I'm implementing YOLO network and have some questions. In the original paper the authors say: "For pretraining we use the first 20 convolutional layers from Figure 3 followed by a average-pooling layer and a fully connected layer". And also they report that they use ImageNet 1000 classes dataset and 224x224 input size instead of 448x448

My questions are the following:

1. What is the size of average-pooling layer kernel? 2x2?

2. How do authors reduce the input size to 224x224? Do they omit the 1st layer?