concatenate axis not getting changed when switching from NCHW mode to NHWC mode

[yogeesh-alphaics]

Describe the bug
I have a pth file for the SSD model which I wish to convert in Keras format, but I need to change the ordering (NCHW -> NHWC). In the end, there are 2 concat layers whose axis is 2 given the input is coming as x,y,z. Now if we change the ordering from nchw to nhwc , the input shape to concat also changes to [ x,z,y ]. But at this moment the axis of concat layer does not change from 2 to 1 and is resulting in error.

To Reproduce
import torch
import numpy as np
from torchsummary import summary
from torch.autograd import Variable

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
ssd_model = torch.hub.load('NVIDIA/DeepLearningExamples:torchhub', 'nvidia_ssd' , map_location=torch.device('cpu'))
ssd_model.to("cpu")
cl_model.eval()
from pytorch2keras import pytorch_to_keras
input_np = np.random.uniform(0,1,(1,3,300,300))
input_var = Variable(torch.FloatTensor(input_np))
kmodel = pytorch_to_keras(ssd_model , input_var , [(3,300,300)] , change_ordering = True , verbose = True)
kmodel.summary()
kmodel.save("./data/nhwc_model.h5" , save_format = "h5")

Expected behavior
Ideally, if change_ordering is enabled, then concatenate axis should change accordingly. in this case axis should be 1 instead of 2

Logs
ValueError: A Concatenate layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 5776, 4), (None, 2166, 4), (None, 600, 4), (None, 150, 4), (None, 36, 4), (None, 4, 4)]

Environment (please complete the following information):

• ubuntu : 18.04
• Python 3.6.9
• Version onnx : 1.8.1