[Term Entry] PyTorch Tensor Operations: .sin()

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

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+---
+Title: '.sin()'
+Description: 'Computes the sine of each element in a PyTorch tensor.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+  - 'Machine Learning'
+Tags:
+  - 'Integers'
+  - 'Python'
+  - 'Tensor'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/computer-science'
+---
+
+The **`.sin()`** function in PyTorch computes the sine of each element in the input [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors). The operation is applied element-wise, using radians as the unit for angle values.
+
+## Syntax
+
+```pseudo
+torch.sin(input, *, out=None) → Tensor
+```
+
+**Parameters:**
+
+- `input`: A tensor containing angle values in radians.
+- `out` (optional): A tensor to store the output. If provided, the result is written into this tensor.
+
+**Return value:**
+
+Returns a new tensor where each element is the sine of the corresponding value in the input tensor.
+
+## Example 1: Sine of Individual Values
+
+This example computes the sine of common angle values (in radians):
+
+```py
+import torch
+import math
+
+x = torch.tensor([0.0, math.pi / 2, math.pi])
+
+result = torch.sin(x)
+
+print("Input:", x)
+print("sin(x):", result)
+```
+
+The output of this code is:
+
+```shell
+Input: tensor([0.0000, 1.5708, 3.1416])
+sin(x): tensor([ 0.0000e+00,  1.0000e+00, -8.7423e-08])
+```
+
+## Example 2: Element-wise Operation on a 2D Tensor
+
+This example applies the sine function to every element of a 2D tensor:
+
+```py
+import torch
+
+angles = torch.tensor([[0.0, 0.5],
+                        [1.0, 1.5]])
+
+result = torch.sin(angles)
+
+print("Input tensor:")
+print(angles)
+print("\nSine of tensor:")
+print(result)
+```
+
+The output of this code is:
+
+```shell
+Input tensor:
+tensor([[0.0000, 0.5000],
+        [1.0000, 1.5000]])
+
+Sine of tensor:
+tensor([[0.0000, 0.4794],
+        [0.8415, 0.9975]])
+```
+
+The `.sin()` function preserves the shape of the input tensor and applies the sine operation independently to each value.