"""simple docstring"""






import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer


def      UpperCAmelCase__			(							lowerCAmelCase__	:Dict   ,						lowerCAmelCase__	:str   ,						lowerCAmelCase__	:Optional[Any]   ,						lowerCAmelCase__	:Union[str, Any]   ,						lowerCAmelCase__	:int=True   ,						lowerCAmelCase__	:Union[str, Any]="pt"						)					->       int:
      '''simple docstring'''


      lowercase								=      {"""add_prefix_space""": True} if isinstance(lowerCAmelCase__   ,						lowerCAmelCase__						) and not line.startswith(""" """						) else {}
      lowercase								=      padding_side
      return tokenizer(
          [line]   ,						max_length=lowerCAmelCase__   ,						padding="""max_length""" if pad_to_max_length else None   ,						truncation=lowerCAmelCase__   ,						return_tensors=lowerCAmelCase__   ,						add_special_tokens=lowerCAmelCase__   ,						**lowerCAmelCase__   ,						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:Any   ,						lowerCAmelCase__	:int   ,						lowerCAmelCase__	:Tuple=None   ,						)					->       List[str]:
      '''simple docstring'''


      lowercase								=      input_ids.ne(lowerCAmelCase__						).any(dim=0						)
      if attention_mask is None:
            return input_ids[:, keep_column_mask]
      else:
            return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])





class 					_A		(			lowerCAmelCase      ):

      def __init__(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase="train"						,			__lowerCAmelCase=None						,			__lowerCAmelCase=None						,			__lowerCAmelCase=None						,			__lowerCAmelCase=""						,			):







            """simple docstring"""



            super().__init__()
            lowercase								=      Path(__lowerCAmelCase		).joinpath(type_path + """.source"""		)
            lowercase								=      Path(__lowerCAmelCase		).joinpath(type_path + """.target"""		)
            lowercase								=      self.get_char_lens(self.src_file		)
            lowercase								=      max_source_length
            lowercase								=      max_target_length
            assert min(self.src_lens		) > 0, f'found empty line in {self.src_file}'
            lowercase								=      tokenizer
            lowercase								=      prefix
            if n_obs is not None:
                  lowercase								=      self.src_lens[:n_obs]
            lowercase								=      src_lang
            lowercase								=      tgt_lang

      def __len__(		self		):







            """simple docstring"""



            return len(self.src_lens		)

      def __getitem__(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      index + 1  # linecache starts at 1
            lowercase								=      self.prefix + linecache.getline(str(self.src_file		)						,			__lowerCAmelCase		).rstrip("""\n"""		)
            lowercase								=      linecache.getline(str(self.tgt_file		)						,			__lowerCAmelCase		).rstrip("""\n"""		)
            assert source_line, f'empty source line for index {index}'
            assert tgt_line, f'empty tgt line for index {index}'

            # Need to add eos token manually for T5
            if isinstance(self.tokenizer						,			__lowerCAmelCase		):
                  source_line += self.tokenizer.eos_token
                  tgt_line += self.tokenizer.eos_token

            # Pad source and target to the right
            lowercase								=      (
                self.tokenizer.question_encoder if isinstance(self.tokenizer						,			__lowerCAmelCase		) else self.tokenizer
            )
            lowercase								=      self.tokenizer.generator if isinstance(self.tokenizer						,			__lowerCAmelCase		) else self.tokenizer

            lowercase								=      encode_line(__lowerCAmelCase						,			__lowerCAmelCase						,			self.max_source_length						,			"""right"""		)
            lowercase								=      encode_line(__lowerCAmelCase						,			__lowerCAmelCase						,			self.max_target_length						,			"""right"""		)

            lowercase								=      source_inputs["""input_ids"""].squeeze()
            lowercase								=      target_inputs["""input_ids"""].squeeze()
            lowercase								=      source_inputs["""attention_mask"""].squeeze()
            return {
                "input_ids": source_ids,
                "attention_mask": src_mask,
                "decoder_input_ids": target_ids,
            }

