big_vision_repo/big_vision/configs/common_fewshot.py

# Copyright 2024 Big Vision 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,
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# See the License for the specific language governing permissions and
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"""Most common few-shot eval configuration."""

import ml_collections as mlc


def get_fewshot_lsr(target_resolution=224, resize_resolution=256,
                    runlocal=False, **kw):
  """Returns a standard-ish fewshot eval configuration."""
  kw.setdefault('representation_layer', 'pre_logits')
  kw.setdefault('shots', (1, 5, 10, 25))
  kw.setdefault('l2_reg', 2.0 ** 10)
  kw.setdefault('num_seeds', 3)
  kw.setdefault('prefix', '')  # No prefix as we already use a/ z/ and zz/

  # Backward-compatible default:
  if not any(f'log_{x}' in kw for x in ['steps', 'percent', 'examples', 'epochs']):  # pylint: disable=line-too-long
    kw['log_steps'] = 25_000

  config = mlc.ConfigDict(kw)
  config.type = 'fewshot_lsr'
  config.datasets = {
      'caltech': ('caltech101', 'train', 'test'),  # copybara:srtip
      'cars': ('cars196:2.1.0', 'train', 'test'),
      'cifar100': ('cifar100', 'train', 'test'),
      'dtd': ('dtd', 'train', 'test'),
      # The first 65000 ImageNet samples have at least 30 shots per any class.
      # Commented out by default because needs manual download.
      # 'imagenet': ('imagenet2012', 'train[:65000]', 'validation'),
      'pets': ('oxford_iiit_pet', 'train', 'test'),
      'uc_merced': ('uc_merced', 'train[:1000]', 'train[1000:]'),
  } if not runlocal else {
      'pets': ('oxford_iiit_pet', 'train', 'test'),
  }
  config.pp_train = (f'decode|resize({resize_resolution})|'
                     f'central_crop({target_resolution})|'
                     f'value_range(-1,1)|keep("image", "label")')
  config.pp_eval = (f'decode|resize({resize_resolution})|'
                    f'central_crop({target_resolution})|'
                    f'value_range(-1,1)|keep("image", "label")')
  config.display_first = [('imagenet', 10)] if not runlocal else [('pets', 10)]

  return config