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

* Create frexp.md

* minor changes

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Author: AtulDeshpande09

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

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+---
+Title: '.frexp()'
+Description: 'Decomposes input into mantissa and exponent tensors.'
+Subjects:
+  - 'Computer Science'
+  - 'Machine Learning'
+Tags:
+  - 'Functions'
+  - 'Machine Learning'
+  - 'Python'
+  - 'Tensor'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/computer-science'
+---
+
+In PyTorch, the **`.frexp()`** function takes a [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors) as input and returns a tuple storing two tensors: mantissa and exponent. The range of mantissa is the open interval (-1, 1). The original input can be reconstructed as :
+
+$$\text{input} = \text{mantissa}\times 2^{\text{exponent}}$$
+
+## Syntax
+
+```pseudo
+torch.frexp(input, *, out=None) -> (Tensor mantissa, Tensor exponent)
+```
+
+**Parameters:**
+
+- `input`: The input tensor.
+- `out` (Optional): A tuple of two tensors `(mantissa, exponent)` that will store the result. If provided, the output is written in place.
+
+**Return value:**
+
+It returns a tuple containing two tensors - mantissa and exponent.
+
+## Example
+
+This example uses the `.frexp()` function on a tensor. The result contains two tensors mantissa and exponent (which can give numerical stability when floating point numbers are too small or too large):
+
+```py
+import torch
+
+x = torch.tensor([1. , 4. , 5. , 9. ])
+mantissa, exponent = torch.frexp(x)
+
+print(mantissa)
+print(exponent)
+```
+
+The output of this code is:
+
+```shell
+tensor([0.5000, 0.5000, 0.6250, 0.5625])
+tensor([1, 3, 3, 4], dtype=torch.int32)
+```