add support for aten::unflatten

python/tvm/relay/frontend/pytorch.py

@@ -1546,6 +1546,16 @@ def flatten(self, inputs, input_types):
             out = _op.squeeze(out, axis=squeeze_axes)
         return out
 
+    def unflatten(self, inputs, input_types):
+        data = inputs[0]
+        dim = int(inputs[1])
+        unflattened_size = tuple(inputs[2])
+        dshape = get_const_tuple(self.infer_shape_with_prelude(data))
+        assert len(dshape) > dim
+        new_shape = dshape[:dim] + unflattened_size + dshape[dim+1:]
+        out = _op.reshape(data, new_shape)
+        return out
+
     def addmm(self, inputs, input_types):
         input_mat = inputs[0]
         mat1 = inputs[1]
@@ -3945,6 +3955,7 @@ def create_convert_map(self):
             "aten::t": self.transpose,
             "aten::numpy_T": self.numpy_T,
             "aten::flatten": self.flatten,
+            "aten::unflatten": self.unflatten,
             "aten::addmm": self.addmm,
             "aten::size": self.size,
             "aten::view": self.view,

tests/python/frontend/pytorch/test_forward.py

@@ -1544,6 +1544,34 @@ def _test_flatten(start_dim, end_dim):
     verify_model(_test_flatten(-3, -2), inp)
 
 
+#@tvm.testing.uses_gpu
+def test_unflatten():
+    """test_unflatten"""
+
+    def _test_unflatten(dim, unflattened_size):
+        return lambda inp: torch.unflatten(inp, dim, unflattened_size)
+
+    inp = torch.rand(60)
+
+    # [60] -> [3, 5, 2, 2]
+    verify_model(_test_unflatten(0, (3, 5, 2, 2)), inp)
+    verify_model(_test_unflatten(0, (-1, 5, 2, 2)), inp)
+    verify_model(_test_unflatten(0, (3, -1, 2, 2)), inp)
+    verify_model(_test_unflatten(0, (3, 5, -1, 2)), inp)
+    verify_model(_test_unflatten(0, (3, 5, 2, -1)), inp)
+
+    inp = torch.rand(3, 4, 1)
+
+    # [3, 4, 1] -> [3, 2, 2, 1]
+    verify_model(_test_unflatten(1, (2, 2)), inp)
+    verify_model(_test_unflatten(1, (-1, 2)), inp)
+
+    inp = torch.rand(5, 12, 3)
+
+    # [5, 12, 3] -> [5, 2, 2, 3, 1, 1, 3]
+    verify_model(_test_unflatten(-2, (2, 2, 3, 1, 1)), inp)
+
+
 @tvm.testing.uses_gpu
 def test_forward_transpose():
     """test_forward_transpose"""