zerogpu test

.gitignore

@@ -0,0 +1 @@
+__pycache__/

README.md

@@ -4,7 +4,7 @@ emoji: 😁
 colorFrom: yellow
 colorTo: red
 sdk: gradio
-sdk_version: 4.36.1
+sdk_version: 5.34.0
 app_file: app.py
 pinned: false
 license: apache-2.0

app.py

@@ -27,22 +27,6 @@ from minigpt4.tasks import *
 import socket
 import os
 
-def find_free_port(start_port, end_port):
-    for port in range(start_port, end_port + 1):
-        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
-            if sock.connect_ex(('localhost', port)) != 0:  # Port is not open
-                return port
-    raise OSError(f"Cannot find empty port in range: {start_port}-{end_port}")
-
-def set_gradio_server_port():
-    start_port = 7870
-    end_port = 9999
-    free_port = find_free_port(start_port, end_port)
-    os.environ["GRADIO_SERVER_PORT"] = str(free_port)
-    print(f"Set GRADIO_SERVER_PORT to {free_port}")
-
-# Set GRADIO_SERVER_PORT
-set_gradio_server_port()
 
 def parse_args():
     parser = argparse.ArgumentParser(description="Demo")
@@ -747,4 +731,4 @@ with gr.Blocks() as demo:
     clear.click(gradio_reset, [chat_state, img_list], [chatbot, image, text_input, chat_state, img_list], queue=False)
 
 demo.queue()
-demo.launch(share=True)
+demo.launch()

minigpt4/common/eval_utils.py

@@ -54,7 +54,7 @@ def init_model(args):
 
     model_config = cfg.model_cfg
     model_cls = registry.get_model_class(model_config.arch)
-    model = model_cls.from_config(model_config).to('cuda:0')
+    model = model_cls.from_config(model_config).to('cuda')
 
 #     import pudb; pudb.set_trace()
     key = list(cfg.datasets_cfg.keys())[0]

minigpt4/conversation/conversation.py

@@ -21,8 +21,7 @@ from typing import List, Tuple, Any
 from minigpt4.common.registry import registry
 
 import os
-from huggingface_hub import login
-login(token=os.environ['API_TOKEN'])
+
 
 class SeparatorStyle(Enum):
     """Different separator style."""
@@ -172,7 +171,7 @@ def extract_audio_from_video(video_path):
     return samples, sr
 
 class Chat:
-    def __init__(self, model, vis_processor, device='cuda:0', stopping_criteria=None):
+    def __init__(self, model, vis_processor, device='cuda', stopping_criteria=None):
         self.device = device
         self.model = model
         self.vis_processor = vis_processor

minigpt4/models/minigpt_v2.py

@@ -90,7 +90,7 @@ class MiniGPTv2(MiniGPTBase):
             self.llama_model.gradient_checkpointing_enable()
 
     def encode_img(self, image, video_features):
-        # device = 'cuda:0'
+        # device = 'cuda'
         device = image.device
         if len(image.shape) > 4:
             image = image.reshape(-1, *image.shape[-3:])

requirements.txt

@@ -16,6 +16,6 @@ torch==2.1.2
 torchvision
 timm==0.6.13
 transformers==4.30.0
-gradio
+gradio==5.34.0
 gradio_client
 numpy<2.0