DeformableConvolution v8: ngraph python API (#6520)

* Python API for DeformableConvolution op

* python codestyle

* fix python codestyle

* resolve review remarks

* fix python codestyle

ngraph/python/src/ngraph/opset8/__init__.py

@@ -33,7 +33,7 @@ from ngraph.opset6.ops import ctc_greedy_decoder_seq_len
 from ngraph.opset4.ops import ctc_loss
 from ngraph.opset3.ops import cum_sum
 from ngraph.opset3.ops import cum_sum as cumsum
-from ngraph.opset1.ops import deformable_convolution
+from ngraph.opset8.ops import deformable_convolution
 from ngraph.opset1.ops import deformable_psroi_pooling
 from ngraph.opset1.ops import depth_to_space
 from ngraph.opset1.ops import detection_output

ngraph/python/src/ngraph/opset8/ops.py

@@ -43,3 +43,59 @@ _get_node_factory_opset8 = partial(_get_node_factory, "opset8")
 
 
 # -------------------------------------------- ops ------------------------------------------------
+
+
+@nameable_op
+def deformable_convolution(
+        data: NodeInput,
+        offsets: NodeInput,
+        filters: NodeInput,
+        strides: List[int],
+        pads_begin: List[int],
+        pads_end: List[int],
+        dilations: List[int],
+        mask: Optional[NodeInput] = None,
+        auto_pad: str = "EXPLICIT",
+        group: int = 1,
+        deformable_group: int = 1,
+        bilinear_interpolation_pad: bool = False,
+        name: Optional[str] = None,
+) -> Node:
+    """Return a node which performs deformable convolution operation.
+
+    @param data: The node providing data batch tensor.
+    @param offsets: The node providing offset tensor.
+    @param filters: The node providing filters tensor.
+    @param strides: The distance (in pixels) to slide the filter on the feature map over the axes.
+    @param pads_begin: The number of pixels to add to the beginning along each axis.
+    @param pads_end: The number of pixels to add to the end along each axis.
+    @param dilations: The distance in width and height between elements (weights) in the filter.
+    @param mask: The node providing modulation scalar (mask) tensor.
+    @param auto_pad: The type of padding. Range of values: explicit, same_upper, same_lower, valid.
+    @param group: The number of groups which both output and input should be split into.
+    @param deformable_group: The number of groups which deformable values and output should be split
+                             into along the channel axis.
+    @param bilinear_interpolation_pad: The flag that determines the mode of bilinear interpolation
+                                               execution.
+    @param name: The optional new name for output node.
+    @return New node performing deformable convolution operation.
+    """
+    if mask is None:
+        inputs = as_nodes(data, offsets, filters)
+    else:
+        inputs = as_nodes(data, offsets, filters, mask)
+
+    return _get_node_factory_opset8().create(
+        "DeformableConvolution",
+        inputs,
+        {
+            "strides": strides,
+            "pads_begin": pads_begin,
+            "pads_end": pads_end,
+            "dilations": dilations,
+            "auto_pad": auto_pad,
+            "group": group,
+            "deformable_group": deformable_group,
+            "bilinear_interpolation_pad": bilinear_interpolation_pad
+        },
+    )

ngraph/python/tests/test_ngraph/test_create_op.py

@@ -104,6 +104,31 @@ def test_ctc_greedy_decoder_seq_len(fp_dtype, int_dtype, int_ci, int_sl, merge_r
     assert list(node.get_output_shape(0)) == expected_shape
 
 
+@pytest.mark.parametrize("dtype", np_types)
+def test_deformable_convolution_opset1(dtype):
+    strides = np.array([1, 1])
+    pads_begin = np.array([0, 0])
+    pads_end = np.array([0, 0])
+    dilations = np.array([1, 1])
+
+    input0_shape = [1, 1, 9, 9]
+    input1_shape = [1, 18, 7, 7]
+    input2_shape = [1, 1, 3, 3]
+    expected_shape = [1, 1, 7, 7]
+
+    parameter_input0 = ng.parameter(input0_shape, name="Input0", dtype=dtype)
+    parameter_input1 = ng.parameter(input1_shape, name="Input1", dtype=dtype)
+    parameter_input2 = ng.parameter(input2_shape, name="Input2", dtype=dtype)
+
+    node = ng_opset1.deformable_convolution(
+        parameter_input0, parameter_input1, parameter_input2, strides, pads_begin, pads_end, dilations,
+    )
+
+    assert node.get_type_name() == "DeformableConvolution"
+    assert node.get_output_size() == 1
+    assert list(node.get_output_shape(0)) == expected_shape
+
+
 @pytest.mark.parametrize("dtype", np_types)
 def test_deformable_convolution(dtype):
     strides = np.array([1, 1])
@@ -129,6 +154,34 @@ def test_deformable_convolution(dtype):
     assert list(node.get_output_shape(0)) == expected_shape
 
 
+@pytest.mark.parametrize("dtype", np_types)
+def test_deformable_convolution_mask(dtype):
+    strides = np.array([1, 1])
+    pads_begin = np.array([0, 0])
+    pads_end = np.array([0, 0])
+    dilations = np.array([1, 1])
+
+    input0_shape = [1, 1, 9, 9]
+    input1_shape = [1, 18, 7, 7]
+    input2_shape = [1, 1, 3, 3]
+    input3_shape = [1, 9, 7, 7]
+    expected_shape = [1, 1, 7, 7]
+
+    parameter_input0 = ng.parameter(input0_shape, name="Input0", dtype=dtype)
+    parameter_input1 = ng.parameter(input1_shape, name="Input1", dtype=dtype)
+    parameter_input2 = ng.parameter(input2_shape, name="Input2", dtype=dtype)
+    parameter_input3 = ng.parameter(input3_shape, name="Input3", dtype=dtype)
+
+    node = ng.deformable_convolution(
+        parameter_input0, parameter_input1, parameter_input2, strides,
+        pads_begin, pads_end, dilations, parameter_input3
+    )
+
+    assert node.get_type_name() == "DeformableConvolution"
+    assert node.get_output_size() == 1
+    assert list(node.get_output_shape(0)) == expected_shape
+
+
 @pytest.mark.parametrize("dtype", np_types)
 def test_deformable_psroi_pooling(dtype):
     output_dim = 8