[GitHub] [incubator-mxnet] LewsTherin511 edited a comment on issue #14875: MXNet to ONNX export bug

[GitBox <gi...@apache.org>]

LewsTherin511 edited a comment on issue #14875:
URL: https://github.com/apache/incubator-mxnet/issues/14875#issuecomment-778132510


   I'm encountering the same issue.
   I fine-tuned an SSD model on a custom dataset (everything working properly), and I'm trying to export it to ONNX in order to run it on Android.
   This is what I'm doing I adapted PR #14942 to my case:
   
   `
   from os import path as osp
   import numpy as np
   import mxnet as mx
   import gluoncv as gcv
   from mxnet.contrib import onnx as onnx_mxnet
   from mxnet import gluon
   from gluoncv import model_zoo, data, utils
   
   ctx = mx.cpu(0)
   
   OUTPUT = 'oxnn/'
   DATA = "./friends.png"
   # SIZE = 320
   MODEL = "CML_exported"
   INPUT_SHAPE = ((1,3,512,683))
   
   CML_classes = ["CML_mug"]
   net = gcv.model_zoo.get_model('ssd_512_mobilenet1.0_custom', classes=CML_classes, pretrained_base=False, ctx=ctx)
   net.load_parameters("saved_weights/CML_mobilenet_mug_00/ep_035.params", ctx=ctx)
   net.hybridize()
   # pass an img to trigger init after hybridize
   x, _ = data.transforms.presets.yolo.load_test(DATA, short=512)
   _ = net(x)
   
   net.export(osp.join(OUTPUT, MODEL))
   sym = osp.join(OUTPUT, MODEL + "-symbol.json")
   params = osp.join(OUTPUT, MODEL + "-0000.params")
   onnx_file = osp.join(OUTPUT, MODEL + ".onnx")
   
   converted_model_path = onnx_mxnet.export_model(sym, params, [INPUT_SHAPE], np.float32, onnx_file, verbose=True)`
   
   I'm getting the usual:
   
   `File ".../anaconda3/envs/gluon/lib/python3.7/site-packages/mxnet/contrib/onnx/mx2onnx/export_onnx.py", line 92, in convert_layer
       return convert_func(node, **kwargs)
     File "/home/lews/anaconda3/envs/gluon/lib/python3.7/site-packages/mxnet/contrib/onnx/mx2onnx/_op_translations.py", line 1502, in convert_slice_axis
       ends = int(attrs.get("end", None))
   ValueError: invalid literal for int() with base 10: 'None'`
   
   Any updates since last year? Was this somehow fixed?


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