Convolution layers: Add support for `same` padding.

[till-m]

First of all, thanks for the package! It's amazing that something like this exists.

While trying to convert a model I noticed that using same padding breaks the conversion of convolution layers. Given that same is supported as an argument by both the torch and the tf version of convolution layers, I would assume that this should be a relatively easy fix.

import torch
import torch.nn as nn
import nobuco
from nobuco import ChannelOrder

dummy_image = torch.rand(size=(1, 3, 2048))

for padding in [0, 'same']:
    pytorch_module = nn.Conv1d(3, 10, 15, padding=padding)

    keras_model = nobuco.pytorch_to_keras(
        pytorch_module,
        args=[dummy_image], kwargs=None,
        inputs_channel_order=ChannelOrder.TENSORFLOW,
        outputs_channel_order=ChannelOrder.TENSORFLOW
    )

[AlexanderLutsenko]

Hi! Sure, here you go. Same padding supported starting with v0.11.6.

[till-m]

thanks!