class_docstr: ONNX data reader to be used for extracting relevant information during conversion.
class_docstr_tok: ["ONNX","data","reader","to","be","used","for","extracting","relevant","information","during","conversion","."]
code: def __init__(self, model):
      self.model = model
      self.input_map = {}
      self.index_map = {
          # Dense
          "kernel": 1,
          "bias": 2,
          # BatchNormalization
          "gamma": 1,
          "beta": 2,
          "moving_mean": 3,
          "moving_variance": 4,
      }
  
imports: import numpy
  import onnx
  from onnx import helper, numpy_helper, shape_inference
  from hls4ml.model import ModelGraph
label_desc: Use image node_id 1 to create a new ONNXDataReader object  with example: obj = ONNXDataReader(model)