# Copyright 2022 KAIST and 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. """GLPN model configuration""" from huggingface_hub.dataclasses import strict from ...configuration_utils import PreTrainedConfig from ...utils import auto_docstring @auto_docstring(checkpoint="vinvino02/glpn-kitti") @strict class GLPNConfig(PreTrainedConfig): r""" num_encoder_blocks (`int`, *optional*, defaults to 4): The number of encoder blocks (i.e. stages in the Mix Transformer encoder). depths (`list[int]`, *optional*, defaults to `[2, 2, 2, 2]`): The number of layers in each encoder block. sr_ratios (`list[int]`, *optional*, defaults to `[8, 4, 2, 1]`): Sequence reduction ratios in each encoder block. patch_sizes (`list[int]`, *optional*, defaults to `[7, 3, 3, 3]`): Patch size before each encoder block. strides (`list[int]`, *optional*, defaults to `[4, 2, 2, 2]`): Stride before each encoder block. num_attention_heads (`list[int]`, *optional*, defaults to `[1, 2, 5, 8]`): Number of attention heads for each attention layer in each block of the Transformer encoder. mlp_ratios (`list[int]`, *optional*, defaults to `[4, 4, 4, 4]`): Ratio of the size of the hidden layer compared to the size of the input layer of the Mix FFNs in the encoder blocks. decoder_hidden_size (`int`, *optional*, defaults to 64): The dimension of the decoder. max_depth (`int`, *optional*, defaults to 10): The maximum depth of the decoder. head_in_index (`int`, *optional*, defaults to -1): The index of the features to use in the head. Example: ```python >>> from transformers import GLPNModel, GLPNConfig >>> # Initializing a GLPN vinvino02/glpn-kitti style configuration >>> configuration = GLPNConfig() >>> # Initializing a model from the vinvino02/glpn-kitti style configuration >>> model = GLPNModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```""" model_type = "glpn" num_channels: int = 3 num_encoder_blocks: int = 4 depths: list[int] | tuple[int, ...] = (2, 2, 2, 2) sr_ratios: list[int] | tuple[int, ...] = (8, 4, 2, 1) hidden_sizes: list[int] | tuple[int, ...] = (32, 64, 160, 256) patch_sizes: list[int] | tuple[int, ...] = (7, 3, 3, 3) strides: list[int] | tuple[int, ...] = (4, 2, 2, 2) num_attention_heads: list[int] | tuple[int, ...] = (1, 2, 5, 8) mlp_ratios: list[int] | tuple[int, ...] = (4, 4, 4, 4) hidden_act: str = "gelu" hidden_dropout_prob: float | int = 0.0 attention_probs_dropout_prob: float | int = 0.0 initializer_range: float = 0.02 drop_path_rate: float | int = 0.1 layer_norm_eps: float = 1e-6 decoder_hidden_size: int = 64 max_depth: int = 10 head_in_index: int = -1 __all__ = ["GLPNConfig"]