Update app.py

app.py

@@ -9,7 +9,7 @@ from sklearn import linear_model
 from sklearn.svm import l1_min_c
 
 
-def train_it(solver, intersect_scaling, tol, max_iter,warm_start):
+def train_it(solver, intersect_scaling, tol, max_iter):
     iris = datasets.load_iris()
     X = iris.data
     y = iris.target
@@ -26,7 +26,7 @@ def train_it(solver, intersect_scaling, tol, max_iter,warm_start):
         solver=solver,
         tol=tol,
         max_iter=int(max_iter),
-        warm_start=warm_start,
+        warm_start=True,
         intercept_scaling=intersect_scaling,
     )
 
@@ -62,9 +62,6 @@ with gr.Blocks() as demo:
             solver = gr.Dropdown(
                 ["liblinear", "saga"], label="Solver", value="liblinear"
             )
-            warm_start = gr.Dropdown(
-                ["True", "False"], label="Warm Start", value="True"
-            )
         with gr.Column(align="center"):
             intersect_scaling = gr.Slider(
                 value=10000.0,
@@ -86,7 +83,7 @@ with gr.Blocks() as demo:
     train_buttion = gr.Button(label="Train")
 
     train_buttion.click(
-        train_it, inputs=[solver, intersect_scaling, tol, max_iter,warm_start], outputs=gr.Plot()
+        train_it, inputs=[solver, intersect_scaling, tol, max_iter], outputs=gr.Plot()
     )