Added first_refinement_step to examples

app.py

@@ -401,31 +401,31 @@ def main():
                 examples=[
                     [
                         PROMPT1, "2,3;6,7", "1,4,5,8,9", "10",
-                        15, 10, 3, 1, 1,
+                        15, 10, 15, 3, 1, 1,
                         7.5, 1, 5, 0.2, 8,
                         12,
                     ],
                     [
                         PROMPT2, "7,8,17;11,12,17;15,16,17", "5,6,9,10,13,14,18,19", "21",
-                        25, 18, 3, 1, 1,
+                        25, 18, 15, 3, 1, 1,
                         7.5, 1, 5, 0.2, 8,
                         286,
                     ],
                     [
                         PROMPT3, "7;10;13,14;17", "5,6,8,9,11,12,15,16", "17",
-                        18, 12, 3, 1, 1,
+                        18, 12, 15, 3, 1, 1,
                         7.5, 1, 5, 0.2, 8,
                         216,
                     ],
                     [
                         PROMPT4, "9,10;13,14;17", "1,4,5,7,8,11,12,15,16", "17",
-                        25, 18, 3, 1, 1,
+                        25, 18, 15, 3, 1, 1,
                         7.5, 1, 5, 0.2, 8,
                         82,
                     ],
                     [
                         PROMPT5, "2,3;6,7;10,11;14,15;18,19", "1,4,5,8,9,12,13,16,17,20,21", "22",
-                        18, 12, 3, 1, 1,
+                        18, 12, 15, 3, 1, 1,
                         7.5, 1, 5, 0.2, 8,
                         152,
                     ],
@@ -433,7 +433,7 @@ def main():
                 fn=build_example_layout,
                 inputs=[
                     prompt, subject_token_indices, filter_token_indices, num_tokens,
-                    init_step_size, final_step_size, num_clusters_per_subject, cross_loss_scale, self_loss_scale,
+                    init_step_size, final_step_size, first_refinement_step, num_clusters_per_subject, cross_loss_scale, self_loss_scale,
                     classifier_free_guidance_scale, batch_size, num_iterations, loss_threshold, num_guidance_steps,
                     seed,
                 ],