Thank you very much @supriyar,
I am still eager to find a solution. I’ve tried your assumptions, installed fresh build and tried again. Re-run QAT on model (just to make sure) and exporting process.
Now it says that MaxPool cannot be created.
Traceback (most recent call last):
  File "./tools/caffe2_converter.py", line 114, in <module>
    caffe2_model = export_caffe2_model(cfg, model, first_batch)
  File "/root/some_detectron2/detectron2/export/api.py", line 157, in export_caffe2_model
    return Caffe2Tracer(cfg, model, inputs).export_caffe2()
  File "/root/some_detectron2/detectron2/export/api.py", line 95, in export_caffe2
    predict_net, init_net = export_caffe2_detection_model(model, inputs)
  File "/root/some_detectron2/detectron2/export/caffe2_export.py", line 151, in export_caffe2_detection_model
    onnx_model = export_onnx_model(model, (tensor_inputs,))
  File "/root/some_detectron2/detectron2/export/caffe2_export.py", line 53, in export_onnx_model
    traced = torch.jit.trace(model, inputs, strict=False)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/jit/__init__.py", line 900, in trace
    check_tolerance, strict, _force_outplace, _module_class)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/jit/__init__.py", line 1054, in trace_module
    module._c._create_method_from_trace(method_name, func, example_inputs, var_lookup_fn, strict, _force_outplace)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/nn/modules/module.py", line 575, in __call__
    result = self._slow_forward(*input, **kwargs)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/nn/modules/module.py", line 561, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/contextlib.py", line 74, in inner
    return func(*args, **kwds)
  File "/root/some_detectron2/detectron2/export/caffe2_modeling.py", line 319, in forward
    features = self._wrapped_model.backbone(images.tensor)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/nn/modules/module.py", line 575, in __call__
    result = self._slow_forward(*input, **kwargs)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/nn/modules/module.py", line 561, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "/root/DensePose_ADASE/densepose/modeling/quantize.py", line 205, in new_forward
    return {"p2": p2_out, "p3": p3_out, "p4": p4_out, "p5": p5_out, "p6": self.top_block(p5_out)[0]}
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/nn/modules/module.py", line 575, in __call__
    result = self._slow_forward(*input, **kwargs)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/nn/modules/module.py", line 561, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "/root/some_detectron2/detectron2/modeling/backbone/fpn.py", line 177, in forward
    return [F.max_pool2d(x, kernel_size=1, stride=2, padding=0)]
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/_jit_internal.py", line 210, in fn
    return if_false(*args, **kwargs)
  File "/root/anaconda2/envs/pytorch-gpu/lib/python3.7/site-packages/torch/nn/functional.py", line 576, in _max_pool2d
    input, kernel_size, stride, padding, dilation, ceil_mode)
RuntimeError: createStatus == pytorch_qnnp_status_success INTERNAL ASSERT FAILED at "/opt/conda/conda-bld/pytorch_1590649859799/work/aten/src/ATen/native/quantized/cpu/qpool.cpp":313, please report a bug to PyTorch. failed to create QNNPACK MaxPool operator


Path to the source
Looks weird, why didn’t it happen earlier?
UPD: It looks like nested F.max_pool2d won’t quantize. Test showed that it works with float32 after convert