From 1b5fc9be472ce02d1ac360f15b55f26b4070fade Mon Sep 17 00:00:00 2001
From: Pragati Verma <itispragativerma@gmail.com>
Date: Mon, 16 Dec 2024 11:21:53 +0530
Subject: [PATCH] [Term Entry] PyTorch Tensors .eye() (#5786)

* Add pytorch eye entry

* Review Fixes

* Update eye.md

minor fixes

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+---
+Title: '.eye()'
+Description: 'Returns a 2D tensor with ones on the diagonal and zeros elsewhere, creating an identity matrix.'
+Subjects:
+  - 'AI'
+  - 'Data Science'
+  - 'Machine Learning'
+Tags:
+  - 'AI'
+  - 'Deep Learning'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/computer-science'
+---
+
+The **`.eye()`** function in PyTorch is used to create a 2D tensor representing an identity matrix. An identity matrix is a square matrix in which all elements of the principal diagonal are ones, and all other elements are zeros.
+
+This function is commonly used in linear algebra operations and initializing neural network weights.
+
+## Syntax
+
+```pseudo
+torch.eye(n, m=None, *, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False)
+```
+
+- `n`: Specifies the number of rows in the resulting 2-D tensor.
+- `m` (Optional): Specifies the number of columns in the resulting tensor. Defaults to `None`, in which case the result is a square matrix with `m = n`.
+- `out` (Optional): A tensor to store the output. If specified, the result is written into this tensor. Defaults to `None`.
+- `dtype` (Optional): Specifies the desired data type of the resulting tensor. Defaults to the global PyTorch settings if not provided.
+- `layout` (Optional): Defines the desired memory layout of the tensor. Defaults to `torch.strided`.
+- `device` (Optional): The desired device on which to create the tensor. If not specified, the tensor will be created on the current device.
+- `requires_grad` (Optional): If `True`, the resulting tensor will be created with gradient computation enabled. Defaults to `False`.
+
+## Example
+
+Here is an example that demonstrates the use of `.eye()` to create a _3x3_ identity matrix:
+
+```py
+import torch
+
+# Create a 3x3 identity matrix
+identity_matrix = torch.eye(3)
+
+print(identity_matrix)
+```
+
+The output of the above code will be as follows:
+
+```shell
+tensor([[1., 0., 0.],
+        [0., 1., 0.],
+        [0., 0., 1.]])
+```
+
+## Codebyte Example
+
+Here is an example that demonstrates the use of `.eye()` to create a _4x4_ identity matrix:
+
+```codebyte/python
+import torch
+
+# Create a 4x4 identity matrix
+identity_matrix = torch.eye(4)
+
+print(identity_matrix)
+```