I am confused about Exercise 2 - alpaca_model

Are we suppose to fill in all the lines of code between “START” and “FINISH”? or just do the 1. 2. 3. mentioned in the instructions in part 3.2? I am not sure how to go about this? Are we supposed to read the Keras documentation and figure it out? Please help.

```
### START CODE HERE
base_model_path="imagenet_base_model/without_top_mobilenet_v2_weights_tf_dim_ordering_tf_kernels_1.0_160_no_top.h5"
base_model ...
# freeze the base model by making it non trainable
base_model.trainable = ...
# create the input layer (Same as the imageNetv2 input size)
inputs = tf.keras.Input(shape=...
# apply data augmentation to the inputs
x = data_augmentation(...
# data preprocessing using the same weights the model was trained on
x = preprocess_input(...
# set training to False to avoid keeping track of statistics in the batch norm layer
x = base_model(...
# add the new Binary classification layers
# use global avg pooling to summarize the info in each channel
x = ...()(x)
# include dropout with probability of 0.2 to avoid overfitting
x = ...(x)
# use a prediction layer with one neuron (as a binary classifier only needs one)
outputs = ...
### END CODE HERE
```