Web DL Compiler - Lightweight deep learning compiler utilities
Project description
What will we need to do?
Implement the major layers in pytorch:
- Linear
- Conv2D
- FC
- ReLU
- Pool
- RNN
- LSTM
- Batch Norm ... etc
-
Support
nn.Sequential -
Support hugging face models
-
Support saved model.
-
Optimization Phase:
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
wdlc-0.6.0.tar.gz
(15.9 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
wdlc-0.6.0-py3-none-any.whl
(16.6 kB
view details)
File details
Details for the file wdlc-0.6.0.tar.gz.
File metadata
- Download URL: wdlc-0.6.0.tar.gz
- Upload date:
- Size: 15.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fe92bd65475e9c8baaa90b279d3dffb0cb4b8031de1e71ab93a11c123bf2c478
|
|
| MD5 |
46a25f58dd0821628f4ff71af373de05
|
|
| BLAKE2b-256 |
1389435622d963e301ae47b643577b6bc43c81f94e0aa1abfb2a34f93cea2bb4
|
File details
Details for the file wdlc-0.6.0-py3-none-any.whl.
File metadata
- Download URL: wdlc-0.6.0-py3-none-any.whl
- Upload date:
- Size: 16.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e70462fdc403aa64ea86973adbe4319119f6b7e0b397b8abcc17d2aaac88e32d
|
|
| MD5 |
9eca0aec92d572ec76175eb38be503fa
|
|
| BLAKE2b-256 |
a080280282ffc0fd33859e831f1f926daafd42376c6542056d327555dda9bd81
|