PoolformerImageProcessor defaults to match previous FE
# What does this PR do?

Output of PoolformerImageProcessor didn't exactly match previous feature extractor. Updates defaults and size calculation logic to match outputs. 

Running:
```
import torch
from transformers import PoolFormerFeatureExtractor, PoolFormerModel
from datasets import load_dataset
dataset = load_dataset("huggingface/cats-image")
image = dataset["test"]["image"][0]

feature_extractor = PoolFormerFeatureExtractor.from_pretrained("sail/poolformer_s12")
model = PoolFormerModel.from_pretrained("sail/poolformer_s12")

inputs = feature_extractor(image, return_tensors="pt")

with torch.no_grad():
    outputs = model(**inputs)

last_hidden_states = outputs.last_hidden_state
r = list(last_hidden_states.shape)
print(r)
```

Now outputs images of size `[1, 512, 7, 7]` - matching the output of the images before #19796 was merged in. 


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- [ ] Did you write any new necessary tests?

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