text: # coding=utf-8
  # Copyright 2022 The Google Research Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """Configuration file."""
  # pylint: disable=line-too-long
  
  import ml_collections
  
  
  def get_config():
    """Get the default hyperparameter configuration."""
    config = ml_collections.ConfigDict()
    config.seed = 42
    config.trial = 0  # Dummy for repeated runs.
  
    config.dataset = "billiardleft-color-min-max"  # -- overwritten in sweep
    config.train_preprocess_str = "to_float_0_1"
    config.eval_preprocess_str = "to_float_0_1"
  
    # Top-k extraction.
    config.model = "patchnet"
    config.k = 10
    config.patch_size = 100
    config.downscale = 4
    config.feature_network = "ResNet50"
  
    config.aggregation_method = "maxpooling"
  
    config.scorer_has_se = True
  
    config.selection_method = "perturbed-topk"
    config.selection_method_inference = "hard-topk"
  
    # parameters for perturbed_topk
    config.perturbed_topk_kwargs = ml_collections.ConfigDict()
    config.perturbed_topk_kwargs.num_samples = 500
    config.perturbed_topk_kwargs.sigma = 0.05
  
    config.normalization_str = "zerooneeps(1e-5)"
    config.use_iterative_extraction = True
  
    # Same set up as usual.
    config.optimizer = "adam"
    config.learning_rate = 1e-10
    config.batch_size = 2
    config.num_train_steps = 201
  
    config.log_loss_every_steps = 100
    config.eval_every_steps = 100
    config.checkpoint_every_steps = 5000
    config.log_images = False
    config.log_histograms = False
    config.do_eval_only = True
  
    config.trial = 0  # Dummy for repeated runs.
  
    return config
  
  
  