Create app.py

app.py

@@ -0,0 +1,91 @@
+import gradio as gr
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Predefined hyperparameter sets
+PARAM_SETS = {
+    "Set A": {"param1": 0.1, "param2": 0.01, "param3": 100, "param4": 50},
+    "Set B": {"param1": 0.2, "param2": 0.02, "param3": 200, "param4": 100}
+}
+
+def generate_plot(param1, param2, param3, param4):
+    """Generate visualization based on hyperparameters"""
+    plt.figure(figsize=(10, 6))
+    x = np.linspace(0, 10, int(param3))
+    y = np.sin(x * param1) * np.cos(x * param2) * param4
+    plt.plot(x, y)
+    plt.title(f'Parameter Visualization (p1={param1}, p2={param2}, p3={param3}, p4={param4})')
+    plt.grid(True)
+    return plt
+
+def process_inputs(param_set, custom_param1, custom_param2, custom_param3, custom_param4, 
+                  input1, input2):
+    """Process inputs and return results"""
+    # Determine which parameter set to use
+    if param_set in PARAM_SETS:
+        params = PARAM_SETS[param_set]
+        p1, p2, p3, p4 = params.values()
+    else:
+        p1, p2, p3, p4 = custom_param1, custom_param2, custom_param3, custom_param4
+    
+    # Generate plot
+    plot = generate_plot(p1, p2, p3, p4)
+    
+    # Calculate result (example calculation)
+    result = (input1 * p1 + input2 * p2) * (p3 + p4)
+    
+    return plot, result
+
+# Create interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Hyperparameter Calculation and Visualization System")
+    
+    with gr.Row():
+        with gr.Column():
+            # Hyperparameter selection section
+            param_set = gr.Dropdown(
+                choices=["Custom"] + list(PARAM_SETS.keys()),
+                value="Custom",
+                label="Select Hyperparameter Set"
+            )
+            
+            # Custom parameter inputs
+            custom_param1 = gr.Number(value=0.1, label="Parameter 1 (Learning Rate)")
+            custom_param2 = gr.Number(value=0.01, label="Parameter 2 (Weight Decay)")
+            custom_param3 = gr.Number(value=100, label="Parameter 3 (Iterations)")
+            custom_param4 = gr.Number(value=50, label="Parameter 4 (Batch Size)")
+            
+            # Input values
+            input1 = gr.Number(value=1.0, label="Input Value 1")
+            input2 = gr.Number(value=1.0, label="Input Value 2")
+            
+            submit_btn = gr.Button("Calculate")
+        
+        with gr.Column():
+            # Output section
+            plot_output = gr.Plot(label="Parameter Visualization")
+            result_output = gr.Number(label="Calculation Result")
+    
+    # Auto-fill parameters when selecting predefined sets
+    def update_params(param_set):
+        if param_set in PARAM_SETS:
+            params = PARAM_SETS[param_set]
+            return [params["param1"], params["param2"], params["param3"], params["param4"]]
+        return [gr.skip(), gr.skip(), gr.skip(), gr.skip()]
+    
+    param_set.change(
+        update_params,
+        inputs=[param_set],
+        outputs=[custom_param1, custom_param2, custom_param3, custom_param4]
+    )
+    
+    # Submit button event
+    submit_btn.click(
+        process_inputs,
+        inputs=[param_set, custom_param1, custom_param2, custom_param3, custom_param4,
+                input1, input2],
+        outputs=[plot_output, result_output]
+    )
+
+# Launch application
+demo.launch()