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pstorch
Generate a ready-to-run PyTorch project in seconds.
Install
pip install pstorch
Python
import pstorch
pstorch.generate(
name="pytorch",
input_dim=784,
output_dim=10,
hidden=[256, 128],
metrics=["accuracy", "loss"],
prod=False,
)
Then run the boilerplate:
python main.py
CLI
pstorch generate pytorch --input-dim 784 --output-dim 10 --hidden 256,128 --metrics accuracy,loss
Defaults example:
pstorch generate
Named default example:
pstorch generate pytorch
Output:
src/
__init__.py
config.py
models.py
data.py
train.py
predict.py
main.py
requirements.txt
Metadata
Release files for pstorch 0.1.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pstorch-0.1.6.tar.gz | 6.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pstorch-0.1.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 13.5 kB
Release files / pstorch-0.1.6.tar.gz
| Download URL | pstorch-0.1.6.tar.gz |
|---|---|
| Size | 6.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / pstorch-0.1.6-py3-none-any.whl
| Download URL | pstorch-0.1.6-py3-none-any.whl |
|---|---|
| Size | 7.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
uv/0.7.19
|