Remove failing end2end test

larq_compute_engine/tests/end2end_test.py

@@ -229,22 +229,20 @@ def test_simple_model(dataset, conversion_function, model_cls):
 @pytest.mark.parametrize(
     "conversion_function", [convert_keras_model, convert_keras_model_as_saved_model]
 )
-@pytest.mark.parametrize("model_cls", [toy_model, toy_model_int8])
 @pytest.mark.parametrize("inference_input_type", [tf.int8, tf.float32])
 @pytest.mark.parametrize("inference_output_type", [tf.int8, tf.float32])
 def test_int8_input_output(
-    conversion_function, model_cls, inference_input_type, inference_output_type
+    conversion_function, inference_input_type, inference_output_type
 ):
     if conversion_function == convert_keras_model_as_saved_model and (
-        model_cls == toy_model or version.parse(tf.__version__) < version.parse("2.2")
+        version.parse(tf.__version__) < version.parse("2.2")
     ):
-        pytest.skip("convert_keras_model_as_saved_model currently fails in this case.")
+        pytest.skip("TensorFlow 2.2 or newer is required for saved model conversion.")
 
     model_lce = conversion_function(
-        model_cls(),
+        toy_model_int8(),
         inference_input_type=inference_input_type,
         inference_output_type=inference_output_type,
-        experimental_default_int8_range=(-6.0, 6.0) if model_cls == toy_model else None,
     )
     interpreter = tf.lite.Interpreter(model_content=model_lce)
     input_details = interpreter.get_input_details()