Create floor term for pytorch

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

@@ -0,0 +1,79 @@
+---
+Title: '.floor()'
+Description: 'Returns a new tensor with each element rounded down to the nearest integer.'
+Subjects:
+  - 'Computer Science'
+  - 'Machine Learning'
+Tags:
+  - 'Neural Networks'
+  - 'PyTorch'
+  - 'Tensor'
+CatalogContent:
+  - 'learn-python'
+  - 'paths/machine-learning'
+---
+
+In PyTorch, the **`.floor()`** function rounds each element of the input [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors) down to the nearest integer, including negative numbers.
+
+## Syntax
+
+```pseudo
+torch.floor(input, *, out=None)
+```
+
+**Parameters:**
+
+- `input`: The input tensor whose elements will be rounded down.
+- `out` (optional): A tensor to store the output. Must have the same shape as input.
+
+**Return value:**
+
+Returns a new tensor with each element rounded down to the nearest integer. If out is provided, the result is written there instead.
+
+## Example 1: Basic Rounding Down with `.floor()`
+
+The following example demonstrates the usage of the `.floor()` function:
+
+```py
+import torch
+
+# Define input
+input = torch.randn(4)
+print(input)
+
+# Round down to the nearest integer
+output = torch.floor(input)
+print(output)
+```
+
+A sample output of this code is:
+
+```shell
+tensor([-0.0032, -0.0333, -0.2857, -1.3986])
+tensor([-1., -1., -1., -2.])
+```
+
+## Example 2: Using the `out` Parameter
+
+This example shows how to use the optional `out` argument to store the results in a pre-allocated tensor:
+
+```py
+import torch
+
+# Define input
+input = torch.tensor([1.7, -0.2, 3.9])
+
+# Pre-allocate an output tensor with the same shape
+result = torch.empty_like(input)
+
+# Compute floor and store result in `result` tensor
+torch.floor(input, out=result)
+
+print(result)
+```
+
+The output of this code is:
+
+```shell
+tensor([ 1., -1.,  3.])
+```