data_if_not_exists(source, destination):
 
 
 def get_available_template_names():
-    templates_directory_path = os.path.join(Global.data_dir, "templates")
+    templates_directory_path = os.path.join(Config.data_dir, "templates")
     all_files = os.listdir(templates_directory_path)
     names = [filename.rstrip(".json") for filename in all_files if fnmatch.fnmatch(filename, "*.json") or fnmatch.fnmatch(filename, "*.py")]
     return sorted(names)
 
 
 def get_available_dataset_names():
-    datasets_directory_path = os.path.join(Global.data_dir, "datasets")
+    datasets_directory_path = os.path.join(Config.data_dir, "datasets")
     all_files = os.listdir(datasets_directory_path)
     names = [filename for filename in all_files if fnmatch.fnmatch(filename, "*.json") or fnmatch.fnmatch(filename, "*.jsonl")]
     return sorted(names)
 
 
 def get_available_lora_model_names():
-    lora_models_directory_path = os.path.join(Global.data_dir, "lora_models")
+    lora_models_directory_path = os.path.join(Config.data_dir, "lora_models")
     all_items = os.listdir(lora_models_directory_path)
     names = [item for item in all_items if os.path.isdir(os.path.join(lora_models_directory_path, item))]
     return sorted(names)
 
 
 def get_path_of_available_lora_model(name):
-    datasets_directory_path = os.path.join(Global.data_dir, "lora_models")
+    datasets_directory_path = os.path.join(Config.data_dir, "lora_models")
     path = os.path.join(datasets_directory_path, name)
     if os.path.isdir(path):
         return path
@@ -73,7 +75,7 @@ def get_info_of_available_lora_model(name):
 
 
 def get_dataset_content(name):
-    file_name = os.path.join(Global.data_dir, "datasets", name)
+    file_name = os.path.join(Config.data_dir, "datasets", name)
     if not os.path.exists(file_name):
         raise ValueError(
             f"Can't read {file_name} from datasets. File does not exist.")

llama_lora/utils/prompter.py

@@ -9,6 +9,7 @@ import importlib
 import itertools
 from typing import Union, List
 
+from ..config import Config
 from ..globals import Global
 
 
@@ -31,7 +32,7 @@ class Prompter(object):
         else:
             filename = base_filename + ext
 
-        file_path = osp.join(Global.data_dir, "templates", filename)
+        file_path = osp.join(Config.data_dir, "templates", filename)
 
         if not osp.exists(file_path):
             raise ValueError(f"Can't read {file_path}")