fix test and coverage

Author: irenab

model_compression_toolkit/core/common/mixed_precision/sensitivity_evaluation.py

@@ -75,7 +75,7 @@ def __init__(self,
         self.fw_impl = fw_impl
         self.disable_activation_for_metric = disable_activation_for_metric
         if self.quant_config.use_hessian_based_scores:
-            if not isinstance(hessian_info_service, HessianInfoService):
+            if not isinstance(hessian_info_service, HessianInfoService):    # pragma: no cover
                 Logger.critical(
                     f"When using Hessian-based approximations for sensitivity evaluation, a valid HessianInfoService object is required; found {type(hessian_info_service)}.")
             self.hessian_info_service = hessian_info_service

model_compression_toolkit/core/common/mixed_precision/set_layer_to_bitwidth.py

@@ -15,7 +15,7 @@
 import typing
 from typing import Any, Optional
 
-if typing.TYPE_CHECKING:
+if typing.TYPE_CHECKING:    # pragma: no cover
     from model_compression_toolkit.core.common.framework_implementation import FrameworkImplementation
 
 

tests_pytest/_fw_tests_common_base/base_sensitivity_eval_integ_test.py

@@ -223,18 +223,22 @@ def test_configure_mp_model_errors(self):
         """ Test errors during model configuration. """
         model, g, se = self.model, self.g, self.se
         with pytest.raises(ValueError, match='Requested configuration is either empty or contain only None values'):
-            se._configured_mp_model({}, {})
+            with se._configured_mp_model({}, {}):
+                pass
 
         conv, relu, conv_tr = [n.name for n in g.get_topo_sorted_nodes() if n.has_configurable_activation()]
         _, fc = [n.name for n in g.get_topo_sorted_nodes() if n.has_any_configurable_weight()]
         with pytest.raises(ValueError, match='Requested configuration is either empty or contain only None values'):
-            se._configured_mp_model({relu: None}, {conv: None})
+            with se._configured_mp_model({relu: None}, {conv: None}):
+                pass
 
         with pytest.raises(ValueError, match='Not all mp configs were consumed'):
-            se._configured_mp_model({conv: 1}, {conv: 0, relu: None})
+            with se._configured_mp_model({conv: 1}, {conv: 0, relu: None}):
+                pass
 
         with pytest.raises(ValueError, match='Not all mp configs were consumed'):
-            se._configured_mp_model({conv: 1, fc: 0}, {conv: 0})
+            with se._configured_mp_model({conv: 1, fc: 0}, {conv: 0}):
+                pass
 
     def test_compute_metric_method(self):
         """ Test compute_metric method (not the metric computation itself) """

tests_pytest/pytorch_tests/integration_tests/core/mixed_precision/test_sensitivity_evaluation.py

@@ -68,7 +68,7 @@ def test_configure_mp_model(self):
         super().test_configure_mp_model()
 
     def test_configure_mp_model_errors(self):
-        super().test_configure_mp_model()
+        super().test_configure_mp_model_errors()
 
     def test_compute_metric_method(self):
         super().test_compute_metric_method()