# load_torch

### deepinv.utils.load_torch(fname, device=None, \*\*kwargs)

Load torch tensor from file.

* **Parameters:**
  * **fname** ([*str*](https://docs.python.org/3.12/library/stdtypes.html#str) *,* [*pathlib.Path*](https://docs.python.org/3.12/library/pathlib.html#pathlib.Path)) – file to load.
  * **device** ([*torch.device*](https://docs.pytorch.org/docs/stable/tensor_attributes.html#torch.device) *,* [*str*](https://docs.python.org/3.12/library/stdtypes.html#str)) – device to load onto.
* **Returns:**
  [`torch.Tensor`](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor) containing loaded torch tensor.
* **Return type:**
  [*Tensor*](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor)

## Examples using `load_torch`:

<div class="sphx-glr-thumbnails">
<!-- thumbnail-parent-div-open --><div class="sphx-glr-thumbcontainer" tooltip="This example presents the various input/output functions provided by DeepInverse for handling medical and scientific imaging formats. We demonstrate loading and plotting from DICOM, NIfTI, ISMRMRD, PyTorch, NumPy and raster data sources.">![](auto_examples/external-libraries/images/thumb/sphx_glr_demo_io_thumb.png)

[Loading scientific images](https://deepinv.org/auto_examples/external-libraries/demo_io.html.md)

  <div class="sphx-glr-thumbnail-title">Loading scientific images</div>
</div>
<!-- thumbnail-parent-div-close --></div>