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- # 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"]
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