

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      _lowerCAmelCase(	__A   ,       __A   ,       __A   ,       __A   ,       __A=True   ,       __A="pt"			):
		UpperCAmelCase					      =  {"""add_prefix_space""": True} if isinstance(lowerCamelCase_   ,       lowerCamelCase_			) and not line.startswith(" "			) else {}
		UpperCAmelCase					      =  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      _lowerCAmelCase(	__A   ,       __A   ,       __A=None   ,       ):
		UpperCAmelCase					      =  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 						__magic_name__    (       lowercase_    ):


	def __init__(						self		: str			,						lowerCAmelCase__		: Tuple			,						lowerCAmelCase__		: Tuple			,						lowerCAmelCase__		: List[str]			,						lowerCAmelCase__		: List[str]			,						lowerCAmelCase__		: List[str]="train"			,						lowerCAmelCase__		: List[str]=None			,						lowerCAmelCase__		: List[Any]=None			,						lowerCAmelCase__		: int=None			,						lowerCAmelCase__		: Union[str, Any]=""			,						)    ->      Optional[Any]:
			super().__init__()
			UpperCAmelCase					      =  Path(lowerCamelCase_    ).joinpath(type_path + ".source"    )
			UpperCAmelCase					      =  Path(lowerCamelCase_    ).joinpath(type_path + ".target"    )
			UpperCAmelCase					      =  self.get_char_lens(self.src_file    )
			UpperCAmelCase					      =  max_source_length
			UpperCAmelCase					      =  max_target_length
			assert min(self.src_lens    ) > 0, f"found empty line in {self.src_file}"
			UpperCAmelCase					      =  tokenizer
			UpperCAmelCase					      =  prefix
			if n_obs is not None:
					UpperCAmelCase					      =  self.src_lens[:n_obs]
			UpperCAmelCase					      =  src_lang
			UpperCAmelCase					      =  tgt_lang


	def __len__(						self		: List[Any]    )    ->      Tuple:
			return len(self.src_lens    )


	def __getitem__(						self		: Union[str, Any]			,						lowerCAmelCase__		: Optional[Any]    )    ->      Tuple:
			UpperCAmelCase					      =  index + 1  # linecache starts at 1
			UpperCAmelCase					      =  self.prefix + linecache.getline(str(self.src_file    )			,						lowerCamelCase_    ).rstrip("\n"    )
			UpperCAmelCase					      =  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
			UpperCAmelCase					      =  (
			    self.tokenizer.question_encoder if isinstance(self.tokenizer			,						lowerCamelCase_    ) else self.tokenizer
			)
			UpperCAmelCase					      =  self.tokenizer.generator if isinstance(self.tokenizer			,						lowerCamelCase_    ) else self.tokenizer

			UpperCAmelCase					      =  encode_line(lowerCamelCase_			,						lowerCamelCase_			,						self.max_source_length			,						"right"    )
			UpperCAmelCase					      =  encode_line(lowerCamelCase_			,						lowerCamelCase_			,						self.max_target_length			,						"right"    )

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


	@staticmethod
	def _UpperCamelCase	(						lowerCAmelCase__		: Dict    )    ->      Any:
			return [len(lowerCamelCase_    ) for x in Path(lowerCamelCase_    ).open().readlines()]


	def _UpperCamelCase	(						self		: Tuple			,						lowerCAmelCase__		: Any    )    ->      List[Any]:
			UpperCAmelCase					      =  torch.stack([x["input_ids"] for x in batch]    )
			UpperCAmelCase					      =  torch.stack([x["attention_mask"] for x in batch]    )
			UpperCAmelCase					      =  torch.stack([x["decoder_input_ids"] for x in batch]    )
			UpperCAmelCase					      =  (
			    self.tokenizer.generator.pad_token_id
			    if isinstance(self.tokenizer			,						lowerCamelCase_    )
			    else self.tokenizer.pad_token_id
			)
			UpperCAmelCase					      =  (
			    self.tokenizer.question_encoder.pad_token_id
			    if isinstance(self.tokenizer			,						lowerCamelCase_    )
			    else self.tokenizer.pad_token_id
			)
			UpperCAmelCase					      =  trim_batch(lowerCamelCase_			,						lowerCamelCase_    )
			UpperCAmelCase					      =  trim_batch(lowerCamelCase_			,						lowerCamelCase_			,						attention_mask=lowerCamelCase_    )
			UpperCAmelCase					      =  {
			    """input_ids""": source_ids,
			    """attention_mask""": source_mask,
			    """decoder_input_ids""": y,
			}
			return batch

