tf.raw_ops.UniformQuantizedDot

Perform quantized dot of quantized Tensor lhs and quantized Tensor rhs to make quantized output.

tf.raw_ops.UniformQuantizedDot(
    lhs,
    rhs,
    lhs_scales,
    lhs_zero_points,
    rhs_scales,
    rhs_zero_points,
    output_scales,
    output_zero_points,
    Tout,
    lhs_quantization_min_val,
    lhs_quantization_max_val,
    rhs_quantization_min_val,
    rhs_quantization_max_val,
    output_quantization_min_val,
    output_quantization_max_val,
    lhs_quantization_axis=-1,
    rhs_quantization_axis=-1,
    output_quantization_axis=-1,
    name=None
)

Given quantized lhs and quantized rhs, performs quantized dot on lhs and rhs to make quantized output. lhs and rhs must be 2D Tensors and the lhs.dim_size(1) must match rhs.dim_size(0). lhs and rhs must be quantized Tensor, where data value is quantized using the formula: quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). output is also quantized, using the same formula. If rhs is per-tensor quantized, output must be also per-tensor quantized.

lhs A Tensor. Must be one of the following types: qint8. Must be a 2D Tensor of Tin.
rhs A Tensor. Must have the same type as lhs. Must be a 2D Tensor of Tin.
lhs_scales A Tensor of type float32. The float value(s) used as scale when quantizing original data that lhs represents. Must be a scalar Tensor (lhs supports only per-tensor quantization).
lhs_zero_points A Tensor of type int32. The int32 value(s) used as zero_point when quantizing original data that lhs represents. Same shape condition as lhs_scales.
rhs_scales A Tensor of type float32. The float value(s) used as scale when quantizing original data that rhs represents. Must be a scalar Tensor (per-tensor quantization) or 1D Tensor of size (rhs.dim_size(1),) (per-channel quantization).
rhs_zero_points A Tensor of type int32. The int32 value(s) used as zero_point when quantizing original data that rhs represents. Same shape condition as rhs_scales.
output_scales A Tensor of type float32. The float value(s) to use as scales when quantizing original data that output represents. Must be a scalar Tensor (per-tensor quantization) or 1D Tensor of size (output.dim_size(1),) (per-channel quantization). If rhs is per-tensor quantized, output must be also per-tensor quantized. This means that if rhs_scales and rhs_zero_points are scalar Tensors, output_scales and output_zero_points must be scalar Tensors as well.
output_zero_points A Tensor of type int32. The int32 value(s) used as zero_point when quantizing original data that output represents. Same shape condition as rhs_scales.
Tout A tf.DType from: tf.qint32. The type of output Tensor.
lhs_quantization_min_val An int. The min value of the quantized data stored in lhs. For example, if Tin is qint8, this must be set to -127 if narrow range quantized or -128 if not.
lhs_quantization_max_val An int. The max value of the quantized data stored in rhs. For example, if Tin is qint8, this must be set to 127.
rhs_quantization_min_val An int. The min value of the quantized data stored in rhs. For example, if Trhs is qint8, this must be set to -127 if narrow range quantized or -128 if not.
rhs_quantization_max_val An int. The max value of the quantized data stored in rhs. For example, if Trhs is qint8, this must be set to 127.
output_quantization_min_val An int. The min value of the quantized data stored in output. For example, if Tout is qint8, this must be set to -127 if narrow range quantized or -128 if not.
output_quantization_max_val An int. The max value of the quantized data stored in output. For example, if Tout is qint8, this must be set to 127.
lhs_quantization_axis An optional int. Defaults to -1. Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For dot op lhs, only per-tensor quantization is supported. Thus, this attribute must be set to -1. Other values are rejected.
rhs_quantization_axis An optional int. Defaults to -1. Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For dot op rhs, only per-tensor quantization or per-channel quantization along dimension 1 is supported. Thus, this attribute must be set to -1 or 1. Other values are rejected.
output_quantization_axis An optional int. Defaults to -1. Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. If set to -1 (default), this indicates per-tensor quantization. For dot op output, only per-tensor quantization or per-channel quantization along dimension 1 is supported. Thus, this attribute must be set to -1 or 1. Other values are rejected.
name A name for the operation (optional).

A Tensor of type Tout.