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Add .i0() term entry for PyTorch Tensor Operations (Issue #7790) (#7845)
* Add .i0() term entry for PyTorch Tensor Operations (Issue #7790) * Improve documentation for the .i0() function Updated the description and syntax for the .i0() function, including parameters and return value. Added examples to illustrate its usage. * using pseudo for syntax * Fixing typo and other minor issues * Removed the codebyte due to compiler error ---------
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---
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Title: '.i0()'
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Description: 'Computes the modified Bessel function of the first kind of order zero.'
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Subjects:
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- 'AI'
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- 'Data Science'
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- 'Machine Learning'
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Tags:
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- 'AI'
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- 'Deep Learning'
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- 'Functions'
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- 'Machine Learning'
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- 'PyTorch'
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CatalogContent:
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- 'intro-to-py-torch-and-neural-networks'
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- 'paths/computer-science'
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---
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In PyTorch, the **`.i0()`** function (an alias of `torch.special.i0()`) computes the modified Bessel function of the first kind of order zero (I₀). This function is commonly used in signal processing, physics simulations, and statistical distributions such as the von Mises distribution for circular data.
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## Syntax
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```pseudo
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torch.i0(input, *, out=None)
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```
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Or, alternatively:
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```pseudo
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torch.special.i0(input, *, out=None)
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```
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**Parameters:**
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- `input` (Tensor): The input tensor whose elements are the values at which to compute the modified Bessel function I₀.
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- `out` (Tensor, optional): The output tensor to store the result.
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**Return value:**
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Returns a tensor containing the computed modified Bessel function of the first kind, order zero (I₀), for each element of the input tensor.
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## Example
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In this example, `torch.i0()` calculates the modified Bessel function I₀ for each element in a 1D tensor:
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```py
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import torch
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# Create input tensor
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x = torch.tensor([0.0, 1.0, 2.0, 3.0, 4.0])
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# Compute the modified Bessel function
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result = torch.i0(x)
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print("Input values:", x)
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print("I₀(x) values:", result)
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```
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The above code produces the following output:
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```shell
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Input values: tensor([0., 1., 2., 3., 4.])
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I₀(x) values: tensor([1.0000, 1.2661, 2.2796, 4.8808, 11.3019])
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```

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