code: def max_pool(inputs, window_shape, strides=None, padding="VALID"):
      """Pools the input by taking the maximum of a window slice.
  
      Args:
        inputs: input data with dimensions (batch, window dims..., features).
        window_shape: a shape tuple defining the window to reduce over.
        strides: a sequence of ``n`` integers, representing the inter-window
          strides (default: ``(1, ..., 1)``).
        padding: either the string ``'SAME'``, the string ``'VALID'``, or a sequence
          of ``n`` ``(low, high)`` integer pairs that give the padding to apply before
          and after each spatial dimension (default: ``'VALID'``).
      Returns:
        The maximum for each window slice.
      """
      y = pool(
          inputs, -jnp.inf, lax.max, window_shape, strides, padding
      )
      return y
  
imports: import jax.numpy
  import numpy
  from jax import lax
label_desc: Use image node_id 3 for calling a global function with example usage: max_pool(inputs, window_shape, strides, padding) and returns: y