issue with calibration data set, I have selected randomly 1024 training samples from imagenet dataset. Now I can I see some good results.
Size (MB): 102.491395
{"metric": "original_resnet50_val_accuracy", "value": 90.234375}
Size (MB): 102.143772
{"metric": "fused_resnet50_val_accuracy", "value": 90.234375}
calibration
{"metric": "quntize_per_tensor_resent50_val_accuracy", "value": 78.22265625}
after quantization
{"metric": "quntize_per_tensor_resent50_val_accuracy", "value": 88.28125}
calibration
{"metric": "quntize_per_tensor_resent50_val_accuracy", "value": 76.26953125}
after quantization
{"metric": "quntize_per_channel_resent50_val_accuracy", "value": 89.84375}
size of quantization per tensor model
Size (MB): 25.653446
size of quantization per channel model
Size (MB): 25.957137