tf.raw_ops.QuantizedBiasAdd

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

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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.