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The following commit(s) were added to refs/heads/main by this push:
     new e12ddca  [FRONTEND][PYTORCH] Support fo nn.SiLU added (#8753)
e12ddca is described below

commit e12ddcafd74cc10cef343fc39a0c6a892a431650
Author: Alperen Bag <[email protected]>
AuthorDate: Sun Aug 15 07:01:08 2021 +0300

    [FRONTEND][PYTORCH] Support fo nn.SiLU added (#8753)
---
 python/tvm/relay/frontend/pytorch.py          | 5 +++++
 tests/python/frontend/pytorch/test_forward.py | 8 ++++++++
 2 files changed, 13 insertions(+)

diff --git a/python/tvm/relay/frontend/pytorch.py 
b/python/tvm/relay/frontend/pytorch.py
index 9406c3b..7c10889 100644
--- a/python/tvm/relay/frontend/pytorch.py
+++ b/python/tvm/relay/frontend/pytorch.py
@@ -804,6 +804,10 @@ class PyTorchOpConverter:
             alpha * _op.nn.relu(_expr.const(1.0, dtype=dtype) - _op.exp(data)) 
+ _op.nn.relu(data)
         )
 
+    def silu(self, inputs, input_types):
+        data = inputs[0]
+        return data * _op.tensor.sigmoid(data)
+
     def log_sigmoid(self, inputs, input_types):
         data = inputs[0]
         return _op.log(_op.tensor.sigmoid(data))
@@ -2623,6 +2627,7 @@ class PyTorchOpConverter:
             "aten::celu": self.celu,
             "aten::gelu": self.gelu,
             "aten::selu": self.selu,
+            "aten::silu": self.silu,
             "aten::log_sigmoid": self.log_sigmoid,
             "aten::adaptive_avg_pool2d": self.adaptive_avg_pool_2d,
             "aten::adaptive_max_pool2d": self.adaptive_max_pool_2d,
diff --git a/tests/python/frontend/pytorch/test_forward.py 
b/tests/python/frontend/pytorch/test_forward.py
index c924e73..e2cb51a 100644
--- a/tests/python/frontend/pytorch/test_forward.py
+++ b/tests/python/frontend/pytorch/test_forward.py
@@ -701,6 +701,14 @@ def test_forward_selu():
 
 
 @tvm.testing.uses_gpu
+def test_forward_silu():
+    torch.set_grad_enabled(False)
+    input_shape = [1, 3, 10, 10]
+    input_data = torch.rand(input_shape).float()
+    verify_model(torch.nn.SiLU().eval(), input_data=input_data)
+
+
[email protected]_gpu
 def test_forward_softplus():
     torch.set_grad_enabled(False)
     input_shape = [1, 3, 10, 10]

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