Tests revision (openvinotoolkit#2749)

### Changes

- Revised `xfailed` tests.

### Reason for changes

- Absence of the revision for tests at all.

### Related tickets

- N/A

### Tests

- N/A

tests/openvino/native/quantization/test_graphs.py

@@ -32,7 +32,6 @@
 from tests.openvino.native.common import dump_model
 from tests.openvino.native.common import get_actual_reference_for_current_openvino
 from tests.openvino.native.common import get_dataset_for_test
-from tests.openvino.native.common import get_openvino_major_minor_version
 from tests.openvino.native.models import SYNTHETIC_MODELS
 from tests.openvino.native.models import DepthwiseConv3DModel
 from tests.openvino.native.models import DepthwiseConv4DModel
@@ -231,9 +230,6 @@ def test_if_model_fq_placement_ignored_scope():
 
 @pytest.mark.parametrize("q_params", [{}, {"model_type": ModelType.TRANSFORMER}], ids=["default", "transformer"])
 def test_scaled_dot_product_attention_placement(q_params, tmp_path):
-    ov_major_version, ov_minor_version = get_openvino_major_minor_version()
-    if ov_major_version < 2023 or (ov_major_version == 2023 and ov_minor_version < 3):
-        pytest.xfail("ScaledDotProductAttention is not supported until 2023.3")
     model = ScaledDotProductAttentionModel().ov_model
     quantized_model = quantize_model(model, q_params)
 
@@ -257,9 +253,6 @@ def test_scaled_dot_product_attention_placement(q_params, tmp_path):
     [SYNTHETIC_MODELS.get("LinearModel"), SYNTHETIC_MODELS.get("ConvModel"), SYNTHETIC_MODELS.get("SharedConvModel")],
 )
 def test_synthetic_models_fc_placement(model_creator_func):
-    ov_major_version, ov_minor_version = get_openvino_major_minor_version()
-    if ov_major_version < 2023 or (ov_major_version == 2023 and ov_minor_version < 3):
-        pytest.xfail("FakeConvert is not supported until 2023.3")
     model = model_creator_func()
     quantized_model = quantize_model(
         model.ov_model,

tests/openvino/native/quantization/test_weights_compression.py

@@ -33,7 +33,6 @@
 from nncf.quantization.algorithms.weight_compression.weight_lowering import reshape_weight_for_grouped_quantization
 from nncf.scopes import IgnoredScope
 from tests.openvino.native.common import get_actual_reference_for_current_openvino
-from tests.openvino.native.common import get_openvino_major_minor_version
 from tests.openvino.native.models import AWQActMatmulModel
 from tests.openvino.native.models import AWQMatmulModel
 from tests.openvino.native.models import GatherAndMatmulShareData
@@ -766,11 +765,6 @@ def test_data_type_for_num_weights(mocker):
     ],
 )
 def test_compression_for_different_dtypes(activation_dtype, weight_dtype):
-    if weight_dtype == ov.Type.bf16:
-        ov_major_version, ov_minor_version = get_openvino_major_minor_version()
-        if ov_major_version < 2024 or (ov_major_version == 2024 and ov_minor_version < 2):
-            pytest.xfail("const_node.get_data() is not supported until 2024.2")
-
     model = IdentityMatmul(weights_dtype=weight_dtype, activation_dtype=activation_dtype).ov_model
     compressed_model = compress_weights(
         model, mode=CompressWeightsMode.INT4_SYM, ratio=1, group_size=1, all_layers=True

tests/openvino/native/test_model_transformer.py

@@ -45,7 +45,6 @@
 from nncf.quantization.fake_quantize import FakeQuantizeParameters
 from tests.openvino.native.common import compare_nncf_graphs
 from tests.openvino.native.common import get_actual_reference_for_current_openvino
-from tests.openvino.native.common import get_openvino_major_minor_version
 from tests.openvino.native.models import ConvModel
 from tests.openvino.native.models import ConvNotBiasModel
 from tests.openvino.native.models import FPModel
@@ -473,9 +472,6 @@ def test_fq_insertion_pre_layer(target_layers, ref_fq_names):
 
 @pytest.mark.parametrize("target_layers, ref_fс_names", zip(TARGET_INSERT_LAYERS, TARGET_PRE_LAYER_FCS))
 def test_fc_insertion_pre_layer(target_layers, ref_fс_names):
-    ov_major_version, ov_minor_version = get_openvino_major_minor_version()
-    if ov_major_version < 2023 or (ov_major_version == 2023 and ov_minor_version < 3):
-        pytest.xfail("FakeConvert is not supported until 2023.3")
     model = LinearModel().ov_model
 
     transformed_model = create_transformed_model(
@@ -512,9 +508,6 @@ def test_fq_insertion_post_layer(target_layers, ref_fq_names):
 
 @pytest.mark.parametrize("target_layers, ref_fс_names", zip(TARGET_INSERT_LAYERS, TARGET_POST_LAYER_FCS))
 def test_fc_insertion_post_layer(target_layers, ref_fс_names):
-    ov_major_version, ov_minor_version = get_openvino_major_minor_version()
-    if ov_major_version < 2023 or (ov_major_version == 2023 and ov_minor_version < 3):
-        pytest.xfail("FakeConvert is not supported until 2023.3")
     model = LinearModel().ov_model
 
     transformed_model = create_transformed_model(
@@ -552,9 +545,6 @@ def test_fq_insertion_weights(target_layers, ref_fq_names):
 
