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tf.raw_ops.QuantizedReluX

Computes Quantized Rectified Linear X: min(max(features, 0), max_value)

tf.raw_ops.QuantizedReluX(
    features,
    max_value,
    min_features,
    max_features,
    out_type=tf.dtypes.quint8,
    name=None
)
Args
features A Tensor. Must be one of the following types: qint8, quint8, qint32, qint16, quint16.
max_value A Tensor of type float32.
min_features A Tensor of type float32. The float value that the lowest quantized value represents.
max_features A Tensor of type float32. The float value that the highest quantized value represents.
out_type An optional tf.DType from: tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16. Defaults to tf.quint8.
name A name for the operation (optional).
Returns
A tuple of Tensor objects (activations, min_activations, max_activations).
activations A Tensor of type out_type.
min_activations A Tensor of type float32.
max_activations A Tensor of type float32.

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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/raw_ops/QuantizedReluX