mediapipe_model_maker.object_detector.QATHParams
Stay organized with collections
Save and categorize content based on your preferences.
The hyperparameters for running quantization aware training (QAT) on object detectors.
mediapipe_model_maker.object_detector.QATHParams(
learning_rate: float = 0.3,
batch_size: int = 8,
epochs: int = 15,
decay_steps: int = 8,
decay_rate: float = 0.96
)
For more information on QAT, see:
https://www.tensorflow.org/model_optimization/guide/quantization/training
Attributes |
learning_rate
|
Learning rate to use for gradient descent QAT.
|
batch_size
|
Batch size for QAT.
|
epochs
|
Number of training iterations over the dataset.
|
decay_steps
|
Learning rate decay steps for Exponential Decay. See
https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/schedules/ExponentialDecay
for more information.
|
decay_rate
|
Learning rate decay rate for Exponential Decay. See
https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/schedules/ExponentialDecay
for more information.
|
Methods
__eq__
__eq__(
other
)
Class Variables |
|
batch_size
|
8
|
|
decay_rate
|
0.96
|
|
decay_steps
|
8
|
|
epochs
|
15
|
|
learning_rate
|
0.3
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2026-05-28 UTC.
[null,null,["Last updated 2026-05-28 UTC."],[],[]]