code: def decompose(self, x, known_axes_lengths: dict[str, int]):
      xp = x.__array_namespace__()
      shape = x.shape
  
      flat_shape = []
  
      for i, axis_group in enumerate(self.composed_shape):
          unknown_axis_name = None
          known_sizes_prod = 1
          for axis_name in axis_group:
              if axis_name in known_axes_lengths:
                  known_sizes_prod *= known_axes_lengths[axis_name]
              else:
                  if unknown_axis_name is None:
                      unknown_axis_name = axis_name
                  else:
                      raise EinopsError("Can't infer the size")
  
          if unknown_axis_name is None:
              assert shape[i] == known_sizes_prod
          else:
              known_axes_lengths[unknown_axis_name] = (
                  shape[i] // known_sizes_prod
              )
  
          for axis in axis_group:
              flat_shape.append(known_axes_lengths[axis])
  
      x = xp.reshape(x, flat_shape)
      return xp.permute_dims(x, self.decompose_transposition)
  
file_path: einops/einops/experimental/indexing.py
imports: from typing import List, Union, TypeVar, Tuple
  from einops import EinopsError
label_desc: Use image node_id 2 for calling the CompositionDecomposition obj's underlying member method code with example usage: obj.decompose(x, known_axes_lengths) and returns: xp