If you print your graph in a human-readable form using print(onnx.helper.printable_graph(model.graph)) you’ll probably realize that the blob 325 is a Dropout module of the model. I’m facing the same problem with MobileNetV2 exported from PyTorch to Caffe2 using ONNX. If I omit (remove) the Dropout module when building the model in PyTorch and export it again, there’s no error when executing using predictor.
I don’t know if someone has a solution for this. Meanwhile you can try executing the model with Dropout as follows:
init_def = caffe2_pb2.NetDef()
with open("init_net.pb", "rb") as f:
    init_def.ParseFromString(f.read())
    workspace.RunNetOnce(init_def.SerializeToString())

predict_def = caffe2_pb2.NetDef()
with open("predict_net.pb", "rb") as f:
    predict_def.ParseFromString(f.read())
    workspace.CreateNet(predict_def.SerializeToString())

print ('Running net...')

workspace.FeedBlob('0', inputArray) #Feed the inputArray into the input blob (0) of the network
workspace.RunNetOnce(predict_def)

img_out = workspace.FetchBlob("468") #Fetch the result from the output blob (468) of the network
print(img_out)

Of course, you have to replace the id number of each blob in FeedBlob and FetchBlob, but you can obtain them easily after printing your graph in human-readable form.
I hope it helps. I’m currently still looking for a way to execute it using predictor, because I need to run it in an Android app and FeedBlob doesn’t seem to be usable in there.