diff --git a/python/tvm/relay/frontend/pytorch.py b/python/tvm/relay/frontend/pytorch.py
index da81280d76a3..ca24335d4fd0 100644
--- a/python/tvm/relay/frontend/pytorch.py
+++ b/python/tvm/relay/frontend/pytorch.py
@@ -771,7 +771,7 @@ def leaky_relu(self, inputs, input_types):
     def elu(self, inputs, input_types):
         data = inputs[0]
         dtype = input_types[0]
-        alpha = _expr.const(float(inputs[1]), dtype=dtype)
+        alpha = _expr.const(-float(inputs[1]), dtype=dtype)
         return alpha * _op.nn.relu(_expr.const(1, dtype=dtype) - _op.exp(data)) + _op.nn.relu(data)
 
     def celu(self, inputs, input_types):
diff --git a/tests/python/frontend/pytorch/test_forward.py b/tests/python/frontend/pytorch/test_forward.py
index 2e6828f693b6..c924e73a9034 100644
--- a/tests/python/frontend/pytorch/test_forward.py
+++ b/tests/python/frontend/pytorch/test_forward.py
@@ -666,7 +666,7 @@ def test_forward_leakyrelu():
 def test_forward_elu():
     torch.set_grad_enabled(False)
     input_shape = [1, 3, 10, 10]
-    input_data = torch.rand(input_shape).float()
+    input_data = torch.randn(input_shape).float()
     verify_model(torch.nn.ELU().eval(), input_data=input_data)
     verify_model(torch.nn.ELU(alpha=0.3).eval(), input_data=input_data)
     verify_model(torch.nn.ELU(alpha=1.0).eval(), input_data=input_data)