feat(nnx): add object-oriented pooling layers and GlobalAveragePool

[starryendymion]

Description

This PR adds native object-oriented pooling layers to flax.nnx.

I am currently migrating from Keras to Flax NNX and noticed that while functional pooling exists in linen, NNX was missing the modular, object-oriented equivalents (e.g., nnx.AvgPool, nnx.MaxPool). Currently, users have to import functional pooling from linen or wrap them manually, which breaks the object-oriented flow of NNX.

Additionally, I noticed that GlobalAveragePool was missing entirely, so I have implemented it as a standard NNX module to simplify workflows for those coming from other frameworks like Keras or PyTorch.

Changes Made

• Added flax/nnx/nn/pooling.py: Implemented MaxPool, MinPool, AvgPool, and GlobalAveragePool as nnx.Module subclasses.
• Updated flax/nnx/__init__.py: Exposed the new layers in the top-level nnx namespace.
• Documentation: Added pooling.rst to the API reference and updated the index.

Usage Example

Before (Linen Functional Pooling)

from flax import linen as nn

# Max Pool
x = nn.max_pool(x, window_shape=(2, 2), strides=(2, 2))

# Average Pool
x = nn.avg_pool(x, window_shape=(3, 3), strides=(2, 2), padding="SAME")

# Global Average Pool (manual)
x = x.mean(axis=(1, 2))

After (NNX Object-Oriented Pooling)

from flax import nnx

# Max Pool
x = nnx.MaxPool(window_shape=(2, 2), strides=(2, 2))(x)

# Average Pool
x = nnx.AvgPool(window_shape=(3, 3), strides=(2, 2), padding="SAME")(x)

# Global Average Pool
x = nnx.GlobalAveragePool()(x)

**Closes #5202 **