more tests to see the probşem with enabling hardware

.config/accelerate/default_config.yaml

@@ -0,0 +1,15 @@
+compute_environment: LOCAL_MACHINE
+distributed_type: 'NO'
+downcast_bf16: 'no'
+gpu_ids: all
+machine_rank: 0
+main_training_function: main
+mixed_precision: 'no'
+num_machines: 1
+num_processes: 1
+rdzv_backend: static
+same_network: true
+tpu_env: []
+tpu_use_cluster: false
+tpu_use_sudo: false
+use_cpu: false

Dockerfile

@@ -0,0 +1,28 @@
+FROM nvidia/cuda:11.7.1-runtime-ubuntu22.04
+
+# Set up system
+RUN apt-get update && apt-get install -y \
+    python3-pip \
+    python3-dev \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /code
+
+# Copy requirements first to leverage Docker cache
+COPY requirements.txt .
+
+# Install dependencies
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application
+COPY . .
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1
+ENV GRADIO_SERVER_NAME=0.0.0.0
+ENV GRADIO_SERVER_PORT=7860
+
+# Command to run the application
+CMD ["python3", "app.py"]

app.py

@@ -1,6 +1,32 @@
+import torch
+import sys
+import subprocess
+
+def check_gpu_status():
+    print("Python version:", sys.version)
+    print("PyTorch version:", torch.__version__)
+    print("CUDA available:", torch.cuda.is_available())
+    print("CUDA version:", torch.version.cuda if torch.cuda.is_available() else "Not available")
+    
+    if torch.cuda.is_available():
+        print("GPU Device:", torch.cuda.get_device_name(0))
+        print("GPU Memory:", torch.cuda.get_device_properties(0).total_memory / 1024**3, "GB")
+    
+    try:
+        nvidia_smi = subprocess.check_output(["nvidia-smi"])
+        print("nvidia-smi output:")
+        print(nvidia_smi.decode())
+    except:
+        print("nvidia-smi not available")
+
+# Run GPU check at startup
+print("=== GPU Status Check ===")
+check_gpu_status()
+print("======================")
+
+# Rest of your imports
 import gradio as gr
 import easyocr
-import torch
 from transformers import pipeline, DistilBertTokenizer, DistilBertForSequenceClassification
 import numpy as np
 from PIL import Image

requirements.txt

@@ -1,8 +1,10 @@
---extra-index-url https://download.pytorch.org/whl/cu113
-torch
+--extra-index-url https://download.pytorch.org/whl/cu117
+torch==2.0.1+cu117
+torchvision==0.15.2+cu117
+torchaudio==2.0.2+cu117
 gradio
-transformers
 easyocr
+transformers
 pandas
 numpy
 pillow

runtime.txt

@@ -0,0 +1 @@
+python-3.10