scripts/tf_cnn_benchmarks/models/tf1_only/nasnet_model.py [306:329]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  normal_cell = nasnet_utils.NasNetANormalCell(
      hparams.num_conv_filters, hparams.drop_path_keep_prob, total_num_cells,
      hparams.total_training_steps)
  reduction_cell = nasnet_utils.NasNetAReductionCell(
      hparams.num_conv_filters, hparams.drop_path_keep_prob, total_num_cells,
      hparams.total_training_steps)
  with arg_scope(
      [slim.dropout, nasnet_utils.drop_path, slim.batch_norm],
      is_training=is_training):
    with arg_scope(
        [
            slim.avg_pool2d, slim.max_pool2d, slim.conv2d, slim.batch_norm,
            slim.separable_conv2d, nasnet_utils.factorized_reduction,
            nasnet_utils.global_avg_pool, nasnet_utils.get_channel_index,
            nasnet_utils.get_channel_dim
        ],
        data_format=hparams.data_format):
      return _build_nasnet_base(
          images,
          normal_cell=normal_cell,
          reduction_cell=reduction_cell,
          num_classes=num_classes,
          hparams=hparams,
          is_training=is_training,
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



scripts/tf_cnn_benchmarks/models/tf1_only/nasnet_model.py [356:379]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  normal_cell = nasnet_utils.NasNetANormalCell(
      hparams.num_conv_filters, hparams.drop_path_keep_prob, total_num_cells,
      hparams.total_training_steps)
  reduction_cell = nasnet_utils.NasNetAReductionCell(
      hparams.num_conv_filters, hparams.drop_path_keep_prob, total_num_cells,
      hparams.total_training_steps)
  with arg_scope(
      [slim.dropout, nasnet_utils.drop_path, slim.batch_norm],
      is_training=is_training):
    with arg_scope(
        [
            slim.avg_pool2d, slim.max_pool2d, slim.conv2d, slim.batch_norm,
            slim.separable_conv2d, nasnet_utils.factorized_reduction,
            nasnet_utils.global_avg_pool, nasnet_utils.get_channel_index,
            nasnet_utils.get_channel_dim
        ],
        data_format=hparams.data_format):
      return _build_nasnet_base(
          images,
          normal_cell=normal_cell,
          reduction_cell=reduction_cell,
          num_classes=num_classes,
          hparams=hparams,
          is_training=is_training,
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -