Creation of hsplit entry for pytorch

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

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+---
+Title: '.hsplit()'
+Description: 'Splits a tensor horizontally into multiple sub-tensors.'
+Subjects:
+  - 'AI'
+  - 'Data Science'
+Tags:
+  - 'AI'
+  - 'Arrays'
+  - 'Data Structures'
+  - 'Deep Learning'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/computer-science'
+---
+
+In PyTorch, the **`.hsplit()`** method splits a [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors) into multiple sub-tensors horizontally (column-wise) along the specified dimension (axis).
+
+## Syntax
+
+```pseudo
+torch.hsplit(tensor, indices_or_sections)
+```
+
+- `tensor`: The tensor to be split.
+- `indices_or_sections`: This can be an integer or a list of integers.
+  - If it's an integer, it specifies the number of equal-sized sub-tensors to split the tensor into.
+  - If it's a list of integers, it specifies the sizes of each sub-tensor along the specified dimension.
+
+## Example
+
+The following example demonstrates the usage of the `.hsplit()` method:
+
+```py
+import torch
+
+# Define a tensor
+tensor = torch.tensor([[1, 2, 3, 4],
+                       [5, 6, 7, 8],
+                       [9, 10, 11, 12]])
+
+# Split the tensor into 2 equal parts
+sub_tensors = torch.hsplit(tensor, 2)
+
+print(sub_tensors)
+```
+
+The above code produces the following output:
+
+```shell
+(tensor([[ 1,  2],
+        [ 5,  6],
+        [ 9, 10]]), tensor([[ 3,  4],
+        [ 7,  8],
+        [11, 12]]))
+```
+
+The tensor is split into two sub-tensors along the columns. The first sub-tensor contains the first two columns of the original tensor, while the second sub-tensor contains the last two columns.