We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
selu


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `ivy/functional/frontends/paddle/nn/functional/activation.py`
Content:
```
1 # local
2 from ivy.functional.frontends.paddle.tensor.math import tanh as paddle_tanh
3 from ivy.functional.frontends.paddle.tensor.math import (
4     log_softmax as paddle_log_softmax,
5 )
6 
7 
8 tanh = paddle_tanh
9 log_softmax = paddle_log_softmax
10
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/ivy/functional/frontends/paddle/nn/functional/activation.py b/ivy/functional/frontends/paddle/nn/functional/activation.py
--- a/ivy/functional/frontends/paddle/nn/functional/activation.py
+++ b/ivy/functional/frontends/paddle/nn/functional/activation.py
@@ -1,9 +1,33 @@
 # local
+import ivy
+from ivy.func_wrapper import with_supported_dtypes
+from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back
 from ivy.functional.frontends.paddle.tensor.math import tanh as paddle_tanh
 from ivy.functional.frontends.paddle.tensor.math import (
     log_softmax as paddle_log_softmax,
 )
 
 
+@with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
+@to_ivy_arrays_and_back
+def selu(
+    x,
+    /,
+    *,
+    alpha=1.6732632423543772848170429916717,
+    scale=1.0507009873554804934193349852946,
+    name=None,
+):
+    if scale <= 1.0:
+        raise ValueError(f"The scale must be greater than 1.0. Received: {scale}.")
+
+    if alpha < 0:
+        raise ValueError(f"The alpha must be no less than zero. Received: {alpha}.")
+
+    ret = ivy.where(x > 0, x, alpha * ivy.expm1(x))
+    arr = scale * ret
+    return ivy.astype(arr, x.dtype)
+
+
 tanh = paddle_tanh
 log_softmax = paddle_log_softmax

{"golden_diff": "diff --git a/ivy/functional/frontends/paddle/nn/functional/activation.py b/ivy/functional/frontends/paddle/nn/functional/activation.py\n--- a/ivy/functional/frontends/paddle/nn/functional/activation.py\n+++ b/ivy/functional/frontends/paddle/nn/functional/activation.py\n@@ -1,9 +1,33 @@\n # local\n+import ivy\n+from ivy.func_wrapper import with_supported_dtypes\n+from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back\n from ivy.functional.frontends.paddle.tensor.math import tanh as paddle_tanh\n from ivy.functional.frontends.paddle.tensor.math import (\n     log_softmax as paddle_log_softmax,\n )\n \n \n+@with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\n+@to_ivy_arrays_and_back\n+def selu(\n+    x,\n+    /,\n+    *,\n+    alpha=1.6732632423543772848170429916717,\n+    scale=1.0507009873554804934193349852946,\n+    name=None,\n+):\n+    if scale <= 1.0:\n+        raise ValueError(f\"The scale must be greater than 1.0. Received: {scale}.\")\n+\n+    if alpha < 0:\n+        raise ValueError(f\"The alpha must be no less than zero. Received: {alpha}.\")\n+\n+    ret = ivy.where(x > 0, x, alpha * ivy.expm1(x))\n+    arr = scale * ret\n+    return ivy.astype(arr, x.dtype)\n+\n+\n tanh = paddle_tanh\n log_softmax = paddle_log_softmax\n", "issue": "selu\n\n", "before_files": [{"content": "# local\nfrom ivy.functional.frontends.paddle.tensor.math import tanh as paddle_tanh\nfrom ivy.functional.frontends.paddle.tensor.math import (\n    log_softmax as paddle_log_softmax,\n)\n\n\ntanh = paddle_tanh\nlog_softmax = paddle_log_softmax\n", "path": "ivy/functional/frontends/paddle/nn/functional/activation.py"}], "after_files": [{"content": "# local\nimport ivy\nfrom ivy.func_wrapper import with_supported_dtypes\nfrom ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back\nfrom ivy.functional.frontends.paddle.tensor.math import tanh as paddle_tanh\nfrom ivy.functional.frontends.paddle.tensor.math import (\n    log_softmax as paddle_log_softmax,\n)\n\n\n@with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef selu(\n    x,\n    /,\n    *,\n    alpha=1.6732632423543772848170429916717,\n    scale=1.0507009873554804934193349852946,\n    name=None,\n):\n    if scale <= 1.0:\n        raise ValueError(f\"The scale must be greater than 1.0. Received: {scale}.\")\n\n    if alpha < 0:\n        raise ValueError(f\"The alpha must be no less than zero. Received: {alpha}.\")\n\n    ret = ivy.where(x > 0, x, alpha * ivy.expm1(x))\n    arr = scale * ret\n    return ivy.astype(arr, x.dtype)\n\n\ntanh = paddle_tanh\nlog_softmax = paddle_log_softmax\n", "path": "ivy/functional/frontends/paddle/nn/functional/activation.py"}]}