prompt: 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()
  
  ```
  
golden_diff: 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
  
verification_info: {"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"}]}