
    fTh                     `    S r SSKJr  SSKJr  \R
                  " \5      r " S S\5      rS/r	g)zTrOCR model configuration   )PretrainedConfig)loggingc                   n   ^  \ rS rSrSrSrS/rSSSS.r                    SU 4S	 jjrS
r	U =r
$ )TrOCRConfig   a  
This is the configuration class to store the configuration of a [`TrOCRForCausalLM`]. It is used to instantiate an
TrOCR model according to the specified arguments, defining the model architecture. Instantiating a configuration
with the defaults will yield a similar configuration to that of the TrOCR
[microsoft/trocr-base-handwritten](https://huggingface.co/microsoft/trocr-base-handwritten) architecture.

Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information.


Args:
    vocab_size (`int`, *optional*, defaults to 50265):
        Vocabulary size of the TrOCR model. Defines the number of different tokens that can be represented by the
        `inputs_ids` passed when calling [`TrOCRForCausalLM`].
    d_model (`int`, *optional*, defaults to 1024):
        Dimensionality of the layers and the pooler layer.
    decoder_layers (`int`, *optional*, defaults to 12):
        Number of decoder layers.
    decoder_attention_heads (`int`, *optional*, defaults to 16):
        Number of attention heads for each attention layer in the Transformer decoder.
    decoder_ffn_dim (`int`, *optional*, defaults to 4096):
        Dimensionality of the "intermediate" (often named feed-forward) layer in decoder.
    activation_function (`str` or `function`, *optional*, defaults to `"gelu"`):
        The non-linear activation function (function or string) in the pooler. If string, `"gelu"`, `"relu"`,
        `"silu"` and `"gelu_new"` are supported.
    max_position_embeddings (`int`, *optional*, defaults to 512):
        The maximum sequence length that this model might ever be used with. Typically set this to something large
        just in case (e.g., 512 or 1024 or 2048).
    dropout (`float`, *optional*, defaults to 0.1):
        The dropout probability for all fully connected layers in the embeddings, and pooler.
    attention_dropout (`float`, *optional*, defaults to 0.0):
        The dropout ratio for the attention probabilities.
    activation_dropout (`float`, *optional*, defaults to 0.0):
        The dropout ratio for activations inside the fully connected layer.
    init_std (`float`, *optional*, defaults to 0.02):
        The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
    decoder_layerdrop (`float`, *optional*, defaults to 0.0):
        The LayerDrop probability for the decoder. See the [LayerDrop paper](see https://arxiv.org/abs/1909.11556)
        for more details.
    use_cache (`bool`, *optional*, defaults to `True`):
        Whether or not the model should return the last key/values attentions (not used by all models).
    scale_embedding (`bool`, *optional*, defaults to `False`):
        Whether or not to scale the word embeddings by sqrt(d_model).
    use_learned_position_embeddings (`bool`, *optional*, defaults to `True`):
        Whether or not to use learned position embeddings. If not, sinusoidal position embeddings will be used.
    layernorm_embedding (`bool`, *optional*, defaults to `True`):
        Whether or not to use a layernorm after the word + position embeddings.

Example:

```python
>>> from transformers import TrOCRConfig, TrOCRForCausalLM

>>> # Initializing a TrOCR-base style configuration
>>> configuration = TrOCRConfig()

>>> # Initializing a model (with random weights) from the TrOCR-base style configuration
>>> model = TrOCRForCausalLM(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```trocrpast_key_valuesdecoder_attention_headsd_modeldecoder_layers)num_attention_headshidden_sizenum_hidden_layersc                    > Xl         X l        X0l        X@l        XPl        X`l        Xpl        Xl        Xl        Xl	        Xl
        Xl        Xl        Xl        UU l        UU l        [         TU ]D  " SUUUUS.UD6  g )N)pad_token_idbos_token_ideos_token_iddecoder_start_token_id )
vocab_sizer   r   r
   decoder_ffn_dimactivation_functionmax_position_embeddingsdropoutattention_dropoutactivation_dropoutinit_stddecoder_layerdrop	use_cachescale_embeddinguse_learned_position_embeddingslayernorm_embeddingsuper__init__)selfr   r   r   r
   r   r   r   r   r   r   r   r   r   r   r    r!   r"   r   r   r   kwargs	__class__s                         e/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/trocr/configuration_trocr.pyr$   TrOCRConfig.__init__`   s    0 %,'>$.#6 '>$!2"4 !2"./N,#6  	
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