fix and enable torch bops tests

sony · Mar 3, 2025 · fd444d5 · fd444d5
1 parent 4a1f731
commit fd444d5
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Showing 2 changed files with 9 additions and 9 deletions.
diff --git a/tests/pytorch_tests/model_tests/feature_models/mixed_precision_bops_test.py b/tests/pytorch_tests/model_tests/feature_models/mixed_precision_bops_test.py
@@ -131,7 +131,7 @@ def compare(self, quantized_model, float_model, input_x=None, quantization_info=
         # Verify that some layers got bit-width smaller than 8 bits (so checking candidate index is not 0)
         self.unit_test.assertTrue(any(i > 0 for i in quantization_info.mixed_precision_cfg))
         # Verify final BOPs utilization
-        self.unit_test.assertTrue(quantization_info.final_resource_utilization.bops <= self.get_resource_utilization().bops)
+        self.unit_test.assertTrue(self.get_resource_utilization().is_satisfied_by(quantization_info.final_resource_utilization))
 
 
 class MixedPrecisionBopsBasicTest(BaseMixedPrecisionBopsTest):
@@ -198,23 +198,24 @@ def __init__(self, unit_test):
         super().__init__(unit_test)
 
     def get_resource_utilization(self):
-        return ResourceUtilization(activation_memory=1000, bops=3000000)  # should require some quantization to all layers
+        # act max cut 2bit = 2*(30*30*4)*2/8 = 1800
+        return ResourceUtilization(activation_memory=1800, bops=3000000)  # should require some quantization to all layers
 
 
 class MixedPrecisionBopsAndTotalMemoryUtilizationTest(MixedPrecisionBopsAllWeightsLayersTest):
     def __init__(self, unit_test):
         super().__init__(unit_test)
 
     def get_resource_utilization(self):
-        return ResourceUtilization(total_memory=1100, bops=3000000)  # should require some quantization to all layers
+        return ResourceUtilization(total_memory=2000, bops=3000000)  # should require some quantization to all layers
 
 
 class MixedPrecisionBopsWeightsActivationUtilizationTest(MixedPrecisionBopsAllWeightsLayersTest):
     def __init__(self, unit_test):
         super().__init__(unit_test)
 
     def get_resource_utilization(self):
-        return ResourceUtilization(weights_memory=150, activation_memory=1000, bops=3000000)  # should require some quantization to all layers
+        return ResourceUtilization(weights_memory=150, activation_memory=1800, bops=3000000)  # should require some quantization to all layers
 
 
 class MixedPrecisionBopsMultipleOutEdgesTest(BaseMixedPrecisionBopsTest):

diff --git a/tests/pytorch_tests/model_tests/test_feature_models_runner.py b/tests/pytorch_tests/model_tests/test_feature_models_runner.py
@@ -624,11 +624,10 @@ def test_mixed_precision_bops_utilization(self):
         MixedPrecisionBopsAllWeightsLayersTest(self).run_test()
         MixedPrecisionWeightsOnlyBopsTest(self).run_test()
         MixedPrecisionActivationOnlyBopsTest(self).run_test()
-        # TODO: uncomment these tests when the issue of combined BOPs and other RU metrics is solved.
-        # MixedPrecisionBopsAndWeightsMemoryUtilizationTest(self).run_test()
-        # MixedPrecisionBopsAndActivationMemoryUtilizationTest(self).run_test()
-        # MixedPrecisionBopsAndTotalMemoryUtilizationTest(self).run_test()
-        # MixedPrecisionBopsWeightsActivationUtilizationTest(self).run_test()
+        MixedPrecisionBopsAndWeightsMemoryUtilizationTest(self).run_test()
+        MixedPrecisionBopsAndActivationMemoryUtilizationTest(self).run_test()
+        MixedPrecisionBopsAndTotalMemoryUtilizationTest(self).run_test()
+        MixedPrecisionBopsWeightsActivationUtilizationTest(self).run_test()
         MixedPrecisionBopsMultipleOutEdgesTest(self).run_test()
 
     def test_mixed_precision_distance_functions(self):