


import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin







class       _lowercase			(							lowercase__							,  unittest.TestCase):


       """simple docstring"""




       A__ 						=      SpeechaTextaTokenizer
       A__ 						=      False





       def 						lowerCAmelCase					(       self							:      Optional[Any]	):


             '''simple docstring'''



             super().setUp()

             lowerCamelCase__		:    List[Any]   =  "<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" "	)
             lowerCamelCase__		:    str   =  ["he re</w> 123", "here a 1456"]
             lowerCamelCase__		:    List[Any]   =  dict(zip(__lowerCamelCase ,				range(len(__lowerCamelCase	)	)	)	)

             lowerCamelCase__		:    Union[str, Any]   =  {"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

             lowerCamelCase__		:    List[str]   =  tempfile.mkdtemp()
             lowerCamelCase__		:    str   =  os.path.join(self.tmpdirname ,				VOCAB_FILES_NAMES["vocab_file"]	)
             lowerCamelCase__		:    int   =  os.path.join(self.tmpdirname ,				VOCAB_FILES_NAMES["merges_file"]	)

             with open(self.vocab_file ,				"w" ,				encoding="utf-8"	) as fp:
                   fp.write(json.dumps(__lowerCamelCase	) + "\n"	)

             with open(self.merges_file ,				"w"	) as fp:
                   fp.write("\n".join(__lowerCamelCase	)	)





       def 						lowerCAmelCase					(       self							:      Any	):


             '''simple docstring'''



             lowerCamelCase__		:    Any   =  list(self.get_tokenizer().get_vocab().keys()	)

             self.assertEqual(vocab_keys[0] ,				"<s>"	)
             self.assertEqual(vocab_keys[1] ,				"<pad>"	)
             self.assertEqual(vocab_keys[-1] ,				"vocab"	)
             self.assertEqual(len(__lowerCamelCase	) ,				14	)





       def 						lowerCAmelCase					(       self							:      Tuple	):


             '''simple docstring'''



             self.assertEqual(self.get_tokenizer().vocab_size ,				14	)





       def 						lowerCAmelCase					(       self							:      List[Any]	):


             '''simple docstring'''



             lowerCamelCase__		:    List[str]   =  SpeechaTextaTokenizer.from_pretrained(self.tmpdirname	)

             # make sure @@ is correctly concatenated
             lowerCamelCase__		:    Any   =  [4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
             lowerCamelCase__		:    Optional[Any]   =  tokenizer.decode(__lowerCamelCase	)

             self.assertTrue(output_string == "herecouple words ofthe"	)





       def 						lowerCAmelCase					(       self							:      Tuple	):


             '''simple docstring'''



             lowerCamelCase__		:    List[Any]   =  SpeechaTextaTokenizer.from_pretrained(self.tmpdirname	)

             with tempfile.TemporaryDirectory() as tmp_dirname:
                   tokenizer.save_pretrained(__lowerCamelCase	)
                   os.remove(os.path.join(__lowerCamelCase ,				"merges.txt"	)	)

                   # load tokenizer without merges file should not throw an error
                   lowerCamelCase__		:    Dict   =  SpeechaTextaTokenizer.from_pretrained(__lowerCamelCase	)

             with tempfile.TemporaryDirectory() as tmp_dirname:
                   # save tokenizer and load again
                   tokenizer.save_pretrained(__lowerCamelCase	)
                   lowerCamelCase__		:    Any   =  SpeechaTextaTokenizer.from_pretrained(__lowerCamelCase	)

             self.assertIsNotNone(__lowerCamelCase	)





       def 						lowerCAmelCase					(       self							:      Optional[Any]	):


             '''simple docstring'''



             if not self.test_slow_tokenizer:
                   return

             lowerCamelCase__		:    List[Any]   =  inspect.signature(self.tokenizer_class.__init__	)
             lowerCamelCase__		:    Optional[int]   =  self.get_tokenizer()

             for parameter_name, parameter in signature.parameters.items():
                   if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
                         self.assertIn(__lowerCamelCase ,				tokenizer.init_kwargs	)






from ...configuration_utils import PretrainedConfig
from ...utils import is_detectrona_available, logging


A				:   int		= logging.get_logger(__name__)

A				:   Any		= {
    "layoutlmv2-base-uncased": "https://huggingface.co/microsoft/layoutlmv2-base-uncased/resolve/main/config.json",
    "layoutlmv2-large-uncased": "https://huggingface.co/microsoft/layoutlmv2-large-uncased/resolve/main/config.json",
    # See all LayoutLMv2 models at https://huggingface.co/models?filter=layoutlmv2
}

# soft dependency
if is_detectrona_available():
    import detectrona







class       _lowercase			(							lowercase__):


       """simple docstring"""




