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A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

Results 228 model-optimization issues
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**System information** - TensorFlow version (you are using): 2.6.0 (TFMOT 0.7.2) - Are you willing to contribute it (Yes/No): Potentially, with some advice on how to implement it **Motivation** Numerous...

feature request

Hello, I have a MobileNetV2 That I am trying to use for image classification by means of transfer learning, although apparently seems to not work. Initially, I perform transfer learning...

System information TensorFlow version (you are using): 2.8 Are you willing to contribute it (Yes/No): Motivation How to extract the original model's weight from the trained QAT model? I want...

feature request

**Describe the bug** When doing the [Sparsity and cluster preserving quantization aware training (PCQAT) Keras example](https://www.tensorflow.org/model_optimization/guide/combine/pcqat_example), if I use a Conv2D Layer with a kernel size of `(1, 1)` the...

bug

**Describe the bug** Saving and subsequently loading a quantized model results in the following error: ``` Traceback (most recent call last): File "test.py", line 37, in model = tf.keras.models.load_model('MinimalExample.h5') File...

bug

**System information** - TensorFlow version (you are using): 2.5.0 - Are you willing to contribute it (Yes/No): Yes **Motivation** Deciding on where to have high filter/channel counts in convnets can...

feature request
technique:pruning

**System information** Ubuntu 18.02 - TensorFlow version (you are using): 2.4.1 - Are you willing to contribute it (Yes/No): Yes This relates to the pruning optimization "block_size: The dimensions (height,...

feature request

**Describe the bug** I'm doing transfer learning and would like to (at the end) quantize my model. The problem is that when I try to use the _quantize_model()_ function (which...

feature request
technique:qat

Updated RELEASE notes with ARM contributions for TFMOT.