

"""simple docstring"""




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


SCREAMING_SNAKE_CASE_     :			Union[str, Any]	  =			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_     :			Optional[int]	  =			{
    '''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.json''',
    # See all Deformable DETR models at https://huggingface.co/models?filter=deformable-detr
}


class 		_A       (			__a					):
						__a								=	'deformable_detr'
						__a								=	{
						    'hidden_size': 'd_model',
						    'num_attention_heads': 'encoder_attention_heads',
						}





						def __init__(  self    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__=None    ,						SCREAMING_SNAKE_CASE__=3    ,						SCREAMING_SNAKE_CASE__=300    ,						SCREAMING_SNAKE_CASE__=1024    ,						SCREAMING_SNAKE_CASE__=6    ,						SCREAMING_SNAKE_CASE__=1024    ,						SCREAMING_SNAKE_CASE__=8    ,						SCREAMING_SNAKE_CASE__=6    ,						SCREAMING_SNAKE_CASE__=1024    ,						SCREAMING_SNAKE_CASE__=8    ,						SCREAMING_SNAKE_CASE__=0.0    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__="relu"    ,						SCREAMING_SNAKE_CASE__=256    ,						SCREAMING_SNAKE_CASE__=0.1    ,						SCREAMING_SNAKE_CASE__=0.0    ,						SCREAMING_SNAKE_CASE__=0.0    ,						SCREAMING_SNAKE_CASE__=0.02    ,						SCREAMING_SNAKE_CASE__=1.0    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__=False    ,						SCREAMING_SNAKE_CASE__="sine"    ,						SCREAMING_SNAKE_CASE__="resnet50"    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__=False    ,						SCREAMING_SNAKE_CASE__=4    ,						SCREAMING_SNAKE_CASE__=4    ,						SCREAMING_SNAKE_CASE__=4    ,						SCREAMING_SNAKE_CASE__=False    ,						SCREAMING_SNAKE_CASE__=300    ,						SCREAMING_SNAKE_CASE__=False    ,						SCREAMING_SNAKE_CASE__=1    ,						SCREAMING_SNAKE_CASE__=5    ,						SCREAMING_SNAKE_CASE__=2    ,						SCREAMING_SNAKE_CASE__=1    ,						SCREAMING_SNAKE_CASE__=1    ,						SCREAMING_SNAKE_CASE__=5    ,						SCREAMING_SNAKE_CASE__=2    ,						SCREAMING_SNAKE_CASE__=0.1    ,						SCREAMING_SNAKE_CASE__=0.25    ,						SCREAMING_SNAKE_CASE__=False    ,						**SCREAMING_SNAKE_CASE__    ,						)   ->					Tuple:
									if backbone_config is not None and use_timm_backbone:
												raise ValueError("You can't specify both `backbone_config` and `use_timm_backbone`."		)

									if not use_timm_backbone:
												if backbone_config is None:
															logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."		)
															lowerCamelCase__						=			CONFIG_MAPPING["resnet"](out_features=["stage4"]		)
												elif isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		):
															lowerCamelCase__						=			backbone_config.get("model_type"		)
															lowerCamelCase__						=			CONFIG_MAPPING[backbone_model_type]
															lowerCamelCase__						=			config_class.from_dict(SCREAMING_SNAKE_CASE__		)
									lowerCamelCase__						=			use_timm_backbone
									lowerCamelCase__						=			backbone_config
									lowerCamelCase__						=			num_channels
									lowerCamelCase__						=			num_queries
									lowerCamelCase__						=			max_position_embeddings
									lowerCamelCase__						=			d_model
									lowerCamelCase__						=			encoder_ffn_dim
									lowerCamelCase__						=			encoder_layers
									lowerCamelCase__						=			encoder_attention_heads
									lowerCamelCase__						=			decoder_ffn_dim
									lowerCamelCase__						=			decoder_layers
									lowerCamelCase__						=			decoder_attention_heads
									lowerCamelCase__						=			dropout
									lowerCamelCase__						=			attention_dropout
									lowerCamelCase__						=			activation_dropout
									lowerCamelCase__						=			activation_function
									lowerCamelCase__						=			init_std
									lowerCamelCase__						=			init_xavier_std
									lowerCamelCase__						=			encoder_layerdrop
									lowerCamelCase__						=			auxiliary_loss
									lowerCamelCase__						=			position_embedding_type
									lowerCamelCase__						=			backbone
									lowerCamelCase__						=			use_pretrained_backbone
									lowerCamelCase__						=			dilation
									# deformable attributes
									lowerCamelCase__						=			num_feature_levels
									lowerCamelCase__						=			encoder_n_points
									lowerCamelCase__						=			decoder_n_points
									lowerCamelCase__						=			two_stage
									lowerCamelCase__						=			two_stage_num_proposals
									lowerCamelCase__						=			with_box_refine
									if two_stage is True and with_box_refine is False:
												raise ValueError("If two_stage is True, with_box_refine must be True."		)
									# Hungarian matcher
									lowerCamelCase__						=			class_cost
									lowerCamelCase__						=			bbox_cost
									lowerCamelCase__						=			giou_cost
									# Loss coefficients
									lowerCamelCase__						=			mask_loss_coefficient
									lowerCamelCase__						=			dice_loss_coefficient
									lowerCamelCase__						=			bbox_loss_coefficient
									lowerCamelCase__						=			giou_loss_coefficient
									lowerCamelCase__						=			eos_coefficient
									lowerCamelCase__						=			focal_alpha
									lowerCamelCase__						=			disable_custom_kernels
									super().__init__(is_encoder_decoder=SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)





