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 into multiple chunks.'
+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 into multiple sub-tensors horizontally (column-wise) along a specified axis.
+
+## Syntax
+
+```pseudo
+torch.hsplit(tensor, split_size_or_sections, dim=0)
+```
+
+- `tensor`: The tensor to be split.
+- `split_size_or_sections`: The number of sub-tensors to be created or the size of each sub-tensor.
+- `dim` (Optional): The axis along which to split the tensor. The default value is `0`.
+
+## 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
+sub_tensors = torch.hsplit(tensor, 2)
+
+print(sub_tensors)
+```[tensor([[1, 2, 3],
+            [5, 6, 7]]), 
+
+    tensor([[4], [8], [12]])]
+
+The above code produces the following output:
+
+[tensor([[1, 2, 3],
+         [5, 6, 7]]),
+
+tensor([[4], [8], [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.