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+---
+Title: '.all()'
+Description: 'Returns True if all elements in a tensor evaluate to True.'
+Subjects:
+  - 'AI'
+  - 'Data Science'
+  - 'Machine Learning'
+Tags:
+  - 'AI'
+  - 'Data Structures'
+  - 'Deep Learning'
+  - 'Functions'
+  - 'Machine Learning'
+  - 'PyTorch'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/data-science'
+---
+
+The **`.all()`** function returns `True` if all elements in the input [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors) evaluate to `True`, otherwise it returns `False`. If a dimension is specified, the function performs a logical AND reduction along that dimension.
+
+Non-zero numeric values evaluate as `True`, and zero evaluates as `False`.
+
+## Syntax
+
+```pseudo
+torch.all(input, dim, keepdim=False, *, out=None)
+```
+
+Or alternatively in tensor method form:
+
+```pseudo
+tensor.all(dim=None, keepdim=False)
+```
+
+**Parameters:**
+
+- `input`: The input tensor.
+- `dim` (optional): An `int` or `tuple` of `int` values defining the dimension or dimensions to reduce. If `None`, all dimensions are reduced.
+- `keepdim` (optional): A `bool` value that defines if the output tensor retains the reduced dimension. The default value is `False`.
+- `out` (optional): The output tensor.
+
+**Return value:**
+
+- If `dim` is not specified, returns a zero-dimensional boolean tensor containing `True` or `False`.
+- If `dim` is specified, returns a tensor reduced along the given dimension(s), containing boolean values.
+
+## Example 1: Reducing an Entire Tensor
+
+In this example, `torch.all()` checks whether all elements in a boolean tensor are `True`:
+
+```py
+import torch
+
+tensor = torch.tensor([True, True, False])
+print(torch.all(tensor))
+```
+
+This produces the following output:
+
+```shell
+tensor(False)
+```
+
+## Example 2: Using Numeric Values
+
+In this example, non-zero values evaluate as `True` and zero evaluates as `False`:
+
+```py
+import torch
+
+tensor = torch.tensor([1, 2, 0])
+print(torch.all(tensor))
+```
+
+This produces the following output:
+
+```shell
+tensor(False)
+```
+
+## Codebyte Example: Reducing Along a Dimension
+
+In this example, `torch.all()` checks values along specific dimensions of a 2D tensor:
+
+```py
+import torch
+
+matrix = torch.tensor([[True, True],
+                       [True, False],
+                       [True, True]])
+
+print(torch.all(matrix, dim=1))
+```