[NNCF][BC] Add test case with depthwise/transpose convolutions to tem…

…plate and backend specific tests (#3004)

### Changes

- Added simple Depthwise and Transpose Convolution models in
`tests/cross_fw/test_templates/helpers.py`.

- Updated `map_references` for Torch FX backend to assign the right
reference node names for model classes Depthwise and Transpose
Convolutions.

- Added `ONNXConvolutionTransposeMetatype` into the list of
OPERATIONS_WITH_BIAS for ONNX.

- Added the missing target for Transpose Conv in `transformations.py`
for Torch FX in the function `_is_conv`.

- Added `OVConvolutionBackpropDataMetatype` into the list of
OPERATIONS_WITH_BIAS for OpenVino backend

- Replaced the unet graph in quantized reference graphs for FX backend.

### Extra Changes

- [X] Update and finalize the right changes to make in
`tests/openvino/native/test_bias_correction.py` for Transpose
Convolution node name and accommodate for the changes in the name after
each run.

### Closes issue

#2916

---------

Co-authored-by: dlyakhov <[email protected]>

nncf/experimental/torch/fx/transformations.py

@@ -569,6 +569,7 @@ def _is_conv(n: torch.fx.Node):
     return n.op == "call_function" and n.target in (
         torch.ops.aten.conv1d.default,
         torch.ops.aten.conv2d.default,
+        torch.ops.aten.conv_transpose2d.input,
     )
 
 

nncf/onnx/graph/metatypes/groups.py

@@ -142,7 +142,11 @@
     # TODO: Need to add MatMul with the separate bias support (CVS-135433)
 ]
 
-OPERATIONS_WITH_BIAS = [*OPERATIONS_WITH_BIAS_REDUCED, onnx_metatypes.ONNXDepthwiseConvolutionMetatype]
+OPERATIONS_WITH_BIAS = [
+    *OPERATIONS_WITH_BIAS_REDUCED,
+    onnx_metatypes.ONNXDepthwiseConvolutionMetatype,
+    onnx_metatypes.ONNXConvolutionTransposeMetatype,
+]
 
 
 QUANTIZE_DEQUANTIZE_OPERATIONS = [

nncf/openvino/graph/metatypes/groups.py

@@ -192,7 +192,11 @@
     ov_metatypes.OVMatMulMetatype,
 ]
 
-OPERATIONS_WITH_BIAS = [*OPERATIONS_WITH_BIAS_REDUCED, ov_metatypes.OVDepthwiseConvolutionMetatype]
+OPERATIONS_WITH_BIAS = [
+    *OPERATIONS_WITH_BIAS_REDUCED,
+    ov_metatypes.OVDepthwiseConvolutionMetatype,
+    ov_metatypes.OVConvolutionBackpropDataMetatype,
+]
 
 CONV_OPERATIONS = [
     ov_metatypes.OVConvolutionMetatype,

tests/cross_fw/test_templates/helpers.py

@@ -19,6 +19,8 @@
 from nncf import Dataset
 from tests.torch.helpers import create_bn
 from tests.torch.helpers import create_conv
+from tests.torch.helpers import create_depthwise_conv
+from tests.torch.helpers import create_transpose_conv
 from tests.torch.helpers import set_torch_seed
 
 TTensor = TypeVar("TTensor")
@@ -436,3 +438,31 @@ def __init__(self):
 
     def forward(self, query, key, value):
         return nn.functional.scaled_dot_product_attention(query, key, value)
+
+
+class DepthwiseConvTestModel(nn.Module):
+    INPUT_SIZE = [1, 2, 4, 4]
+
+    def __init__(self):
+        super().__init__()
+        with set_torch_seed():
+            self.conv = create_depthwise_conv(2, 1, 1, 1)
+            self.conv.weight.data = torch.randn([2, 1, 1, 1])
+            self.conv.bias.data = torch.randn([2])
+
+    def forward(self, x):
+        return self.conv(x)
+
+
+class TransposeConvTestModel(nn.Module):
+    INPUT_SIZE = [1, 1, 3, 3]
+
+    def __init__(self):
+        super().__init__()
+        with set_torch_seed():
+            self.conv = create_transpose_conv(1, 2, 2, 1, 1, 2)
+            self.conv.weight.data = torch.randn([1, 2, 2, 2])
+            self.conv.bias.data = torch.randn([2])
+
+    def forward(self, x):
+        return self.conv(x)

tests/cross_fw/test_templates/test_bias_correction.py

@@ -22,9 +22,11 @@
 from nncf.quantization.algorithms.bias_correction.backend import BiasCorrectionAlgoBackend
 from nncf.quantization.algorithms.post_training.algorithm import PostTrainingQuantization
 from tests.cross_fw.test_templates.helpers import ConvTestModel
+from tests.cross_fw.test_templates.helpers import DepthwiseConvTestModel
 from tests.cross_fw.test_templates.helpers import MultipleConvTestModel
 from tests.cross_fw.test_templates.helpers import SplittedModel
 from tests.cross_fw.test_templates.helpers import StaticDatasetMock
+from tests.cross_fw.test_templates.helpers import TransposeConvTestModel
 
