class_docstr: General N-dimensional downsampling over a sliding window.
class_docstr_tok: ["General","N-dimensional","downsampling","over","a","sliding","window","."]
code: def _check_is_padding_valid(self, padding):
      for (left_padding, right_padding), kernel_size in zip(
          padding, self.kernel_size
      ):
          if max(left_padding, right_padding) > kernel_size:
              raise RuntimeError(
                  "Paddings should be less than the size of the kernel. "
                  f"Padding {(left_padding, right_padding)} received for kernel size "
                  f"{kernel_size}."
              )
  
imports: import math
  from collections.abc import Callable, Sequence
  from typing import Optional, Union
  import jax
  import jax.lax
  import jax.numpy
  import jax.random
  from jaxtyping import Array, PRNGKeyArray
  from .._module import field, Module
  from ._misc import all_sequences
label_desc: Use image node_id 3 for calling the Pool obj's underlying member method code with example usage: obj._check_is_padding_valid(padding) without return types