# Copyright 2023 The HuggingFace Inc. team. 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. """VitMatte model configuration""" from huggingface_hub.dataclasses import strict from ...backbone_utils import consolidate_backbone_kwargs_to_config from ...configuration_utils import PreTrainedConfig from ...utils import auto_docstring from ..auto.configuration_auto import AutoConfig @auto_docstring(checkpoint="hustvl/vitmatte-small-composition-1k") @strict class VitMatteConfig(PreTrainedConfig): r""" batch_norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the batch norm layers. convstream_hidden_sizes (`list[int]`, *optional*, defaults to `[48, 96, 192]`): The output channels of the ConvStream module. fusion_hidden_sizes (`list[int]`, *optional*, defaults to `[256, 128, 64, 32]`): The output channels of the Fusion blocks. Example: ```python >>> from transformers import VitMatteConfig, VitMatteForImageMatting >>> # Initializing a ViTMatte hustvl/vitmatte-small-composition-1k style configuration >>> configuration = VitMatteConfig() >>> # Initializing a model (with random weights) from the hustvl/vitmatte-small-composition-1k style configuration >>> model = VitMatteForImageMatting(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" model_type = "vitmatte" sub_configs = {"backbone_config": AutoConfig} backbone_config: dict | PreTrainedConfig | None = None hidden_size: int = 384 batch_norm_eps: float = 1e-5 initializer_range: float = 0.02 convstream_hidden_sizes: list[int] | tuple[int, ...] = (48, 96, 192) fusion_hidden_sizes: list[int] | tuple[int, ...] = (256, 128, 64, 32) def __post_init__(self, **kwargs): self.backbone_config, kwargs = consolidate_backbone_kwargs_to_config( backbone_config=self.backbone_config, default_config_type="vitdet", default_config_kwargs={"out_features": ["stage4"]}, **kwargs, ) super().__post_init__(**kwargs) __all__ = ["VitMatteConfig"]