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# img_gen.py | |
#img_gen_modal.py | |
# img_gen.py | |
# img_gen_modal.py | |
import modal | |
import random | |
import io | |
from config.config import prompts, models # Indirect import | |
import os | |
CACHE_DIR = "/model_cache" | |
# Define the Modal image | |
image = ( | |
#modal.Image.from_registry("nvidia/cuda:12.2.0-devel-ubuntu22.04", add_python="3.9") | |
modal.Image.debian_slim(python_version="3.9") # Base image | |
.apt_install( | |
"git", | |
) | |
.pip_install( | |
"diffusers", | |
"transformers", | |
"torch", | |
"accelerate", | |
"gradio>=4.44.1", | |
"safetensors", | |
"pillow", | |
"sentencepiece", | |
"hf_transfer", | |
"huggingface_hub[hf_transfer]", | |
"aria2", # aria2 for ultra-fast parallel downloads | |
f"git+https://github.com/huggingface/transformers.git" | |
) | |
.env( | |
{ | |
"HF_HUB_ENABLE_HF_TRANSFER": "1", "HF_HOME": "HF_HOME", "HF_HUB_CACHE": CACHE_DIR | |
} | |
) | |
) | |
# Create a Modal app | |
app = modal.App("tools-test-dir", image=image) | |
with image.imports(): | |
import diffusers | |
import os | |
import gradio | |
from datetime import datetime | |
flux_model_vol = modal.Volume.from_name("flux-model-vol", create_if_missing=True) # Reference your volume | |
def test_dir(): | |
# OS | |
# Get the current working directory (should be /root) | |
current_directory = os.getcwd() | |
print(f"Current working directory: {current_directory}") | |
# List the contents of the current directory | |
print("Contents of current modal directory:") | |
print(os.listdir(current_directory)) | |
# MODAL | |
print ("MODAL") | |
print ("MODAL ROOT") | |
# List contents of the volume | |
file_entries = flux_model_vol.listdir("/") # Replace "/data" with your volume path | |
# Extract and print only the paths | |
paths = [entry.path for entry in file_entries] | |
print("Paths in volume:") | |
print(paths) | |