class_docstr: Reduce layer behaves identically to einops.reduce operation.
  
  :param pattern: str, rearrangement pattern
  :param reduction: one of available reductions ('min', 'max', 'sum', 'mean', 'prod'), case-sensitive
  :param axes_lengths: any additional specification of dimensions
  
  See einops.reduce for source_examples.
class_docstr_tok: ["Reduce","layer","behaves","identically","to","einops.reduce","operation",".",":","param","pattern",":","str",",","rearrangement","pattern",":","param","reduction",":","one","of","available","reductions","(","'min","'",",","'max","'",",","'sum","'",",","'mean","'",",","'prod","'",")",",","case-sensitive",":","param","axes_lengths",":","any","additional","specification","of","dimensions","See","einops.reduce","for","source_examples","."]
code: def _apply_recipe(self, x):
      backend = get_backend(x)
      return _apply_recipe(
          backend=backend,
          recipe=self._multirecipe[len(x.shape)],
          tensor=x,
          reduction_type=self.reduction,
          axes_lengths=self._axes_lengths,
      )
  
file_path: einops/einops/layers/__init__.py
imports: from typing import Any, Dict
  from ..einops import TransformRecipe, _apply_recipe, _prepare_recipes_for_all_dims, get_backend
  from ..None import EinopsError
label_desc: Use image node_id 4 for calling the ReduceMixin obj's underlying member method code with example usage: obj._apply_recipe(x) and returns: _apply_recipe