ONNX to Keras Conversion Failed - Unable to Use same Padding

[ghost]

import onnx
import torch
from onnx2keras import onnx_to_keras

# Load ONNX model
model = onnx.load('output/pytorch_onnx.onnx')

# Call the converter (input - is the main model input name, can be different for your model)
k_model = onnx_to_keras(model, ['input'])

Output -

W0827 20:22:03.981888 140701784454976 pooling_layers.py:33] Unable to use `same` padding. Add ZeroPadding2D layer to fix shapes.

W0827 20:22:03.985505 140701784454976 deprecation_wrapper.py:119] From /home/pat-011/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:3661: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.

W0827 20:22:04.031678 140701784454976 pooling_layers.py:33] Unable to use `same` padding. Add ZeroPadding2D layer to fix shapes.

Model definition -

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(1, 20, 5, 1)
        self.conv2 = nn.Conv2d(20, 50, 5, 1)
        self.fc1 = nn.Linear(4*4*50, 500)
        self.fc2 = nn.Linear(500, 10)

    def forward(self, x):
        x = F.relu(self.conv1(x))
        x = F.max_pool2d(x, 2, 2)
        x = F.relu(self.conv2(x))
        x = F.max_pool2d(x, 2, 2)
        x = x.view(-1, 4*4*50)
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return F.softmax(x, dim=1)
    model = Net().to(device)

[gmalivenko]

Hello. The output contains warnings, not errors.

I can convert your model and I don't see any error: My code sample for your model

[ghost]

Thanks for the help