An edge inference library on embedded device with EPU designed by iluvatar.ai.
Project description
An edge inference library on embedded device that contains Edge EPU coprocessor. It’s ideal for prototyping new projects that demand fast on-device inferencing for machine learning models. tflex library provides three command line tools: tflexconverter is provided to convert .pb/.h5 model to .tflex model directly supported on EPU, tflexviewer is supplied to display the network architecture(.pb and .tflex file are both supported) more intuitively based on advanced tensorboard, and tflexverify is used to validate whether the model was converted successfully. That is, when a pre-trained or custom model are prepared, then you can use tflexconverter command to convert the model to EPU format, and deploy the model in your device for inference.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
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
File details
Details for the file tflex-1.0.0rc6-py2.py3-none-any.whl.
File metadata
- Download URL: tflex-1.0.0rc6-py2.py3-none-any.whl
- Upload date:
- Size: 53.6 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.14.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/2.7.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
89df2ca8d5008856f144124e0aafdad994870ab953f9426d268109e2867b97c8
|
|
| MD5 |
ad02d19cefce7ab6f6e2998cd807152f
|
|
| BLAKE2b-256 |
1a988924017c785b51d2f4ba1c8625ac332e33c4cf721a680c6cae7bdd204211
|