assertion error in data loader while converting to int8

I trained “faster_rcnn_fbnetv3g_fpn” on custom dataset. And model trained successfully. but receiving this error while converting to int8.

code I am using to convert:

import copy
from detectron2.data import build_detection_test_loader
from d2go.export.api import convert_and_export_predictor
from d2go.tests.data_loader_helper import create_fake_detection_data_loader
from d2go.export.d2_meta_arch import patch_d2_meta_arch

import logging

# disable all the warnings
previous_level = logging.root.manager.disable
logging.disable(logging.INFO)

patch_d2_meta_arch()

cfg_name = 'faster_rcnn_fbnetv3g_fpn.yaml'
pytorch_model = model_zoo.get(cfg_name, trained=True)
pytorch_model.cpu()

with create_fake_detection_data_loader(224, 320, is_train=False) as data_loader:
    predictor_path = convert_and_export_predictor(
            model_zoo.get_config(cfg_name),
            copy.deepcopy(pytorch_model),
            "torchscript_int8@tracing",
            './',
            data_loader,
        )

# recover the logging level
logging.disable(previous_level)

The error I am receiving:

WARNING [03/16 06:34:40 mobile_cv.arch.utils.helper]: Arguments ['width_divisor', 'dw_skip_bnrelu', 'zero_last_bn_gamma'] skipped for op Conv2d
loading annotations into memory...
Done (t=0.00s)
creating index...
index created!
/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:477: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
  cpuset_checked))
/usr/local/lib/python3.7/dist-packages/torch/quantization/observer.py:123: UserWarning: Please use quant_min and quant_max to specify the range for observers.                     reduce_range will be deprecated in a future release of PyTorch.
  reduce_range will be deprecated in a future release of PyTorch."
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-19-46e25055929a> in <module>()
     23             "torchscript_int8@tracing",
     24             './',
---> 25             data_loader,
     26         )
     27 

/usr/local/lib/python3.7/dist-packages/d2go/export/api.py in convert_and_export_predictor(cfg, pytorch_model, predictor_type, output_dir, data_loader)
     98             pytorch_model = post_training_quantize(cfg, pytorch_model, data_loader)
     99             # only check bn exists in ptq as qat still has bn inside fused ops
--> 100             assert not fuse_utils.check_bn_exist(pytorch_model)
    101         logger.info(f"Converting quantized model {cfg.QUANTIZATION.BACKEND}...")
    102         if cfg.QUANTIZATION.EAGER_MODE:

AssertionError: 

I have changed the config file and included the newly registered custom dataset. what could be else wrong here?

[DhruvMakwana]

Thanks issue resolved, closing the issue

[Parth38]

https://github.com/pytorch/android-demo-app/issues/164