Update narrow-copy.md

Author: arisdelacruz

content/pytorch/concepts/tensor-operations/terms/narrow-copy/narrow-copy.md

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+---
+Title: '.narrow_copy()'
+Description: 'Creates a new tensor with a narrowed subsection of data from an input tensor.'
+Subjects:
+  - 'Computer Science'
+  - 'Machine Learning'
+Tags:
+    - 'Python'
+    - 'Machine Learning'
+    - 'Methods'
+    - 'Functions'
+CatalogContent:
+    - 'intro-to-py-torch-and-neural-networks'
+    - 'paths/computer-science'
+---
+
+In Pytorch, **`.narrow_copy()`** is a function that creates a new tensor with the same data as the input tensor but with a narrowed dimension. The function is similar to the **`.narrow()`** function, but it returns a new tensor instead of a view of the original tensor.
+
+## Syntax
+
+```pseudo
+torch.narrow_copy(input, dim, start, length)
+```
+
+- `input`: The input tensor to be narrowed.
+- `dim`: The dimension along which the input tensor is to be narrowed.
+- `start`: The index where the narrowing begins. This can be a positive integer, a negative integer (to index from the end of `dim`), or a 0-dimensional integer tensor.
+- `length`: The number of elements to include from the starting position.
+
+## Example
+
+The following example demonstrates the usage of the **`.narrow_copy()`** function:
+
+```py
+import torch
+
+# Create a 2D tensor
+tensor_2d = torch.arange(1, 13).reshape(3, 4)
+print(f"Original 2D Tensor:\n{tensor_2d}")
+
+# Narrow the tensor along rows and create a new tensor
+narrowed_tensor = torch.narrow_copy(tensor_2d, 0, 1, 2)
+print(f"Narrowed 2D Tensor:\n{narrowed_tensor}")
+```
+
+The above code produces the following output:
+
+```shell
+Original 2D Tensor:
+tensor([[ 1,  2,  3,  4],
+        [ 5,  6,  7,  8],
+        [ 9, 10, 11, 12]])
+
+Narrowed 2D Tensor:
+tensor([[ 5,  6,  7,  8],
+        [ 9, 10, 11, 12]])
+```
+
+In this example, the **`.narrow_copy()`** function is used to narrow the input tensor along the rows (dimension 0) starting from index 1 and including 2 rows. The resulting tensor is a new tensor with the narrowed data.
+
+The **`.narrow_copy()`** function is useful when you need to create a new tensor with a subset of data from an existing tensor without modifying the original tensor.