ABOUT
This is a simple deep learning framework created by ch_wong mail:wchh811@gmail.com self_frame.py
Features
- Define Dynamic Computing Graph
- Define Neural Network Operator
- Define Linear, Sigmoid, L2_loss
- Auto-Diff Computing
- Auto-Feedforward and Backward
1 maintainer
Release files for ch-nn 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ch_nn-1.0.0.tar.gz | 4.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ch_nn-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.6 kB
Release files / ch_nn-1.0.0.tar.gz
| Download URL | ch_nn-1.0.0.tar.gz |
|---|---|
| Size | 4.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-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/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.6.8
|
Release files / ch_nn-1.0.0-py3-none-any.whl
| Download URL | ch_nn-1.0.0-py3-none-any.whl |
|---|---|
| Size | 4.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
79498b9e6cb8aab7910ad4125a0e9bd8c1e193611b6a96d37ca7591530a877b6
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BLAKE2b-256 checksum How to use checksums |
32686d4ee0080b0810d54815c5ad2733aa3b448b57be55e6f9e47cd3b1fcb279
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.6.8
|
