# tf.compat.v1.nn.quantized_relu_x

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

    tf.compat.v1.nn.quantized_relu_x(
        features: _atypes.TensorFuzzingAnnotation[TV_QuantizedReluX_Tinput],
        max_value: _atypes.TensorFuzzingAnnotation[_atypes.Float32],
        min_features: _atypes.TensorFuzzingAnnotation[_atypes.Float32],
        max_features: _atypes.TensorFuzzingAnnotation[_atypes.Float32],
        out_type: TV_QuantizedReluX_out_type = https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/dtypes#quint8,
        name=None
    )

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| ## 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`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf/dtypes/DType) from: `tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16`. Defaults to [`tf.quint8`](https://www.tensorflow.org/versions/r2.14/api_docs/python/tf#quint8). |
| `name` | A name for the operation (optional). |

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| ## 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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