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app.py

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+import gradio as gr
+import torch
+import time
+
+def get_gpu_info():
+    """Get information about available GPUs."""
+    if torch.cuda.is_available():
+        gpu_count = torch.cuda.device_count()
+        gpu_info = []
+        for i in range(gpu_count):
+            name = torch.cuda.get_device_name(i)
+            mem_total = torch.cuda.get_device_properties(i).total_memory / (1024**3)
+            gpu_info.append(f"GPU {i}: {name} ({mem_total:.1f}GB)")
+        return "\n".join(gpu_info)
+    return "No GPU available"
+
+def test_gpu(gpu_name):
+    """Test the selected GPU with a simple computation."""
+    if not torch.cuda.is_available():
+        return "No GPU available on this system"
+    
+    # Find the GPU index based on the name
+    device_idx = 0
+    for i in range(torch.cuda.device_count()):
+        if gpu_name in torch.cuda.get_device_name(i):
+            device_idx = i
+            break
+    
+    device = torch.device(f"cuda:{device_idx}")
+    
+    # Simple GPU computation test
+    start_time = time.time()
+    
+    # Create a tensor on GPU
+    x = torch.randn(1000, 1000, device=device)
+    y = torch.randn(1000, 1000, device=device)
+    
+    # Perform matrix multiplication
+    z = torch.matmul(x, y)
+    
+    # Move back to CPU
+    result = z.cpu()
+    
+    elapsed = time.time() - start_time
+    
+    return f"GPU Test Successful!\n\nSelected GPU: {gpu_name}\nComputation Time: {elapsed:.4f} seconds\nResult shape: {result.shape}\nResult sum: {result.sum().item():.2f}"
+
+def get_available_gpus():
+    """Get list of available GPU names."""
+    if torch.cuda.is_available():
+        return [torch.cuda.get_device_name(i) for i in range(torch.cuda.device_count())]
+    return ["No GPU available"]
+
+# Get available GPUs
+available_gpus = get_available_gpus()
+gpu_info = get_gpu_info()
+
+# Create Gradio interface
+with gr.Blocks(title="GPU Tester") as demo:
+    gr.Markdown("# GPU Selector and Tester")
+    gr.Markdown(f"### Available GPU Information:\n```\n{gpu_info}\n```")
+    
+    with gr.Row():
+        with gr.Column():
+            gpu_dropdown = gr.Dropdown(
+                choices=available_gpus if available_gpus else ["No GPU available"],
+                label="Select GPU",
+                value=available_gpus[0] if available_gpus else None
+            )
+            
+            test_button = gr.Button("Test GPU", variant="primary")
+        
+        with gr.Column():
+            output = gr.Textbox(label="Test Results", lines=10)
+    
+    test_button.click(fn=test_gpu, inputs=gpu_dropdown, outputs=output)
+    
+    gr.Markdown("---")
+    gr.Markdown("This app allows you to select a GPU and test its computation capability using PyTorch.")
+
+# Launch the app
+demo.launch(server_name="0.0.0.0", server_port=7860)