
    Z j{                     d    S r SSKJr  SSKJr  SSKJr  \" SS9\ " S S	\5      5       5       rS	/rg
)zGLPN model configuration    )strict   )PreTrainedConfig)auto_docstringzvinvino02/glpn-kitti)
checkpointc                      \ rS rSr% SrSrSr\\S'   Sr	\\S'   Sr
\\   \\S	4   -  \S
'   Sr\\   \\S	4   -  \S'   Sr\\   \\S	4   -  \S'   Sr\\   \\S	4   -  \S'   Sr\\   \\S	4   -  \S'   Sr\\   \\S	4   -  \S'   Sr\\   \\S	4   -  \S'   Sr\\S'   Sr\\-  \S'   Sr\\-  \S'   Sr\\S'   Sr\\-  \S'   S r\\S!'   S"r\\S#'   S$r\\S%'   S&r\\S''   S(rg))*
GLPNConfig   a*  
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
```glpnr   num_channels   num_encoder_blocks)   r   r   r   .depths)   r   r      	sr_ratios)    @         hidden_sizes)   r   r   r   patch_sizes)r   r   r   r   strides)r   r      r   num_attention_heads)r   r   r   r   
mlp_ratiosgelu
hidden_actg        hidden_dropout_probattention_probs_dropout_probg{Gz?initializer_rangeg?drop_path_rategư>layer_norm_epsr   decoder_hidden_size
   	max_depthhead_in_index N)__name__
__module____qualname____firstlineno____doc__
model_typer   int__annotations__r   r   listtupler   r   r   r   r   r   r    strr!   floatr"   r#   r$   r%   r&   r(   r*   __static_attributes__r+       |/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/glpn/configuration_glpn.pyr	   r	      sL   $L JL#*6FDIc3h'6-9ItCy5c?*90BL$s)eCHo-B/;KcU38_,;+7GT#YsCx(77CcU38_4C.:JS	E#s(O+:J'**03 %#+3#u#"%NECK% NE !!IsM3r9   r	   N)	r0   huggingface_hub.dataclassesr   configuration_utilsr   utilsr   r	   __all__r+   r9   r:   <module>r?      sG     . 3 # 12:! :  3:z .r9   