diff --git a/content/pytorch/concepts/tensor-operations/terms/row-stack/row-stack.md b/content/pytorch/concepts/tensor-operations/terms/row-stack/row-stack.md new file mode 100644 index 00000000000..4fef9022b7d --- /dev/null +++ b/content/pytorch/concepts/tensor-operations/terms/row-stack/row-stack.md @@ -0,0 +1,51 @@ +--- +Title: '.row_stack()' +Description: 'Stacks or arranges a sequence of tensors vertically (row-wise).' +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 **`.row_stack()`** function stacks or arranges a sequence of [tensors](https://www.codecademy.com/resources/docs/pytorch/tensors) vertically (row-wise). It is an alias or alternative for the **`.vstack()`** function. + +## Syntax + +```pseudo +torch.row_stack(tensors, *, out=None) +``` + +- `tensors`: The sequence of tensors to be stacked vertically. +- `out` (Optional): A tensor to store the output. It must have the correct shape to accommodate the result. + +## Example + +The following example demonstrates the usage of the `.row_stack()` function: + +```py +import torch + +# Create two tensors +ten1 = torch.tensor([12, 23, 34]) +ten2 = torch.tensor([45, 56, 67]) + +# Stack the tensors vertically +res = torch.row_stack((ten1, ten2)) + +# Print the resultant tensor +print(res) +``` + +The above code produces the following output: + +```shell +tensor([[12, 23, 34], + [45, 56, 67]]) +```