       A__ 						=      "layoutlmv2"





       def __init__(       self							:      Union[str, Any] ,				__lowerCamelCase							:      int=30522 ,				__lowerCamelCase							:      List[Any]=768 ,				__lowerCamelCase							:      Any=12 ,				__lowerCamelCase							:      List[Any]=12 ,				__lowerCamelCase							:      Optional[Any]=3072 ,				__lowerCamelCase							:      List[Any]="gelu" ,				__lowerCamelCase							:      Any=0.1 ,				__lowerCamelCase							:      Union[str, Any]=0.1 ,				__lowerCamelCase							:      int=512 ,				__lowerCamelCase							:      str=2 ,				__lowerCamelCase							:      Any=0.0_2 ,				__lowerCamelCase							:      List[Any]=1E-1_2 ,				__lowerCamelCase							:      List[str]=0 ,				__lowerCamelCase							:      Union[str, Any]=1024 ,				__lowerCamelCase							:      Tuple=128 ,				__lowerCamelCase							:      Tuple=32 ,				__lowerCamelCase							:      Union[str, Any]=True ,				__lowerCamelCase							:      List[Any]=256 ,				__lowerCamelCase							:      Dict=64 ,				__lowerCamelCase							:      List[Any]=True ,				__lowerCamelCase							:      Union[str, Any]=[7, 7, 256] ,				__lowerCamelCase							:      str=128 ,				__lowerCamelCase							:      Dict=128 ,				__lowerCamelCase							:      Dict=True ,				__lowerCamelCase							:      int=True ,				__lowerCamelCase							:      str=False ,				__lowerCamelCase							:      Tuple=None ,				**__lowerCamelCase							:      str ,				):


             '''simple docstring'''



             super().__init__(
                 vocab_size=__lowerCamelCase ,				hidden_size=__lowerCamelCase ,				num_hidden_layers=__lowerCamelCase ,				num_attention_heads=__lowerCamelCase ,				intermediate_size=__lowerCamelCase ,				hidden_act=__lowerCamelCase ,				hidden_dropout_prob=__lowerCamelCase ,				attention_probs_dropout_prob=__lowerCamelCase ,				max_position_embeddings=__lowerCamelCase ,				type_vocab_size=__lowerCamelCase ,				initializer_range=__lowerCamelCase ,				layer_norm_eps=__lowerCamelCase ,				pad_token_id=__lowerCamelCase ,				**__lowerCamelCase ,				)
             lowerCamelCase__		:    Dict   =  max_ad_position_embeddings
             lowerCamelCase__		:    int   =  max_rel_pos
             lowerCamelCase__		:    List[Any]   =  rel_pos_bins
             lowerCamelCase__		:    str   =  fast_qkv
             lowerCamelCase__		:    Optional[Any]   =  max_rel_ad_pos
             lowerCamelCase__		:    List[Any]   =  rel_ad_pos_bins
             lowerCamelCase__		:    Optional[Any]   =  convert_sync_batchnorm
             lowerCamelCase__		:    Any   =  image_feature_pool_shape
             lowerCamelCase__		:    List[Any]   =  coordinate_size
             lowerCamelCase__		:    Any   =  shape_size
             lowerCamelCase__		:    List[str]   =  has_relative_attention_bias
             lowerCamelCase__		:    Optional[int]   =  has_spatial_attention_bias
             lowerCamelCase__		:    Optional[Any]   =  has_visual_segment_embedding
             lowerCamelCase__		:    List[str]   =  (
                 detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
             )





       @classmethod
       def 						lowerCAmelCase					(       self							:      List[Any]	):


             '''simple docstring'''



             return {
                 "MODEL.MASK_ON": True,
                 "MODEL.PIXEL_STD": [5_7.3_7_5, 5_7.1_2_0, 5_8.3_9_5],
                 "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
                 "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
                 "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [128], [256], [512]],
                 "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
                 "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2000,
                 "MODEL.RPN.PRE_NMS_TOPK_TEST": 1000,
                 "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1000,
                 "MODEL.POST_NMS_TOPK_TEST": 1000,
                 "MODEL.ROI_HEADS.NAME": "StandardROIHeads",
                 "MODEL.ROI_HEADS.NUM_CLASSES": 5,
                 "MODEL.ROI_HEADS.IN_FEATURES": ["p2", "p3", "p4", "p5"],
                 "MODEL.ROI_BOX_HEAD.NAME": "FastRCNNConvFCHead",
                 "MODEL.ROI_BOX_HEAD.NUM_FC": 2,
                 "MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION": 14,
                 "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead",
                 "MODEL.ROI_MASK_HEAD.NUM_CONV": 4,
                 "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7,
                 "MODEL.RESNETS.DEPTH": 101,
                 "MODEL.RESNETS.SIZES": [[32], [64], [128], [256], [512]],
                 "MODEL.RESNETS.ASPECT_RATIOS": [[0.5, 1.0, 2.0]],
                 "MODEL.RESNETS.OUT_FEATURES": ["res2", "res3", "res4", "res5"],
                 "MODEL.RESNETS.NUM_GROUPS": 32,
                 "MODEL.RESNETS.WIDTH_PER_GROUP": 8,
                 "MODEL.RESNETS.STRIDE_IN_1X1": False,
             }





       def 						lowerCAmelCase					(       self							:      List[Any]	):


             '''simple docstring'''



             lowerCamelCase__		:    Optional[int]   =  detectrona.config.get_cfg()
             for k, v in self.detectrona_config_args.items():
                   lowerCamelCase__		:    List[Any]   =  k.split("."	)
                   lowerCamelCase__		:    int   =  detectrona_config
                   for attribute in attributes[:-1]:
                         lowerCamelCase__		:    Any   =  getattr(__lowerCamelCase ,				__lowerCamelCase	)
                   setattr(__lowerCamelCase ,				attributes[-1] ,				__lowerCamelCase	)

             return detectrona_config


