Update app.py

app.py

@@ -1,9 +1,6 @@
 import streamlit as st
-import numpy as np
-import tensorflow as tf
 from tf_coder.value_search import colab_interface
-from tf_coder.value_search import value_search_settings as settings_module
-
+from tf_coder.value_search import value_search_settings
 def get_problem():
   """Specifies a problem to run TF-Coder on. Edit this function!"""
   # A dict mapping input variable names to input tensors.
@@ -25,7 +22,7 @@ def get_problem():
 
   return inputs, output, constants, description
 
-settings = settings_module.from_dict({
+settings = value_search_settings.from_dict({
       'timeout': 300,
       'only_minimal_solutions': False,
       'max_solutions': 1,
@@ -37,6 +34,5 @@ i = st.text_area("input tensor","second test")
 
 inputs, output, constants, description = get_problem()
 t = colab_interface.run_value_search_from_colab(inputs, output, constants, description, settings)
-st.write(t.solutions)
-st.write(t.total_time)
-st.write(t.statistics)
+for e in ["benchmark", "count", "index", "settings", "solutions", "statistics", "total_time", "value_set", "values_by_weight"]:
+          st.write(eval(f"t.{e}")