This release is a pre-release and may not be stable for production use.
This library powers Amazon SageMaker Debugger, and helps you develop better, faster and cheaper models by catching common errors quickly. It allows you to save tensors from training jobs and makes these tensors available for analysis, all through a flexible and powerful API. It supports TensorFlow, PyTorch, MXNet, and XGBoost on Python 3.6+.
- Zero Script Change experience on SageMaker when using supported versions of SageMaker Framework containers or AWS Deep Learning containers
- Full visibility into any tensor which is part of the training process
- Real-time training job monitoring through Rules
- Automated anomaly detection and state assertions
- Interactive exploration of saved tensors
- Distributed training support
- TensorBoard support
1 maintainer
Metadata
1 maintainer
Release files for smdebug 1.0.11b20210622
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| smdebug-1.0.11b20210622-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details for smdebug-1.0.11b20210622-py2.py3-none-any.whl |
Release files / smdebug-1.0.11b20210622-py2.py3-none-any.whl
| Download URL | smdebug-1.0.11b20210622-py2.py3-none-any.whl |
|---|---|
| Size | 270.7 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
4d76e71e1dbd8ff45a3d13a24163f6977ed921ea74e316e66d056678f16dbe57
|
|
BLAKE2b-256 checksum How to use checksums |
3f8c897a9e4501dd26e0ae034ab6f602e974ab987fb63bf90eb2bc26b1e4ccd5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.6.6
|
Security for smdebug 1.0.11b20210622
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
