This release is a pre-release and may not be stable for production use.
TFLite Model Maker
Overview
The TFLite Model Maker library simplifies the process of adapting and converting a TensorFlow neural-network model to particular input data when deploying this model for on-device ML applications.
Requirements
- Refer to requirements.txt for dependent libraries that're needed to use the library and run the demo code.
Installation
There are two ways to install Model Maker.
- Install a prebuilt pip package:
tflite-model-maker.
pip install tflite-model-maker
If you want to install nightly version
tflite-model-maker-nightly,
please follow the command:
pip install tflite-model-maker-nightly
- Clone the source code from GitHub and install.
git clone https://github.com/tensorflow/examples
cd examples/tensorflow_examples/lite/model_maker/pip_package
pip install -e .
End-to-End Example
For instance, it could have an end-to-end image classification example that utilizes this library with just 4 lines of code, each of which representing one step of the overall process. For more detail, you could refer to Colab for image classification.
- Load input data specific to an on-device ML app.
data = ImageClassifierDataLoader.from_folder('flower_photos/')
- Customize the TensorFlow model.
model = image_classifier.create(data)
- Evaluate the model.
loss, accuracy = model.evaluate()
- Export to Tensorflow Lite model and label file in
export_dir.
model.export(export_dir='/tmp/')
Notebook
Currently, we support image classification, text classification and question answer tasks. Meanwhile, we provide demo code for each of them in demo folder.
2 maintainers
Metadata
2 maintainers
Release files for tflite-model-maker-nightly 0.2.6.dev202103290439
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| tflite-model-maker-nightly-0.2.6.dev202103290439.tar.gz | 301.6 kB | Without provenance | Details for tflite-model-maker-nightly-0.2.6.dev202103290439.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| tflite_model_maker_nightly-0.2.6.dev202103290439-py3-none-any.whl | Python 3 | none | any | Details for tflite_model_maker_nightly-0.2.6.dev202103290439-py3-none-any.whl |
Total release size: 814.7 kB
Release files / tflite-model-maker-nightly-0.2.6.dev202103290439.tar.gz
| Download URL | tflite-model-maker-nightly-0.2.6.dev202103290439.tar.gz |
|---|---|
| Size | 301.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
690d37b178f4ecd6955b95454d35c6ef3027c1b9d7e65caae7e1a4d6a7736679
|
|
BLAKE2b-256 checksum How to use checksums |
4dc4722648004d1689bbbbd047aff30fbf1602500cd12aee1fbae07de97f60e3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/3.9.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.7.10
|
Release files / tflite_model_maker_nightly-0.2.6.dev202103290439-py3-none-any.whl
| Download URL | tflite_model_maker_nightly-0.2.6.dev202103290439-py3-none-any.whl |
|---|---|
| Size | 513.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
87c8293a893b880c480dce045783197db1d8d251a054e1d24d6d11abde83bef4
|
|
BLAKE2b-256 checksum How to use checksums |
b9230431320da9cf0d0f51d5e840781ecf9c13f53b08a731b39ba4850030acf6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/3.9.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.7.10
|
Security for tflite-model-maker-nightly 0.2.6.dev202103290439
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.