      @staticmethod
      def 							A__			(		__lowerCAmelCase		):







            """simple docstring"""



            return [len(__lowerCAmelCase		) for x in Path(__lowerCAmelCase		).open().readlines()]







      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      torch.stack([x["""input_ids"""] for x in batch]		)
            lowercase								=      torch.stack([x["""attention_mask"""] for x in batch]		)
            lowercase								=      torch.stack([x["""decoder_input_ids"""] for x in batch]		)
            lowercase								=      (
                self.tokenizer.generator.pad_token_id
                if isinstance(self.tokenizer						,			__lowerCAmelCase		)
                else self.tokenizer.pad_token_id
            )
            lowercase								=      (
                self.tokenizer.question_encoder.pad_token_id
                if isinstance(self.tokenizer						,			__lowerCAmelCase		)
                else self.tokenizer.pad_token_id
            )
            lowercase								=      trim_batch(__lowerCAmelCase						,			__lowerCAmelCase		)
            lowercase				,				lowercase								=      trim_batch(__lowerCAmelCase						,			__lowerCAmelCase						,			attention_mask=__lowerCAmelCase		)
            lowercase								=      {
                """input_ids""": source_ids,
                """attention_mask""": source_mask,
                """decoder_input_ids""": y,
            }
            return batch






__lowerCAmelCase       :			Any   	=getLogger(__name__)


def      UpperCAmelCase__			(							lowerCAmelCase__	:List[List]						)					->       Any:
      '''simple docstring'''


      return list(itertools.chain.from_iterable(lowerCAmelCase__						)						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:str						)					->       None:
      '''simple docstring'''


      lowercase								=      get_git_info()
      save_json(lowerCAmelCase__   ,						os.path.join(lowerCAmelCase__   ,						"""git_log.json"""						)						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:Any   ,						lowerCAmelCase__	:str   ,						lowerCAmelCase__	:Optional[int]=4   ,						**lowerCAmelCase__	:Optional[int]						)					->       Tuple:
      '''simple docstring'''


      with open(lowerCAmelCase__   ,						"""w"""						) as f:
            json.dump(lowerCAmelCase__   ,						lowerCAmelCase__   ,						indent=lowerCAmelCase__   ,						**lowerCAmelCase__						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:str						)					->       Union[str, Any]:
      '''simple docstring'''


      with open(lowerCAmelCase__						) as f:
            return json.load(lowerCAmelCase__						)


def      UpperCAmelCase__			(							)					->       Optional[int]:
      '''simple docstring'''


      lowercase								=      git.Repo(search_parent_directories=lowerCAmelCase__						)
      lowercase								=      {
          """repo_id""": str(lowerCAmelCase__						),
          """repo_sha""": str(repo.head.object.hexsha						),
          """repo_branch""": str(repo.active_branch						),
          """hostname""": str(socket.gethostname()						),
      }
      return repo_infos


def      UpperCAmelCase__			(							lowerCAmelCase__	:Callable   ,						lowerCAmelCase__	:Iterable						)					->       List:
      '''simple docstring'''


      return list(map(lowerCAmelCase__   ,						lowerCAmelCase__						)						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:List[Any]   ,						lowerCAmelCase__	:int						)					->       Dict:
      '''simple docstring'''


      with open(lowerCAmelCase__   ,						"""wb"""						) as f:
            return pickle.dump(lowerCAmelCase__   ,						lowerCAmelCase__						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:List[str]						)					->       List[str]:
      '''simple docstring'''


      def remove_articles(lowerCAmelCase__	:Tuple						):
            return re.sub(R"""\b(a|an|the)\b"""   ,						""" """   ,						lowerCAmelCase__						)

      def white_space_fix(lowerCAmelCase__	:List[Any]						):
            return " ".join(text.split()						)

