code: def _deconv_output_length(
      input_size, filter_size, padding, output_padding, stride, dilation
  ):
      """Determines output length of a transposed convolution given input length.
  
      Args:
        input_size: `int`.
        filter_size: `int`.
        padding: one of `"SAME"`, `"VALID"`, `"FULL"`.
        output_padding: `int`, amount of padding along the output dimension. Can
          be set to `None` in which case the output length is inferred.
        stride: `int`.
        dilation: `int`.
  
      Returns:
        output_length: The output length (`int`).
      """
      assert padding in {"SAME", "VALID", "FULL"}
      if input_size is None:
          return None
      # Get the dilated kernel size
      filter_size = filter_size + (filter_size - 1) * (dilation - 1)
      # Infer length if output padding is None, else compute the exact length
      if output_padding is None:
          if padding == "VALID":
              return input_size * stride + ps.maximum(
                  filter_size - stride, 0
              )
          elif padding == "FULL":
              return input_size * stride - (stride + filter_size - 2)
          elif padding == "SAME":
              return input_size * stride
      if padding == "SAME":
          pad = filter_size // 2
      elif padding == "VALID":
          pad = 0
      elif padding == "FULL":
          pad = filter_size - 1
      return (
          (input_size - 1) * stride
          + filter_size
          - 2 * pad
          + output_padding
      )
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.nn.util import utils
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
label_desc: Use image node_id 13 for calling a global function with example usage: _deconv_output_length(input_size, filter_size, padding, output_padding, stride, dilation) and returns: unknown, None, unknown, unknown, unknown