Error Generating model from ONNX

[kanndil]

Given this Onnx file and the following code:

https://drive.google.com/file/d/1h9qmRRbryAZydOmIKnp0HpXJ2PbzyNDB/view?usp=sharing

from __future__ import absolute_import
from __future__ import print_function
import os
import sys
import numpy as np
import nngen as ng

# the next line can be removed after installation
sys.path.insert(0, os.path.dirname(os.path.dirname(
    os.path.dirname(os.path.abspath(__file__)))))

def run(act_dtype=ng.int8, weight_dtype=ng.int8,
        bias_dtype=ng.int32, scale_dtype=ng.int8,
        with_batchnorm=True, disable_fusion=False,
        conv2d_par_ich=1, conv2d_par_och=1, conv2d_par_col=1, conv2d_par_row=1,
        conv2d_concur_och=None, conv2d_stationary='filter',
        pool_par=1, elem_par=1,
        chunk_size=64, axi_datawidth=32, silent=False,
        onnx_filename='model_final-2.onnx',
        weight_filename='vgg11_imagenet.npz',
        verilog_filename=None,
        sim_filename=None,
        simtype=None,  # no RTL simulation
        # simtype='iverilog',
        # simtype='verilator'
        ):

    # input mean and standard deviation
    imagenet_mean = np.array([0.485, 0.456, 0.406]).astype(np.float32)
    imagenet_std = np.array([0.229, 0.224, 0.225]).astype(np.float32)

    act_shape = (1, 62, 12, 1)

    # ONNX to NNgen
    dtypes = {}
    (outputs, placeholders, variables,
     constants, operators) = ng.from_onnx(onnx_filename,
                                          value_dtypes=dtypes,
                                          default_placeholder_dtype=act_dtype,
                                          default_variable_dtype=weight_dtype,
                                          default_constant_dtype=weight_dtype,
                                          default_operator_dtype=act_dtype,
                                          default_scale_dtype=scale_dtype,
                                          default_bias_dtype=bias_dtype,
                                          disable_fusion=disable_fusion)

    # --------------------
    # (2) Assign quantized weights to the NNgen operators
    # --------------------

    if act_dtype.width > 8:
        act_scale_factor = 128
    else:
        act_scale_factor = int(round(2 ** (act_dtype.width - 1) * 0.5))

    input_scale_factors = {'act': act_scale_factor}
    input_means = {'act': imagenet_mean * act_scale_factor}
    input_stds = {'act': imagenet_std * act_scale_factor}

    ng.quantize(outputs, input_scale_factors, input_means, input_stds)


if __name__ == '__main__':
    rslt = run(silent=False, verilog_filename='tmp.v')
    print(rslt)

I get the following error

Youssefs-MacBook-Pro-9:nngen youssef$ python3 kws_onnx_nngen.py 
Traceback (most recent call last):
  File "/Users/youssef/Documents/Work/AUC_Open_Hardware_Lab/nngen/kws_onnx_nngen.py", line 392, in <module>
    rslt = run(silent=False, verilog_filename='tmp.v')
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/youssef/Documents/Work/AUC_Open_Hardware_Lab/nngen/kws_onnx_nngen.py", line 72, in run
    constants, operators) = ng.from_onnx(onnx_filename,
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/youssef/Documents/Work/AUC_Open_Hardware_Lab/nngen/nngen/onnx/__init__.py", line 329, in from_onnx
    visitor.visit(name)
  File "/Users/youssef/Documents/Work/AUC_Open_Hardware_Lab/nngen/nngen/onnx/__init__.py", line 147, in visit
    node_op = node_func(self, node)
              ^^^^^^^^^^^^^^^^^^^^^
  File "/Users/youssef/Documents/Work/AUC_Open_Hardware_Lab/nngen/nngen/onnx/gemm.py", line 63, in Gemm
    reshape_value = filter.value.reshape(shape)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^

Here is the architecture of the used model.