class_docstr: Base class for combinations.
docstr: Calculate the output shape for the given input shapes.
  
  .. note ::
      this method runs a single forward pass if no symbolic computation is available.
  
  :param input_shapes:
      the input shapes without the batch dimensions
  
  :return:
      the output shape
docstr_tok: ["Calculate","the","output","shape","for","the","given","input","shapes",".","..","note",":",":","this","method","runs","a","single","forward","pass","if","no","symbolic","computation","is","available",".",":","param","input_shapes",":","the","input","shapes","without","the","batch","dimensions",":","return",":","the","output","shape"]
code: def output_shape(
      self, input_shapes: Sequence[Tuple[int, ...]]
  ) -> Tuple[int, ...]:
      """
      Calculate the output shape for the given input shapes.
  
      .. note ::
          this method runs a single forward pass if no symbolic computation is available.
  
      :param input_shapes:
          the input shapes without the batch dimensions
  
      :return:
          the output shape
      """
      logger.warning("No symbolic computation of output shape.")
      return self(
          xs=[torch.empty(size=shape) for shape in input_shapes]
      ).shape
  
imports: import logging
  from abc import ABC, abstractmethod
  from typing import Any, Callable, Iterable, Mapping, Optional, Sequence, Tuple
  import torch
  from class_resolver import ClassResolver, Hint, HintOrType, OptionalKwargs
  from class_resolver.contrib.torch import activation_resolver, aggregation_resolver
  from torch import nn
  from ..utils import ExtraReprMixin, combine_complex, split_complex
label_desc: Use image node_id 2 for calling the Combination obj's underlying member method code with example usage: obj.output_shape(input_shapes) and returns: self