Hotfix of #827 test_auto_preset_converted_correctly fails (#828)

* Hotfix of #827 test_auto_preset_converted_correctly fails when the PC performance is quite high

test/unit/api/test_presets.py

@@ -89,11 +89,13 @@ def test_presets_inserting_in_params_correct():
 
 def test_auto_preset_converted_correctly():
     """ Checks that the proposed method of automatic preset detection correctly converts a preset """
+    tiny_timeout_value = 0.005
+    large_pop_size = 500
     data = data_with_binary_features_and_categorical_target()
 
     simple_init_assumption = Pipeline(PrimaryNode('logit'))
-    fedot_model = Fedot(problem='classification', preset='auto', timeout=0.01,
-                        initial_assumption=simple_init_assumption, pop_size=500)
+    fedot_model = Fedot(problem='classification', preset='auto', timeout=tiny_timeout_value,
+                        initial_assumption=simple_init_assumption, pop_size=large_pop_size)
     # API must return initial assumption without composing and tuning (due to population size is too large)
     fedot_model.fit(data)
     assert fedot_model.api_composer.preset_name == FAST_TRAIN_PRESET_NAME