tf.raw_ops.QuantizedBiasAdd

Adds Tensor 'bias' to Tensor 'input' for Quantized types.

Compat aliases for migration

tf.compat.v1.raw_ops.QuantizedBiasAdd

tf.raw_ops.QuantizedBiasAdd(
    input, bias, min_input, max_input, min_bias, max_bias, out_type, name=None
)

Broadcasts the values of bias on dimensions 0..N-2 of 'input'.

Args
`input`	A `Tensor`. Must be one of the following types: `qint8`, `quint8`, `qint32`, `qint16`, `quint16`.
`bias`	A `Tensor`. Must be one of the following types: `qint8`, `quint8`, `qint32`, `qint16`, `quint16`. A 1D bias Tensor with size matching the last dimension of 'input'.
`min_input`	A `Tensor` of type `float32`. The float value that the lowest quantized input value represents.
`max_input`	A `Tensor` of type `float32`. The float value that the highest quantized input value represents.
`min_bias`	A `Tensor` of type `float32`. The float value that the lowest quantized bias value represents.
`max_bias`	A `Tensor` of type `float32`. The float value that the highest quantized bias value represents.
`out_type`	A `tf.DType` from: `tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16`.
`name`	A name for the operation (optional).

Returns
A tuple of `Tensor` objects (output, min_out, max_out).
`output`	A `Tensor` of type `out_type`.
`min_out`	A `Tensor` of type `float32`.
`max_out`	A `Tensor` of type `float32`.

Args