TrainingExtensions/tensorflow/src/python/aimet_tensorflow/keras/quant_sim/qc_quantize_layer.py
def call(self, inputs):
        """
        Forward-pass routine. This quantizes the weights before delegating to the wrapped module and then quantizes the
        output before returning the same
        :param inputs: Inputs passed to the module in the forward pass
        :return: Quantized output from the wrapped module
        """
        outputs = self._quantize_activation(inputs)
        return outputs

        Forward-pass routine. This quantizes the weights before delegating to the wrapped module and then quantizes the
        output before returning the same
        :param inputs: Inputs passed to the module in the forward pass
        :return: Quantized output from the wrapped module
        
Forward-pass routine. This quantizes the weights before delegating to the wrapped module and then quantizes the
output before returning the same
Forward - pass routine . This quantizes the weights before delegating to the wrapped module and then quantizes the output before returning the same
def call(self, inputs):
        outputs = self._quantize_activation(inputs)
        return outputs
def call ( self , inputs ) : outputs = self . _quantize_activation ( inputs ) return outputs
Forward-pass routine.
Forward - pass routine .
"""
        Forward-pass routine. This quantizes the weights before delegating to the wrapped module and then quantizes the
        output before returning the same
        :param inputs: Inputs passed to the module in the forward pass
        :return: Quantized output from the wrapped module
        """
Quantized output from the wrapped module
Quantized output from the wrapped module
self
inputs
Inputs passed to the module in the forward pass
Inputs passed to the module in the forward pass