Add conv2d e2e test from convnext model

Author: AmosLewis

projects/pt1/python/torch_mlir_e2e_test/test_suite/conv.py

@@ -255,6 +255,36 @@ def forward(self, inputVec, weight):
 def Convolution2DStaticModule_basic(module, tu: TestUtils):
     module.forward(tu.rand(3, 3, 10, 10), tu.rand(3, 3, 2, 2))
 
+class Convolution2DNextStaticModule(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args(
+        [
+            None,
+            ([1,80,72,72], torch.float32, True),
+            ([80,1,7,7], torch.float32, True),
+            ([80], torch.float32, True),
+        ]
+    )
+    def forward(self, inputVec, weight, bias):
+        return torch.ops.aten.convolution(
+            inputVec,
+            weight,
+            bias=bias,
+            stride=[1, 1],
+            padding=[3, 3],
+            dilation=[1, 1],
+            transposed=False,
+            output_padding=[0, 0],
+            groups=80,
+        )
+
+
+@register_test_case(module_factory=lambda: Convolution2DNextStaticModule())
+def Convolution2DNextStaticModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand(1,80,72,72), tu.rand(80,1,7,7), tu.rand(80))
 
 class Convolution2DStridedModule(torch.nn.Module):
     def __init__(self):