						@property
						def 					_lowerCamelCase  (  self		)   ->					int:
									return self.encoder_attention_heads





						@property
						def 					_lowerCamelCase  (  self		)   ->					int:
									return self.d_model





						def 					_lowerCamelCase  (  self		)   ->					Any:
									lowerCamelCase__						=			copy.deepcopy(self.__dict__		)
									if self.backbone_config is not None:
												lowerCamelCase__						=			self.backbone_config.to_dict()
									lowerCamelCase__						=			self.__class__.model_type
									return output







"""simple docstring"""




import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin


class 		_A       (			__a				,       unittest.TestCase					):
      __a								=	PhobertTokenizer
      __a								=	False





      def 					_lowerCamelCase  (  self		)   ->					Any:
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         lowerCamelCase__						=			["T@@", "i", "I", "R@@", "r", "e@@"]
         lowerCamelCase__						=			dict(zip(SCREAMING_SNAKE_CASE__    ,						range(len(SCREAMING_SNAKE_CASE__		)		)		)		)
         lowerCamelCase__						=			["#version: 0.2", "l à</w>"]
         lowerCamelCase__						=			{"unk_token": "<unk>"}

         lowerCamelCase__						=			os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["vocab_file"]		)
         lowerCamelCase__						=			os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["merges_file"]		)

         with open(self.vocab_file    ,						"w"    ,						encoding="utf-8"		) as fp:
            for token in vocab_tokens:
               fp.write(f'{token} {vocab_tokens[token]}\n'		)
         with open(self.merges_file    ,						"w"    ,						encoding="utf-8"		) as fp:
            fp.write("\n".join(SCREAMING_SNAKE_CASE__		)		)





      def 					_lowerCamelCase  (  self    ,						**SCREAMING_SNAKE_CASE__		)   ->					Tuple:
         kwargs.update(self.special_tokens_map		)
         return PhobertTokenizer.from_pretrained(self.tmpdirname    ,						**SCREAMING_SNAKE_CASE__		)





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__		)   ->					Tuple:
         lowerCamelCase__						=			"Tôi là VinAI Research"
         lowerCamelCase__						=			"T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
         return input_text, output_text





      def 					_lowerCamelCase  (  self		)   ->					Tuple:
         lowerCamelCase__						=			PhobertTokenizer(self.vocab_file    ,						self.merges_file    ,						**self.special_tokens_map		)
         lowerCamelCase__						=			"Tôi là VinAI Research"
         lowerCamelCase__						=			"T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
         lowerCamelCase__						=			tokenizer.tokenize(SCREAMING_SNAKE_CASE__		)
         print(SCREAMING_SNAKE_CASE__		)
         self.assertListEqual(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		)

         lowerCamelCase__						=			tokens + [tokenizer.unk_token]

         lowerCamelCase__						=			[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__		)    ,						SCREAMING_SNAKE_CASE__		)




