Neural Network Tuning Analysis Toolkit
Analyse neural networks for feature tuning.
Installation
$ pip install nn_analysis
Depending on your use you might need to install several other packages.
The AlexNet network requires you to install PyTorch and PyTorch vision using:
$ pip install torch torchvision
PredNet requires a more specific configuration. For PredNet you need to be using python version 3.6 and TensorFlow version < 2.
Features
- Fitting tuning functions to recorded activations of a neural network,
- Automatic storage of large tables on disk in understandable folder structures,
- Easily extendable to other neural networks and stimuli.
The above features are explained in more detail in nn_analyis' documentation.
2 maintainers
Release files for nn-tuning 1.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nn_tuning-1.0.2.tar.gz | 41.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nn_tuning-1.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 94.8 kB
Release files / nn_tuning-1.0.2.tar.gz
| Download URL | nn_tuning-1.0.2.tar.gz |
|---|---|
| Size | 41.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
36b75335a54233d1d063bcaaa639303292d31d3af5a852194f1ca5a92231743d
|
|
BLAKE2b-256 checksum How to use checksums |
62879b900a91b8ba49a25572f306dac7de02d2eb3f67f85b330903bd2e6c902d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6
|
Release files / nn_tuning-1.0.2-py3-none-any.whl
| Download URL | nn_tuning-1.0.2-py3-none-any.whl |
|---|---|
| Size | 53.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b4cf290cae2a368f694e69316ae5c03f74032229b929f018fa9d29628014075a
|
|
BLAKE2b-256 checksum How to use checksums |
2ab8fe84cd2d0fa920cf50836de8a88dee603420ede21970304f080d9e0b0753
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6
|
