text: # BSD 3-Clause License
  #
  # Copyright (c) 2021 BBC
  # All rights reserved.
  #
  # Redistribution and use in source and binary forms, with or without
  # modification, are permitted provided that the following conditions are met:
  #
  #  1. Redistributions of source code must retain the above copyright notice,
  #  this list of conditions and the following disclaimer.
  #
  #  2. Redistributions in binary form must reproduce the above copyright notice,
  #  this list of conditions and the following disclaimer in the documentation
  #  and/or other materials provided with the distribution.
  #
  #  3. Neither the name of the copyright holder nor the names of its contributors may
  #  be used to endorse or promote products derived from this software without
  #  specific prior written permission.
  #
  # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
  # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
  # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS
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  # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
  # THE POSSIBILITY OF SUCH DAMAGE.
  
  experiment_path = "../experiments/"  # Path to where the YUV files and log files are stored
  encoder_cfg = "ra_main10"            # VVC encoding configuration (for train: ld_P_main10, ra_main10; for test: test)
  orig_bitdepth = 8                    # Bit depth of the original YUV sequence
  deco_bitdepth = 10                   # Bit depth of the decoded YUV sequence
  qp_list = [27]                       # List of Quantization Parameters (QPs) for which the sequence was coded
  
  sequence = "blowingbubbles"          # Name of the video sequence
  size = (416, 240)                    # (width, height) of the YUV sequence
  
  max_block_exp = 8                    # Maximum rectangular block size exponent (e.g. 6 = max block size of 32x32)
  kernel_size = 13                     # Combined size of convolutional kernels (e.g. 9x9, 1x1, 5x5 = 13x13)
  
  dataset_path = "../dataset/"         # Directory where the dataset will be saved
  