 @pytest.mark.parametrize("target_layers, ref_fс_names", zip(TARGET_INSERT_LAYERS, TARGET_WEIGHTS_FCS))
 def test_fc_insertion_weights(target_layers, ref_fс_names):
-    ov_major_version, ov_minor_version = get_openvino_major_minor_version()
-    if ov_major_version < 2023 or (ov_major_version == 2023 and ov_minor_version < 3):
-        pytest.xfail("FakeConvert is not supported until 2023.3")
     model = LinearModel().ov_model
 
     transformed_model = create_transformed_model(

tests/openvino/native/test_smooth_quant.py

@@ -16,6 +16,7 @@
 import pytest
 import torch
 
+import nncf
 from nncf.common.graph.transformations.commands import TransformationCommand
 from nncf.openvino.graph.layer_attributes import OVLayerAttributes
 from nncf.openvino.graph.layout import OVLayoutElem
@@ -130,7 +131,7 @@ def check_scales(model: ov.Model, reference_values: Dict[str, np.ndarray], model
             (OVMatMulMetatype, OVLayerAttributes({}, inputs_attributes={"transpose": True}), 0, -2),
             (OVMatMulMetatype, OVLayerAttributes({}, inputs_attributes={"transpose": False}), 1, -2),
             (OVMatMulMetatype, OVLayerAttributes({}, inputs_attributes={"transpose": True}), 1, -1),
-            (OVMatMulMetatype, OVLayerAttributes({}, inputs_attributes={"transpose": False}), 2, RuntimeError),
+            (OVMatMulMetatype, OVLayerAttributes({}, inputs_attributes={"transpose": False}), 2, nncf.InternalError),
             (OVConvolutionMetatype, OVLayerAttributes({}, inputs_attributes={}), 0, 1),
         ),
     )

tests/openvino/native/test_statistic_collector.py

@@ -11,7 +11,6 @@
 
 
 import numpy as np
-import pytest
 
 from nncf.experimental.tensor import Tensor
 from tests.common.experimental.test_statistic_collector import TemplateTestStatisticCollector
@@ -20,11 +19,3 @@
 class TestOVStatisticCollector(TemplateTestStatisticCollector):
     def get_nncf_tensor(self, value: np.ndarray) -> Tensor:
         return Tensor(value)
-
-    @pytest.mark.skip()
-    def test_median_mad_stat_building(self):
-        pass
-
-    @pytest.mark.skip
-    def test_percentile_max_stat_building(self):
-        pass

tests/post_training/test_templates/test_smooth_quant.py

@@ -28,7 +28,6 @@
 from nncf.quantization.algorithms.post_training.algorithm import PostTrainingQuantization
 from nncf.quantization.algorithms.smooth_quant.algorithm import SmoothQuant
 from nncf.quantization.algorithms.smooth_quant.backend import SmoothQuantAlgoBackend
-from nncf.quantization.algorithms.smooth_quant.openvino_backend import OVSmoothQuantAlgoBackend
 from tests.post_training.test_templates.helpers import ConvTestModel
 from tests.post_training.test_templates.helpers import LinearMultiShapeModel
 from tests.post_training.test_templates.helpers import NonZeroLinearModel
@@ -213,9 +212,6 @@ def test__get_nodes_to_smooth_data(self, model_cls, references, tmpdir):
         model = self.backend_specific_model(model_cls(), tmpdir)
         nncf_graph = NNCFGraphFactory.create(model)
 
-        if isinstance(self.get_backend(), OVSmoothQuantAlgoBackend) and model_cls is ShareWeghtsConvAndShareLinearModel:
-            pytest.xfail("Matmuls don't share one weight in OV ir. Ticket 130912.")
-
         algo = SmoothQuant()
         algo._set_backend_entity(model)
         alpha_map = algo._get_alpha_map()
@@ -268,13 +264,14 @@ def test_get_activation_channel_axis(self, node_metatype, layer_attributes, port
         }
         node = NNCFNode(attributes)
 
-        try:  # noqa
+        if reference_value is nncf.InternalError:
+            with pytest.raises(
+                nncf.InternalError, match=f"{node.metatype.name} can not take more than 2 input tensors."
+            ):
+                backend.get_activation_channel_axis(node, port_id)
+        else:
             activation_channel_axis = backend.get_activation_channel_axis(node, port_id)
-        except nncf.InternalError as e:  # noqa
-            # TODO: this is wrong, should only expect an exception for cases where the exception is known to be raised
-            #  with pytest.raises(...)
-            pytest.xfail("FIXME")
-        assert activation_channel_axis == reference_value
+            assert activation_channel_axis == reference_value
 
     def test_get_weight_channel_axis(self, node_metatype, layer_attributes, reference_value):
         backend = self.get_backend()

tests/torch/ptq/test_statistic_collector.py

@@ -11,7 +11,6 @@
 
 
 import numpy as np
-import pytest
 import torch
 
 from nncf.experimental.tensor import Tensor
@@ -21,7 +20,3 @@
 class TestPTStatisticCollector(TemplateTestStatisticCollector):
     def get_nncf_tensor(self, value: np.ndarray) -> Tensor:
         return Tensor(torch.tensor(value))
-
-    @pytest.mark.skip
-    def test_raw_max_stat_building(self):
-        pass

tests/torch/sparsity/movement/test_model_saving.py

@@ -15,7 +15,6 @@
 import numpy as np
 import onnx
 import onnxruntime
-import openvino as ov
 import pytest
 import torch
 from addict import Dict
@@ -184,9 +183,7 @@ def test_same_outputs_in_torch_and_exported_onnx(self, tmp_path: Path, recipe: B
             ),
             Dict(
                 nncf_weight_ratio=0.43,
-                ov_weight_ratio=(
-                    0.29 if version.parse(ov.runtime.__version__.split("-")[0]) < version.parse("2024.2.0") else 0.33
-                ),
+                ov_weight_ratio=0.33,
                 recipe=SwinRunRecipe().model_config_(
                     num_heads=[4],
                     num_labels=1,