Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"
I am trying to use the trained model in my TPU, so I need to quantize the model (using TF1).
I think I must add the line contrib_quantize.create_training_graph(input_graph=self._sess.graph, quant_delay=0) inside the __init__ function of the file BiseNetV2CityScapesTrainer.py. However it is a bit unclear to me exactly where .
Hi,
I am trying to use the trained model in my TPU, so I need to quantize the model (using TF1).
I think I must add the line
contrib_quantize.create_training_graph(input_graph=self._sess.graph, quant_delay=0)
inside the__init__
function of the fileBiseNetV2CityScapesTrainer.py
. However it is a bit unclear to me exactly where .Would you have any recommendation? Thanks