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+---
+Title: '.bitwise_not()'
+Description: 'Performs element-wise bitwise NOT operation on the input tensor, flipping each bit (0 becomes 1 and 1 becomes 0). Applicable to integer and boolean tensors.'
+Subjects:
+  - 'AI'
+  - 'Data Science'
+Tags:
+  - 'AI'
+  - 'Data Types'
+  - 'Deep Learning'
+  - 'Functions'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/data-science'
+---
+
+In PyTorch, the **`.bitwise_not()`** function performs an element-wise bitwise NOT operation on the input [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors). This flips each bit of the tensor’s binary representation, turning `0` to `1` and `1` to `0`. It works for integer tensors (signed or unsigned) and boolean tensors (where it acts as a logical NOT).
+
+## Syntax
+
+```pseudo
+torch.bitwise_not(input, *, out=None)
+```
+
+**Parameters:**
+
+- `input`: A tensor of integer or boolean dtype.
+- `out` (Optional): A tensor to store the output result. Must have the same shape as the input tensor.
+
+**Return value:**
+
+The `.bitwise_not()` function returns a new tensor containing the result of applying the bitwise NOT operation to each element in the input tensor.
+
+## Example
+
+The following example illustrates the usage of the `.bitwise_not()` function in PyTorch:
+
+```py
+import torch
+
+# Create a boolean tensor
+tensor_in = torch.tensor([True, False, True])
+
+# Apply bitwise NOT
+result = torch.bitwise_not(tensor_in)
+
+print(result)
+```
+
+The above code produces the following output:
+
+```shell
+tensor([False,  True, False])
+```