QuantizedBiasAdd

tensorflow C++ API

tensorflow::ops::QuantizedBiasAdd

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

Summary

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

Arguments:

• scope: A Scope object
• bias: A 1D bias Tensor with size matching the last dimension of 'input'.
• min_input: The float value that the lowest quantized input value represents.
• max_input: The float value that the highest quantized input value represents.
• min_bias: The float value that the lowest quantized bias value represents.
• max_bias: The float value that the highest quantized bias value represents.

Returns:

• Outputoutput
• Outputmin_out: The float value that the lowest quantized output value represents.
• Outputmax_out: The float value that the highest quantized output value represents.

QuantizedBiasAdd block

Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_nn.cpp

Argument:

• Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
• Input bias: connect Input node.
• Input min_input: connect Input node.
• Input max_input: connect Input node.
• Input min_bias: connect Input node.
• Input max_bias: connect Input node.

Return:

• Output output: Output object of QuantizedBiasAdd class object.
• Output min_output: Output object of QuantizedBiasAdd class object.
• Output max_output: Output object of QuantizedBiasAdd class object.

Result:

• std::vector(Tensor) result_output : Returned object of executed result by calling session.
• std::vector(Tensor) result_min_output : Returned object of executed result by calling session.
• std::vector(Tensor) result_max_output : Returned object of executed result by calling session.

Using Method