# Copyright 2022 The TensorFlow Authors. All Rights Reserved. # # 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. """Backbones configurations.""" import dataclasses from typing import Optional, Tuple from official.modeling import hyperparams @dataclasses.dataclass class Transformer(hyperparams.Config): """Transformer config.""" mlp_dim: int = 1 num_heads: int = 1 num_layers: int = 1 attention_dropout_rate: float = 0.0 dropout_rate: float = 0.1 @dataclasses.dataclass class VisionTransformer(hyperparams.Config): """VisionTransformer config.""" model_name: str = 'vit-b16' # pylint: disable=line-too-long pooler: str = 'token' # 'token', 'gap' or 'none'. If set to 'token', an extra classification token is added to sequence. # pylint: enable=line-too-long representation_size: int = 0 hidden_size: int = 1 patch_size: int = 16 transformer: Transformer = Transformer() init_stochastic_depth_rate: float = 0.0 original_init: bool = True pos_embed_shape: Optional[Tuple[int, int]] = None @dataclasses.dataclass class Backbone(hyperparams.OneOfConfig): """Configuration for backbones. Attributes: type: 'str', type of backbone be used, one the of fields below. vit: vit backbone config. """ type: Optional[str] = None vit: VisionTransformer = VisionTransformer()