[Term Entry] PyTorch function: tensor_split()

[mwmartella]

Description

• Added tensor-split term for PyTorch
• Closes [Term Entry] PyTorch Tensor Operations: .tensor_split() #5927

Type of Change

• Adding a new entry

Checklist

• [x ] All writings are my own.
• [ x] My entry follows the Codecademy Docs style guide.
• [ x] My changes generate no new warnings.
• [x ] I have performed a self-review of my own writing and code.
• [ x] I have checked my entry and corrected any misspellings.
• [ x] I have made corresponding changes to the documentation if needed.
• [x ] I have confirmed my changes are not being pushed from my forked main branch.
• [ x] I have confirmed that I'm pushing from a new branch named after the changes I'm making.
• [x ] I have linked any issues that are relevant to this PR in the Issues Solved section.

[CLAassistant]

All committers have signed the CLA.

[SaviDahegaonkar]

Hey @mwmartella,
The entry is well-written! I’ve suggested a few changes—please make them as soon as possible. Also, please note that being on the main branch is discouraged. Please create a new separate branch for this entry. Thanks for contributing to the Codecademy docs! :) Feel free to reach out if you have any questions.

Thanks,
Savi

[SaviDahegaonkar]

Suggested change

	Description: 'Takes a input for a tensor and splits it into multiple tensors.'
	Description: 'Takes an input tensor and splits it into multiple sub-tensors.'

Made the sentence grammatically correct.

[SaviDahegaonkar]

Suggested change

	Subjects:
	- 'Data Science'
	Subjects:
	- 'AI'
	- 'Data Science'
	- 'Machine Learning'

Added some more subjects that are supported by tensor-split term in tensor-operations.

[SaviDahegaonkar]

Suggested change

	- 'Data Structures'
	- 'Data Structures'
	- 'Deep Learning'
	- 'PyTorch'
	- 'Tensor'

Added some more tags for better understanding and relevance.

[SaviDahegaonkar]

Suggested change

	In PyTorch, the **`.tensor_split()`** function splits a tensor into multiple sub-tensors. PyTorch will attempt to split the tensor evenly but when the tensor cannot be split evenly it will create as close to even sub-tensors as possible. The sub tensors can be also shaped with a dim (dimension) input.
	In PyTorch, the **`.tensor_split()`** function splits a tensor into multiple sub-tensors. If the tensor cannot be split evenly, PyTorch distributes the elements as evenly as possible. The shape of the sub-tensors can also be controlled using the `dim` (dimension) parameter.

Reframed the sentence for more consistency and grammatical correctness.

[SaviDahegaonkar]

Suggested change

Please remove this extra blank line over here.

[SaviDahegaonkar]

Suggested change

	- `indices_or_sections(int)`: How many sub tensors to split into
	- `indices_or_sections(int)`: Number of sub-tensors to split the input tensor into, or the indices at which to split along the specified dimension.

This sentence seems grammatically incorrect or incomplete. So rephrase it for more clarity.

[SaviDahegaonkar]

Suggested change

	- `dim(int, optional)`: Change the dimensions of the split tensors, Default=0
	- `dim(int, optional)`: The dimension along which to split the tensor. Default is `0`.

[SaviDahegaonkar]

Suggested change

	The following example demonstrates the usage of the `.tensor_split()` function:
	The following example demonstrates the use of the `.tensor_split()` function:

[SaviDahegaonkar]

Suggested change

	#the above code produces the tensor in 2 equal parts. 10 goes into 2 5 times so each subtensor has 5 elements
	#the above code produces the tensor in 2 equal parts. 10 goes into 2 5 times so each subtensor has 5 elements

Instead of this comment: "#the above code produces the tensor in 2 equal parts. 10 goes into 2 5 times so each sub-tensor has 5 elements," you can use the following sentence before the shell block: "The following code splits the tensor into 2 equal sub-tensors. Since 10 can be evenly divided by 2, each sub-tensor will contain 5 elements:"

[SaviDahegaonkar]

Suggested change

	```py
	import torch
	x = torch.arange(13) #create a one dimensional tensor
	torch.tensor_split(x, 6) #split the tensor into 6 parts
	```
	```shell
	#the above code produces the tensor in 6 almost equal parts. 13 is not divisable by 6 so PyTorch does this as close to even as possible the first sub tensor having 3 elements and the rest only 2.
	(tensor([0, 1, 2]), tensor([3, 4]), tensor([5, 6]), tensor([7, 8]), tensor([ 9, 10]), tensor([11, 12]))
	```
	```py
	import torch
	x = torch.arange(13) #create a one dimensional tensor
	torch.tensor_split(x, 6) #split the tensor into 6 parts

#the above code produces the tensor in 6 almost equal parts. 13 is not divisable by 6 so PyTorch does this as close to even as possible the first sub tensor having 3 elements and the rest only 2.
(tensor([0, 1, 2]), tensor([3, 4]), tensor([5, 6]), tensor([7, 8]), tensor([ 9, 10]), tensor([11, 12]))

This section can be removed since an example has already been added earlier in this entry.