nowcasting-dataloader
PyTorch Dataloader for working with multi-modal data for nowcasting applications. In particular, this code loads the pre-prepared batches saved to disk by nowcasting_dataset. This code also computes some optional, additional input features.
Usage
Installation
Run pip install nowcasting-dataloader
Conventions
The dataloader assumes that data is generally in B, C, T, H, W ordering, where B is Batch size, C is number of channels, T is timestep, H is height, and W is width.
Metadata
Release files for nowcasting-dataloader 2.0.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nowcasting_dataloader-2.0.6.tar.gz | 19.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nowcasting_dataloader-2.0.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 45.9 kB
Release files / nowcasting_dataloader-2.0.6.tar.gz
| Download URL | nowcasting_dataloader-2.0.6.tar.gz |
|---|---|
| Size | 19.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
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Release files / nowcasting_dataloader-2.0.6-py3-none-any.whl
| Download URL | nowcasting_dataloader-2.0.6-py3-none-any.whl |
|---|---|
| Size | 26.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
|