      def remove_punc(lowerCAmelCase__	:Dict						):
            lowercase								=      set(string.punctuation						)
            return "".join(ch for ch in text if ch not in exclude						)

      def lower(lowerCAmelCase__	:Dict						):
            return text.lower()

      return white_space_fix(remove_articles(remove_punc(lower(lowerCAmelCase__						)						)						)						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:int   ,						lowerCAmelCase__	:Union[str, Any]						)					->       Any:
      '''simple docstring'''


      lowercase								=      normalize_answer(lowerCAmelCase__						).split()
      lowercase								=      normalize_answer(lowerCAmelCase__						).split()
      lowercase								=      Counter(lowerCAmelCase__						) & Counter(lowerCAmelCase__						)
      lowercase								=      sum(common.values()						)
      if num_same == 0:
            return 0
      lowercase								=      1.0 * num_same / len(lowerCAmelCase__						)
      lowercase								=      1.0 * num_same / len(lowerCAmelCase__						)
      lowercase								=      (2 * precision * recall) / (precision + recall)
      return fa


def      UpperCAmelCase__			(							lowerCAmelCase__	:Dict   ,						lowerCAmelCase__	:Dict						)					->       int:
      '''simple docstring'''


      return normalize_answer(lowerCAmelCase__						) == normalize_answer(lowerCAmelCase__						)


def      UpperCAmelCase__			(							lowerCAmelCase__	:List[str]   ,						lowerCAmelCase__	:List[str]						)					->       Dict:
      '''simple docstring'''


      assert len(lowerCAmelCase__						) == len(lowerCAmelCase__						)
      lowercase								=      0
      for hypo, pred in zip(lowerCAmelCase__   ,						lowerCAmelCase__						):
            em += exact_match_score(lowerCAmelCase__   ,						lowerCAmelCase__						)
      if len(lowerCAmelCase__						) > 0:
            em /= len(lowerCAmelCase__						)
      return {"em": em}


def      UpperCAmelCase__			(							lowerCAmelCase__	:Any						)					->       Tuple:
      '''simple docstring'''


      return model_prefix.startswith("""rag"""						)






def      UpperCAmelCase__			(							lowerCAmelCase__	:str   ,						lowerCAmelCase__	:Any   ,						lowerCAmelCase__	:List[str]						)					->       List[Any]:
      '''simple docstring'''


      lowercase								=      {p: p for p in extra_params}
      # T5 models don't have `dropout` param, they have `dropout_rate` instead
      lowercase								=      """dropout_rate"""
      for p in extra_params:
            if getattr(lowerCAmelCase__   ,						lowerCAmelCase__   ,						lowerCAmelCase__						):
                  if not hasattr(lowerCAmelCase__   ,						lowerCAmelCase__						) and not hasattr(lowerCAmelCase__   ,						equivalent_param[p]						):
                        logger.info("""config doesn't have a `{}` attribute""".format(lowerCAmelCase__						)						)
                        delattr(lowerCAmelCase__   ,						lowerCAmelCase__						)
                        continue
                  lowercase								=      p if hasattr(lowerCAmelCase__   ,						lowerCAmelCase__						) else equivalent_param[p]
                  setattr(lowerCAmelCase__   ,						lowerCAmelCase__   ,						getattr(lowerCAmelCase__   ,						lowerCAmelCase__						)						)
                  delattr(lowerCAmelCase__   ,						lowerCAmelCase__						)
      return hparams, config




