TensorFlow Metadata
TensorFlow Metadata provides standard representations for metadata that are useful when training machine learning models with TensorFlow.
The metadata serialization formats include:
- A schema describing tabular data (e.g., tf.Examples).
- A collection of summary statistics over such datasets.
- A problem statement quantifying the objectives of a model.
The metadata may be produced by hand or automatically during input data analysis, and may be consumed for data validation, exploration, and transformation.
2 maintainers
Release files for tensorflow-metadata 1.21.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| tensorflow_metadata-1.21.0.tar.gz | 24.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tensorflow_metadata-1.21.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 54.8 kB
Release files / tensorflow_metadata-1.21.0.tar.gz
| Download URL | tensorflow_metadata-1.21.0.tar.gz |
|---|---|
| Size | 24.6 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/6.1.0 CPython/3.12.8
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Release files / tensorflow_metadata-1.21.0-py3-none-any.whl
| Download URL | tensorflow_metadata-1.21.0-py3-none-any.whl |
|---|---|
| Size | 30.2 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.8
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