code: def _pooling_general(
      inputs,
      reducer,
      init_val,
      rescaler=None,
      pool_size=(2, 2),
      strides=None,
      padding="VALID",
  ):
      """Helper: general pooling computation used in pooling layers later."""
      spatial_strides = strides or (1,) * len(pool_size)
      rescale = (
          rescaler(pool_size, spatial_strides, padding)
          if rescaler
          else None
      )
      dims = (1,) + pool_size + (1,)  # NHWC
      strides = (1,) + spatial_strides + (1,)
      out = lax.reduce_window(
          inputs, init_val, reducer, dims, strides, padding
      )
      return rescale(out, inputs) if rescale else out
  
imports: import functools
  import jax
  from jax import lax
  from jax import random
  import jax.numpy
  import jax.scipy.special
  import numpy
  import tensorflow
  import tensorflow_datasets
  from trax.fastmath import numpy
  from trax.shapes import signature
label_desc: Use image node_id 2 for calling a global function with example usage: _pooling_general(inputs, reducer, init_val, rescaler, pool_size, strides, padding) and returns: unknown