code: def valid_padding(
      in_size: Tuple[int, int],
      filter_size: Union[int, Tuple[int, int]],
      stride_size: Union[int, Tuple[int, int]],
  ) -> Tuple[int, int]:
      """Emulates TF Conv2DLayer "valid" padding (no padding) and computes output dims.
  
      This method, analogous to its "same" counterpart, but it only computes the output
      image size, since valid padding means (0, 0, 0, 0).
  
      See www.tensorflow.org/versions/r0.12/api_docs/python/nn/convolution
  
      Args:
          in_size: Rows (Height), Column (Width) for input
          stride_size (Union[int,Tuple[int, int]]): Rows (Height), column (Width)
              for stride. If int, height == width.
          filter_size: Rows (Height), column (Width) for filter
  
      Returns:
          The output shape after padding and convolution.
      """
      in_height, in_width = in_size
      if isinstance(filter_size, int):
          filter_height, filter_width = filter_size, filter_size
      else:
          filter_height, filter_width = filter_size
      if isinstance(stride_size, (int, float)):
          stride_height, stride_width = int(stride_size), int(
              stride_size
          )
      else:
          stride_height, stride_width = int(stride_size[0]), int(
              stride_size[1]
          )
  
      out_height = int(
          np.ceil(
              (in_height - filter_height + 1) / float(stride_height)
          )
      )
      out_width = int(
          np.ceil((in_width - filter_width + 1) / float(stride_width))
      )
  
      return (out_height, out_width)
  
imports: import numpy
  from typing import Union, Tuple, Any, List
  from ray.rllib.models.utils import get_activation_fn
  from ray.rllib.utils.annotations import DeveloperAPI
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.typing import TensorType
label_desc: Use image node_id 4 for calling a global function with example usage: valid_padding(in_size, filter_size, stride_size) and returns: out_height,  out_width