"""simple docstring"""






import copy

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


__lowerCAmelCase       :			Tuple   	=logging.get_logger(__name__)

__lowerCAmelCase       :			Dict   	={
    """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}





class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  Optional[int]				    =      'deta'
      snake_case__     :  Dict				    =      {
          'hidden_size': 'd_model',
          'num_attention_heads': 'encoder_attention_heads',
      }

      def __init__(		self						,			__lowerCAmelCase=None						,			__lowerCAmelCase=900						,			__lowerCAmelCase=2048						,			__lowerCAmelCase=6						,			__lowerCAmelCase=2048						,			__lowerCAmelCase=8						,			__lowerCAmelCase=6						,			__lowerCAmelCase=1024						,			__lowerCAmelCase=8						,			__lowerCAmelCase=0.0						,			__lowerCAmelCase=True						,			__lowerCAmelCase="relu"						,			__lowerCAmelCase=256						,			__lowerCAmelCase=0.1						,			__lowerCAmelCase=0.0						,			__lowerCAmelCase=0.0						,			__lowerCAmelCase=0.0_2						,			__lowerCAmelCase=1.0						,			__lowerCAmelCase=True						,			__lowerCAmelCase=False						,			__lowerCAmelCase="sine"						,			__lowerCAmelCase=5						,			__lowerCAmelCase=4						,			__lowerCAmelCase=4						,			__lowerCAmelCase=True						,			__lowerCAmelCase=300						,			__lowerCAmelCase=True						,			__lowerCAmelCase=True						,			__lowerCAmelCase=1						,			__lowerCAmelCase=5						,			__lowerCAmelCase=2						,			__lowerCAmelCase=1						,			__lowerCAmelCase=1						,			__lowerCAmelCase=5						,			__lowerCAmelCase=2						,			__lowerCAmelCase=0.1						,			__lowerCAmelCase=0.2_5						,			**__lowerCAmelCase						,			):







            """simple docstring"""



            if backbone_config is None:
                  logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""		)
                  lowercase								=      CONFIG_MAPPING["""resnet"""](out_features=["""stage2""", """stage3""", """stage4"""]		)
            else:
                  if isinstance(__lowerCAmelCase						,			__lowerCAmelCase		):
                        lowercase								=      backbone_config.pop("""model_type"""		)
                        lowercase								=      CONFIG_MAPPING[backbone_model_type]
                        lowercase								=      config_class.from_dict(__lowerCAmelCase		)

            lowercase								=      backbone_config
            lowercase								=      num_queries
            lowercase								=      max_position_embeddings
            lowercase								=      d_model
            lowercase								=      encoder_ffn_dim
            lowercase								=      encoder_layers
            lowercase								=      encoder_attention_heads
            lowercase								=      decoder_ffn_dim
            lowercase								=      decoder_layers
            lowercase								=      decoder_attention_heads
            lowercase								=      dropout
            lowercase								=      attention_dropout
            lowercase								=      activation_dropout
            lowercase								=      activation_function
            lowercase								=      init_std
            lowercase								=      init_xavier_std
            lowercase								=      encoder_layerdrop
            lowercase								=      auxiliary_loss
            lowercase								=      position_embedding_type
            # deformable attributes
            lowercase								=      num_feature_levels
            lowercase								=      encoder_n_points
            lowercase								=      decoder_n_points
            lowercase								=      two_stage
            lowercase								=      two_stage_num_proposals
            lowercase								=      with_box_refine
            lowercase								=      assign_first_stage
            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
            lowercase								=      class_cost
            lowercase								=      bbox_cost
            lowercase								=      giou_cost
            # Loss coefficients
            lowercase								=      mask_loss_coefficient
            lowercase								=      dice_loss_coefficient
            lowercase								=      bbox_loss_coefficient
            lowercase								=      giou_loss_coefficient
            lowercase								=      eos_coefficient
            lowercase								=      focal_alpha
            super().__init__(is_encoder_decoder=__lowerCAmelCase						,			**__lowerCAmelCase		)

      @property
      def 							A__			(		self		):







            """simple docstring"""



            return self.encoder_attention_heads

      @property
      def 							A__			(		self		):







            """simple docstring"""



            return self.d_model







      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      copy.deepcopy(self.__dict__		)
            lowercase								=      self.backbone_config.to_dict()
            lowercase								=      self.__class__.model_type
            return output



