Distributed framework to accelerate training and support serving.
Project description
OpenEmbedding is a distributed framework to accelerate TensorFlow training and support TensorFlow Serving. It uses the parameter server architecture to store the Embedding Layer. So that single machine memory is not the limit of model size. OpenEmbedding can cooperate with all-reduce framework to support both data parallel and model parallel.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
openembedding-0.1.2.tar.gz
(21.8 MB
view details)
File details
Details for the file openembedding-0.1.2.tar.gz.
File metadata
- Download URL: openembedding-0.1.2.tar.gz
- Upload date:
- Size: 21.8 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.5.0 importlib_metadata/4.8.2 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
15aae49db02e65db99857ab62ebeeb34d8874bbc4982aee1f07c2fbcd222c1b0
|
|
| MD5 |
c9eb151b04d1a0aa14d666eba01f02c9
|
|
| BLAKE2b-256 |
c7c633dd9305228b99e66b8a28be6952cd0b0ae7cc2fb295fd66fecbf0181af9
|
