code: def _determine_depth_max_pooling(
      x, kernel, strides, dims, data_format="channel_last"
  ):
      # determine depth pooling
      _, _, depth_pooling = _depth_max_pooling_helper(
          x.shape, kernel, strides, dims=dims, data_format=data_format
      )
      if depth_pooling:
          kernel = [1, 1, 1, kernel[-1]]
          strides = [1, 1, 1, strides[-1]]
      return x, kernel, strides, depth_pooling
  
imports: from typing import Optional, Union, Tuple, List, Literal, Sequence, Callable
  import jax
  import jax.lax
  import jax.numpy
  import math
  import ivy
  from ivy import output_to_native_arrays
  from ivy.functional.backends.jax import JaxArray
  from ivy.functional.backends.jax.random import RNG
  from ivy.functional.ivy.experimental.general import _correct_ivy_callable
  from ivy.functional.ivy.layers import _handle_padding, _validate_max_pool_params, _depth_max_pooling_helper
  from ivy.functional.ivy.experimental.layers import _padding_ceil_mode, _get_size
  from ivy.func_wrapper import with_supported_dtypes
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
  from ivy.functional.backends.jax.experimental.manipulation import _to_nested_tuple
label_desc: Use image node_id 1 for calling a global function with example usage: _determine_depth_max_pooling(x, kernel, strides, dims, data_format) and returns: x,  kernel,  strides,  depth_pooling