o ei @s@dZddlmZddlmZeeZGdddeZdgZ dS)zUDOP model configuration)PreTrainedConfig)loggingcs|eZdZdZdZdgZddddZdd d d d d dddddiddiddigddddddddd ddddddffdd ZZS)! UdopConfiga This is the configuration class to store the configuration of a [`UdopForConditionalGeneration`]. It is used to instantiate a UDOP 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 UDOP [microsoft/udop-large](https://huggingface.co/microsoft/udop-large) architecture. Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Arguments: vocab_size (`int`, *optional*, defaults to 33201): Vocabulary size of the UDOP model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`UdopForConditionalGeneration`]. d_model (`int`, *optional*, defaults to 1024): Size of the encoder layers and the pooler layer. d_kv (`int`, *optional*, defaults to 64): Size of the key, query, value projections per attention head. The `inner_dim` of the projection layer will be defined as `num_heads * d_kv`. d_ff (`int`, *optional*, defaults to 4096): Size of the intermediate feed forward layer in each `UdopBlock`. num_layers (`int`, *optional*, defaults to 24): Number of hidden layers in the Transformer encoder and decoder. num_decoder_layers (`int`, *optional*): Number of hidden layers in the Transformer decoder. Will use the same value as `num_layers` if not set. num_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the Transformer encoder and decoder. relative_attention_num_buckets (`int`, *optional*, defaults to 32): The number of buckets to use for each attention layer. relative_attention_max_distance (`int`, *optional*, defaults to 128): The maximum distance of the longer sequences for the bucket separation. relative_bias_args (`list[dict]`, *optional*, defaults to `[{'type': '1d'}, {'type': 'horizontal'}, {'type': 'vertical'}]`): A list of dictionaries containing the arguments for the relative bias layers. dropout_rate (`float`, *optional*, defaults to 0.1): The ratio for all dropout layers. layer_norm_epsilon (`float`, *optional*, defaults to 1e-06): The epsilon used by the layer normalization layers. initializer_factor (`float`, *optional*, defaults to 1.0): A factor for initializing all weight matrices (should be kept to 1, used internally for initialization testing). feed_forward_proj (`string`, *optional*, defaults to `"relu"`): Type of feed forward layer to be used. Should be one of `"relu"` or `"gated-gelu"`. Udopv1.1 uses the `"gated-gelu"` feed forward projection. Original Udop uses `"relu"`. is_encoder_decoder (`bool`, *optional*, defaults to `True`): Whether the model should behave as an encoder/decoder or not. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). pad_token_id (`int`, *optional*, defaults to 0): The id of the padding token in the vocabulary. eos_token_id (`int`, *optional*, defaults to 1): The id of the end-of-sequence token in the vocabulary. max_2d_position_embeddings (`int`, *optional*, defaults to 1024): The maximum absolute position embeddings for relative position encoding. image_size (`int`, *optional*, defaults to 224): The size of the input images. patch_size (`int`, *optional*, defaults to 16): The patch size used by the vision encoder. num_channels (`int`, *optional*, defaults to 3): The number of channels in the input images. is_decoder (`bool`, *optional*, defaults to `False`): Whether to only use the decoder in an encoder-decoder architecture, otherwise it has no effect on decoder-only or encoder-only architectures. add_cross_attention (`bool`, *optional*, defaults to `False`): Whether cross-attention layers should be added to the model. tie_word_embeddings (`bool`, *optional*, defaults to `True`): Whether to tie weight embeddings udoppast_key_valuesd_model num_heads num_layers) hidden_sizenum_attention_headsnum_hidden_layersii@iN type1d horizontalverticalg?gư>g?reluTrFc s"||_||_||_||_||_||_||_|dur|n|j|_||_||_ | |_ | |_ | |_ | |_ ||_||_||_||_||_||_||_||_t| tsRtd| |_|jd}|d|_|ddk|_t|dkrs|ddksyt|dkrtd|d d |_t j!d d |i|dS) Nz6`relative_bias_args` should be a list of dictionaries.-rgatedrz`feed_forward_proj`: z is not a valid activation function of the dense layer.Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. 'gated-gelu' or 'relu'Tis_encoder_decoder)" is_decoderadd_cross_attention vocab_sizerd_kvd_ffr num_decoder_layersrrelative_attention_num_bucketsrelative_attention_max_distance dropout_ratelayer_norm_epsiloninitializer_factorfeed_forward_proj use_cache pad_token_id eos_token_idmax_2d_position_embeddings image_size patch_size num_channels isinstancelist TypeErrorrelative_bias_argssplit dense_act_fn is_gated_actlen ValueErrortie_word_embeddingssuper__init__)selfr"rr#r$r r%rr&r'r6r(r)r*r+rr,r-r.r/r0r1r2r r!r<kwargsact_info __class__ri/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/transformers/models/udop/configuration_udop.pyr>_sF   $ zUdopConfig.__init__) __name__ __module__ __qualname____doc__ model_typekeys_to_ignore_at_inference attribute_mapr> __classcell__rrrBrDrs>C rN) rHconfiguration_utilsrutilsr get_loggerrEloggerr__all__rrrrDs