Adding Gradio App

gradio_app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+import matplotlib
+import matplotlib.pyplot as plt
+from quantum_perceptron import Perceptron
+
+matplotlib.pyplot.switch_backend('Agg')
+
+def run_perceptron(
+        num_qubits: int,
+        input_value: int,
+        weight_value: int,
+        num_iters: int
+):
+    p = Perceptron(num_qubits, weight_value, input_value)
+    counts = p.measure_circuit(num_iters)
+    prob_1 = counts.get('1', 0) / num_iters
+    freq_hist = plt.figure()
+    plt.bar(counts.keys(), counts.values(), width=0.5)
+    for i, v in enumerate(list(counts.values())):
+        plt.text(i, v+10, v)
+    plt.xlabel('Measured State')
+    plt.ylabel('Frequency of Measured State')
+    plt.tight_layout()
+    return prob_1, freq_hist
+
+app_inputs = [
+    gr.Slider(1, 9, value=2, step=1, label="Number of Qubits"),
+    gr.Number(value=12, label="Input Value", precision=0),
+    gr.Number(value=13, label="Weight Value", precision=0),
+    gr.Number(value=1000, label="Number of Measurement Iterations", precision=0),
+]
+
+app_outputs = [
+    gr.Number(precision=2, label="Probability of Firing Perceptron"),
+    gr.Plot(label="Distribution of Measurement Frequencies")
+]
+
+demo = gr.Interface(
+    fn=run_perceptron,
+    inputs=app_inputs,
+    outputs=app_outputs,
+)
+demo.launch(share=True)

requirements.txt

@@ -2,4 +2,5 @@ numpy
 qiskit
 pycodestyle
 pytest
-mypy
+mypy
+gradio