 TModel = TypeVar("TModel")
 TTensor = TypeVar("TTensor")
@@ -139,6 +141,8 @@ def quantized_test_model(self, tmpdir) -> TModel:
                 },
             ),
             (ConvTestModel, {"/conv/Conv": [0.11085186, 1.0017344]}),
+            (DepthwiseConvTestModel, {"/conv/Conv": [-1.1229, -0.1863]}),
+            (TransposeConvTestModel, {"/conv/ConvTranspose": [0.66797173, -0.7070703]}),
         ),
     )
     def test_update_bias(self, model_cls, ref_biases, tmpdir):

tests/onnx/quantization/test_bias_correction.py

@@ -22,8 +22,10 @@
 from nncf.onnx.graph.node_utils import get_bias_value
 from nncf.quantization.algorithms.bias_correction.onnx_backend import ONNXBiasCorrectionAlgoBackend
 from tests.cross_fw.test_templates.helpers import ConvTestModel
+from tests.cross_fw.test_templates.helpers import DepthwiseConvTestModel
 from tests.cross_fw.test_templates.helpers import MultipleConvTestModel
 from tests.cross_fw.test_templates.helpers import SplittedModel
+from tests.cross_fw.test_templates.helpers import TransposeConvTestModel
 from tests.cross_fw.test_templates.test_bias_correction import TemplateTestBCAlgorithm
 from tests.onnx.quantization.common import compare_nncf_graph
 
@@ -211,6 +213,8 @@ def test__get_subgraph_data_for_node(self, quantized_test_model, layer_name, ref
                 },
             ),
             (ConvTestModel, {("/conv/Conv", 0): ("nncf_model_input_0", 0)}),
+            (DepthwiseConvTestModel, {("/conv/Conv", 0): ("nncf_model_input_0", 0)}),
+            (TransposeConvTestModel, {("/conv/ConvTranspose", 0): ("nncf_model_input_0", 0)}),
         ),
     )
     def test_verify_collected_stat_inputs_map(self, model_cls, ref_stat_inputs_map, tmpdir):

tests/openvino/native/test_bias_correction.py

@@ -22,13 +22,17 @@
 from nncf.openvino.graph.node_utils import get_bias_value
 from nncf.quantization.algorithms.bias_correction.openvino_backend import OVBiasCorrectionAlgoBackend
 from tests.cross_fw.test_templates.helpers import ConvTestModel
+from tests.cross_fw.test_templates.helpers import DepthwiseConvTestModel
 from tests.cross_fw.test_templates.helpers import MultipleConvTestModel
 from tests.cross_fw.test_templates.helpers import SplittedModel
+from tests.cross_fw.test_templates.helpers import TransposeConvTestModel
 from tests.cross_fw.test_templates.test_bias_correction import TemplateTestBCAlgorithm
 from tests.openvino.native.common import compare_nncf_graphs
 
 
 class TestOVBCAlgorithm(TemplateTestBCAlgorithm):
+    TRANSPOSE_CONV_NAME = "/conv/ConvTranspose/WithoutBiases"
+
     @staticmethod
     def list_to_backend_type(data: List) -> np.ndarray:
         return np.array(data)
@@ -42,6 +46,10 @@ def backend_specific_model(model: torch.nn.Module, tmp_dir: str):
         onnx_path = f"{tmp_dir}/model.onnx"
         torch.onnx.export(model, torch.rand(model.INPUT_SIZE), onnx_path, opset_version=13, input_names=["input.1"])
         ov_model = ov.convert_model(onnx_path)
+        if isinstance(model, TransposeConvTestModel):
+            for node in ov_model.get_ops():
+                if node.get_type_name() == "ConvolutionBackpropData":
+                    node.set_friendly_name(TestOVBCAlgorithm.TRANSPOSE_CONV_NAME)
         return ov_model
 
     @staticmethod
@@ -206,6 +214,8 @@ def test__get_subgraph_data_for_node(self, quantized_test_model, layer_name, ref
                 },
             ),
             (ConvTestModel, {("/conv/Conv/WithoutBiases", 0): ("input.1", 0)}),
+            (DepthwiseConvTestModel, {("/conv/Conv/WithoutBiases", 0): ("input.1", 0)}),
+            (TransposeConvTestModel, {(TRANSPOSE_CONV_NAME, 0): ("input.1", 0)}),
         ),
     )
     def test_verify_collected_stat_inputs_map(self, model_cls, ref_stat_inputs_map, tmpdir):