Convert tf to pytorch model

translate_architecture.py

# >>> tf1 implementation (without encapsulating class)
import tensorflow as tf

def upconvcat(self, x1, x2, n_filter, name):
    x1 = tf.keras.layers.UpSampling2D((2, 2))(x1)
    x1 = tf.layers.conv2d(x1, filters=n_filter, kernel_size=(3, 3), padding='same', name="upsample_{}".format(name))
    return tf.concat([x1, x2], axis=-1, name="concat_{}".format(name))  # NHWC format

# >>> pytorch implementation
import torch

class UpConvCat(nn.Module):
    def __init__(self, in_channels, out_channels):
        super().__init__()
        self.up = torch.nn.Upsample(scale_factor=2)
        self.conv = torch.nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1)

    def forward(self, x1, x2):
        x1 = self.up(x1)
        return torch.cat([x1, x2], dim=1)  # NCHW format