alicera edited a comment on issue #19808: URL: https://github.com/apache/incubator-mxnet/issues/19808#issuecomment-770659754
By the way, I based on NGC "nvcr.io/nvidia/mxnet:20.12-py3" to do git clone --recursive https://github.com/apache/incubator-mxnet mxnet cd mxnet git checkout v1.x cp -r ./python/mxnet/contrib/onnx/mx2onnx/ /opt/mxnet/python/mxnet/contrib/onnx/ then I run the script. here is the script > from gluoncv import model_zoo import numpy as np import mxnet as mx model_name = 'resnest101' resnet50 = model_zoo.get_model(model_name, pretrained=True) print(model_name+' downloaded') resnet50.hybridize() print(model_name+' hybridized') input_shape=(1,3,224,224) data_array = np.random.uniform(0, 255, size=input_shape).astype("float32") mx_data = mx.nd.array(data_array) resnet50(mx_data) resnet50.export(model_name) print(model_name+' exported') #convert using onnx from mxnet.contrib import onnx as onnx_mxnet onnx_file='./tp.onnx' params = './'+model_name+'-0000.params' #sym = mx.sym.load('./resnetfifty-symbol.json') sym='./'+model_name+'-symbol.json' onnx_mxnet.export_model(sym, params, [input_shape], np.float32, onnx_file) print('onnx export done') > ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
