Use groups

Author: Alejandro Gaston Alvarez Franceschi

coremltools/converters/mil/frontend/torch/test/test_torch_ops.py

@@ -1488,6 +1488,7 @@ def test_convolution1d(
             padding=padding,
             dilation=dilation,
             bias=bias,
+            groups=groups,
         )
         self.run_compare_torch(
             (1, in_channels, length),
@@ -1557,6 +1558,7 @@ def test_convolution2d(
             padding=padding,
             dilation=dilation,
             bias=bias,
+            groups=groups,
         )
         self.run_compare_torch(
             (1, in_channels, height, width),
@@ -1628,6 +1630,7 @@ def test_convolution3d(
             padding=padding,
             dilation=dilation,
             bias=bias,
+            groups=groups,
         )
         self.run_compare_torch(
             (1, in_channels, depth, height, width),
@@ -1687,7 +1690,7 @@ def test_convolution1d(
         class DynamicConv(nn.Module):
             def forward(self, input_data, weights):
                 return nn.functional.conv1d(
-                    input_data, weights, stride=stride, padding=padding
+                    input_data, weights, stride=stride, padding=padding, groups=groups
                 )
 
         model = DynamicConv()
@@ -1754,7 +1757,7 @@ def test_convolution2d(
         class DynamicConv(nn.Module):
             def forward(self, input_data, weights):
                 return nn.functional.conv2d(
-                    input_data, weights, stride=stride, padding=padding
+                    input_data, weights, stride=stride, padding=padding, groups=groups
                 )
 
         model = DynamicConv()
@@ -1890,6 +1893,7 @@ def test_convolution_transpose2d(
             stride=stride,
             padding=padding,
             dilation=dilation,
+            groups=groups,
         )
         self.run_compare_torch(
             (1, in_channels, height, width),
@@ -2016,6 +2020,7 @@ def test_convolution_transpose2d_output_padding(
             padding=padding,
             dilation=dilation,
             output_padding=output_padding,
+            groups=groups,
         )
         self.run_compare_torch(
             (1, in_channels, height, width),
@@ -2099,6 +2104,7 @@ def test_convolution_transpose3d(
         stride,
         padding,
         dilation,
+        groups=1,
     ):
         model = nn.ConvTranspose3d(
             in_channels=in_channels,