[Term Entry] PyTorch Tensor Operations: .asinh()

content/pytorch/concepts/tensor-operations/terms/asinh/asinh.md

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+---
+Title: '.asinh()'
+Description: 'Returns the inverse hyperbolic sine of each element in an input tensor.'
+Subjects:
+  - 'AI'
+  - 'Computer Science'
+  - 'Data Science'
+  - 'Data Visualization'
+  - 'Machine Learning'
+Tags:
+  - 'AI'
+  - 'Machine Learning'
+  - 'PyTorch'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/data-science'
+---
+
+The PyTorch method **`.asinh()`** returns the inverse hyperbolic sine of each element in a given [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors). It is useful for mathematical and scientific computations involving hyperbolic functions.
+
+## Syntax
+
+```psuedo
+torch.asinh(input, *, out=None) → Tensor
+```
+
+### Parameters
+
+- `input`: A tensor containing real or complex values of any dimension.
+- `out` (Optional): The output tensor to store the result. If not specified, a new tensor is returned.
+
+### Returns
+
+A new tensor containing the inverse hyperbolic sine of each element in the input tensor.
+
+## Example
+
+The following example demonstrates how to use `.asinh()` to compute the inverse hyperbolic sine for the real-valued 1D tensor:
+
+```py
+import torch
+
+input_tensor = torch.tensor([0.125, 0.25, 0.5, 0.75])
+
+output_tensor = torch.asinh(input_tensor)
+
+print("Input Tensor:")
+print(input_tensor)
+
+print("\nOutput Tensor:")
+print(output_tensor)
+```
+
+This example outputs:
+
+```shell
+Input Tensor:
+tensor([0.1250, 0.2500, 0.5000, 0.7500])
+
+Output Tensor:
+tensor([0.1253, 0.2526, 0.5211, 0.8223])
+```
+
+The values in `output_tensor` represents the inverse hyperbolic sine of the corresponding values in `input_tensor`.