/TensorFlow 2.4

# tf.raw_ops.QuantizedMatMulWithBias

Performs a quantized matrix multiplication of `a` by the matrix `b` with bias

The inputs must be two-dimensional matrices and 1D bias vector. And the inner dimension of `a` (after being transposed if `transpose_a` is non-zero) must match the outer dimension of `b` (after being transposed if `transposed_b` is non-zero). Then do broadcast add operation with bias values on the matrix multiplication result. The bias size must match inner dimension of `b`.

Args: a: A `Tensor`. Must be one of the following types: `qint8`, `quint8`, `qint32`, `qint16`, `quint16`. A matrix to be multiplied. Must be a two-dimensional tensor of type `quint8`. b: A `Tensor`. Must be one of the following types: `qint8`, `quint8`, `qint32`, `qint16`, `quint16`. A matrix to be multiplied and must be a two-dimensional tensor of type `qint8`. bias: A `Tensor`. Must be one of the following types: `float32`, `qint32`. A 1D bias tensor with size matching inner dimension of `b` (after being transposed if `transposed_b` is non-zero). min_a: A `Tensor` of type `float32`. The float value that the lowest quantized `a` value represents. max_a: A `Tensor` of type `float32`. The float value that the highest quantized `a` value represents. min_b: A `Tensor` of type `float32`. The float value that the lowest quantized `b` value represents. max_b: A `Tensor` of type `float32`. The float value that the highest quantized `b` value represents. Toutput: An optional `tf.DType` from: `tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16`. Defaults to `tf.qint32`. transpose_a: An optional `bool`. Defaults to `False`. If true, `a` is transposed before multiplication. transpose_b: An optional `bool`. Defaults to `False`. If true, `b` is transposed before multiplication. input_quant_mode: An optional `string` from: `"MIN_FIRST", "SCALED"`. Defaults to `"MIN_FIRST"`. Input data quantization mode. Either MIN_FIRST(default) or SCALED. name: A name for the operation (optional).

Returns: A tuple of `Tensor` objects (out, min_out, max_out).

```out: A `Tensor` of type `Toutput`.
min_out: A `Tensor` of type `float32`.
max_out: A `Tensor` of type `float32`.
```