





'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_					= logging.get_logger(__name__)

lowercase_					= {
    """unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json""",
}


class 					a_     (				snake_case_       ):

    '''simple docstring'''
    UpperCamelCase     = '''lxmert'''
    UpperCamelCase     = {}


    def __init__(		self ,		A=3_0522 ,		A=768 ,		A=12 ,		A=9500 ,		A=1600 ,		A=400 ,		A=3072 ,		A="gelu" ,		A=0.1 ,		A=0.1 ,		A=512 ,		A=2 ,		A=0.02 ,		A=1e-12 ,		A=9 ,		A=5 ,		A=5 ,		A=2048 ,		A=4 ,		A=6.67 ,		A=True ,		A=True ,		A=True ,		A=True ,		A=True ,		A=True ,		A=True ,		**A ,		)		->   int:
        _SCREAMING_SNAKE_CASE									=			vocab_size
        _SCREAMING_SNAKE_CASE									=			hidden_size
        _SCREAMING_SNAKE_CASE									=			num_attention_heads
        _SCREAMING_SNAKE_CASE									=			hidden_act
        _SCREAMING_SNAKE_CASE									=			intermediate_size
        _SCREAMING_SNAKE_CASE									=			hidden_dropout_prob
        _SCREAMING_SNAKE_CASE									=			attention_probs_dropout_prob
        _SCREAMING_SNAKE_CASE									=			max_position_embeddings
        _SCREAMING_SNAKE_CASE									=			type_vocab_size
        _SCREAMING_SNAKE_CASE									=			initializer_range
        _SCREAMING_SNAKE_CASE									=			layer_norm_eps
        _SCREAMING_SNAKE_CASE									=			num_qa_labels
        _SCREAMING_SNAKE_CASE									=			num_object_labels
        _SCREAMING_SNAKE_CASE									=			num_attr_labels
        _SCREAMING_SNAKE_CASE									=			l_layers
        _SCREAMING_SNAKE_CASE									=			x_layers
        _SCREAMING_SNAKE_CASE									=			r_layers
        _SCREAMING_SNAKE_CASE									=			visual_feat_dim
        _SCREAMING_SNAKE_CASE									=			visual_pos_dim
        _SCREAMING_SNAKE_CASE									=			visual_loss_normalizer
        _SCREAMING_SNAKE_CASE									=			task_matched
        _SCREAMING_SNAKE_CASE									=			task_mask_lm
        _SCREAMING_SNAKE_CASE									=			task_obj_predict
        _SCREAMING_SNAKE_CASE									=			task_qa
        _SCREAMING_SNAKE_CASE									=			visual_obj_loss
        _SCREAMING_SNAKE_CASE									=			visual_attr_loss
        _SCREAMING_SNAKE_CASE									=			visual_feat_loss
        _SCREAMING_SNAKE_CASE									=			{"""vision""": r_layers, """cross_encoder""": x_layers, """language""": l_layers}
        super().__init__(**A       )










'''simple docstring'''

import os

from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home


lowercase_					= HUGGINGFACE_HUB_CACHE


lowercase_					= """config.json"""
lowercase_					= """diffusion_pytorch_model.bin"""
lowercase_					= """diffusion_flax_model.msgpack"""
lowercase_					= """model.onnx"""
lowercase_					= """diffusion_pytorch_model.safetensors"""
lowercase_					= """weights.pb"""
lowercase_					= """https://huggingface.co"""
lowercase_					= default_cache_path
lowercase_					= """diffusers_modules"""
lowercase_					= os.getenv("""HF_MODULES_CACHE""", os.path.join(hf_cache_home, """modules"""))
lowercase_					= ["""fp16""", """non-ema"""]
lowercase_					= """.self_attn"""



