Update app_test.py

app_test.py

@@ -0,0 +1,90 @@
+# from .demo_modelpart import InferenceDemo
+import gradio as gr
+import os
+from threading import Thread
+
+# import time
+import cv2
+
+import datetime
+# import copy
+import torch
+
+import spaces
+import numpy as np
+
+from llava.constants import DEFAULT_IMAGE_TOKEN
+
+from llava.constants import (
+    IMAGE_TOKEN_INDEX,
+    DEFAULT_IMAGE_TOKEN,
+)
+from llava.conversation import conv_templates, SeparatorStyle
+from llava.model.builder import load_pretrained_model
+from llava.utils import disable_torch_init
+from llava.mm_utils import (
+    tokenizer_image_token,
+    get_model_name_from_path,
+    KeywordsStoppingCriteria,
+)
+
+from serve_constants import html_header, bibtext, learn_more_markdown, tos_markdown
+
+from decord import VideoReader, cpu
+
+import requests
+from PIL import Image
+import io
+from io import BytesIO
+from transformers import TextStreamer, TextIteratorStreamer
+
+import hashlib
+import PIL
+import base64
+import json
+
+import datetime
+import gradio as gr
+import gradio_client
+import subprocess
+import sys
+
+from huggingface_hub import HfApi
+from huggingface_hub import login
+from huggingface_hub import revision_exists
+
+login(token=os.environ["HF_TOKEN"],
+      write_permission=True)
+
+api = HfApi()
+repo_name = os.environ["LOG_REPO"]
+
+external_log_dir = "./logs"
+LOGDIR = external_log_dir
+VOTEDIR = "./votes"
+
+if __name__ == "__main__":
+    import argparse
+
+    argparser = argparse.ArgumentParser()
+    argparser.add_argument("--server_name", default="0.0.0.0", type=str)
+    argparser.add_argument("--model_path", default="TIGER-Lab/MAmmoTH-VL2", type=str)
+    argparser.add_argument("--model-base", type=str, default=None)
+    argparser.add_argument("--num-gpus", type=int, default=1)
+    argparser.add_argument("--conv-mode", type=str, default=None)
+    argparser.add_argument("--temperature", type=float, default=0.7)
+    argparser.add_argument("--max-new-tokens", type=int, default=4096)
+    argparser.add_argument("--num_frames", type=int, default=32)
+    argparser.add_argument("--load-8bit", action="store_true")
+    argparser.add_argument("--load-4bit", action="store_true")
+    argparser.add_argument("--debug", action="store_true")
+
+    args = argparser.parse_args()
+
+    model_path = args.model_path
+    filt_invalid = "cut"
+    model_name = get_model_name_from_path(args.model_path)
+    tokenizer, model, image_processor, context_len = load_pretrained_model(args.model_path, args.model_base, model_name, args.load_8bit, args.load_4bit)
+    model=model.to(torch.device('cuda'))
+    chat_image_num = 0
+    demo.launch()