lowerCAmelCase__       = getLogger(__name__)
def      _lowerCAmelCase(	__A			):
		return list(itertools.chain.from_iterable(lowerCamelCase_			)			)
def      _lowerCAmelCase(	__A			):
		UpperCAmelCase					      =  get_git_info()
		save_json(lowerCamelCase_   ,       os.path.join(lowerCamelCase_   ,       "git_log.json"			)			)
def      _lowerCAmelCase(	__A   ,       __A   ,       __A=4   ,       **__A			):



		with open(lowerCamelCase_   ,       "w"			) as f:
				json.dump(lowerCamelCase_   ,       lowerCamelCase_   ,       indent=lowerCamelCase_   ,       **lowerCamelCase_			)
def      _lowerCAmelCase(	__A			):



		with open(lowerCamelCase_			) as f:
				return json.load(lowerCamelCase_			)
def      _lowerCAmelCase(	):
		UpperCAmelCase					      =  git.Repo(search_parent_directories=lowerCamelCase_			)
		UpperCAmelCase					      =  {
		    """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      _lowerCAmelCase(	__A   ,       __A			):
		return list(map(lowerCamelCase_   ,       lowerCamelCase_			)			)
def      _lowerCAmelCase(	__A   ,       __A			):



		with open(lowerCamelCase_   ,       "wb"			) as f:
				return pickle.dump(lowerCamelCase_   ,       lowerCamelCase_			)
def      _lowerCAmelCase(	__A			):



		def remove_articles(__A			):
				return re.sub(r"\b(a|an|the)\b"   ,       " "   ,       lowerCamelCase_			)

		def white_space_fix(__A			):
				return " ".join(text.split()			)

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

		def lower(__A			):
				return text.lower()

		return white_space_fix(remove_articles(remove_punc(lower(lowerCamelCase_			)			)			)			)
def      _lowerCAmelCase(	__A   ,       __A			):
		UpperCAmelCase					      =  normalize_answer(lowerCamelCase_			).split()
		UpperCAmelCase					      =  normalize_answer(lowerCamelCase_			).split()
		UpperCAmelCase					      =  Counter(lowerCamelCase_			) & Counter(lowerCamelCase_			)
		UpperCAmelCase					      =  sum(common.values()			)
		if num_same == 0:
				return 0
		UpperCAmelCase					      =  1.0 * num_same / len(lowerCamelCase_			)
		UpperCAmelCase					      =  1.0 * num_same / len(lowerCamelCase_			)
		UpperCAmelCase					      =  (2 * precision * recall) / (precision + recall)
		return fa
def      _lowerCAmelCase(	__A   ,       __A			):
		return normalize_answer(lowerCamelCase_			) == normalize_answer(lowerCamelCase_			)
def      _lowerCAmelCase(	__A   ,       __A			):
		assert len(lowerCamelCase_			) == len(lowerCamelCase_			)
		UpperCAmelCase					      =  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      _lowerCAmelCase(	__A			):
		return model_prefix.startswith("rag"			)





def      _lowerCAmelCase(	__A   ,       __A   ,       __A			):
		UpperCAmelCase					      =  {p: p for p in extra_params}
		# T5 models don't have `dropout` param, they have `dropout_rate` instead
		UpperCAmelCase					      =  """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
						UpperCAmelCase					      =  p if hasattr(lowerCamelCase_   ,       lowerCamelCase_			) else equivalent_param[p]
						setattr(lowerCamelCase_   ,       lowerCamelCase_   ,       getattr(lowerCamelCase_   ,       lowerCamelCase_			)			)
						delattr(lowerCamelCase_   ,       lowerCamelCase_			)
		return hparams, config






import glob
import os
import random
from string import ascii_lowercase, digits

import cva
lowerCAmelCase__       = ""
lowerCAmelCase__       = ""
lowerCAmelCase__       = ""
lowerCAmelCase__       = 1  # (0 is vertical, 1 is horizontal)
def      _lowerCAmelCase(	):
  UpperCAmelCase      ,	UpperCAmelCase					      =  get_dataset(__A   ,       __A			)
  print("Processing..."			)
  UpperCAmelCase      ,	UpperCAmelCase      ,	UpperCAmelCase					      =  update_image_and_anno(__A   ,       __A   ,       __A			)

  for index, image in enumerate(__A			):
    # Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
    UpperCAmelCase					      =  random_chars(32			)
    UpperCAmelCase					      =  paths[index].split(os.sep			)[-1].rsplit("."   ,       1			)[0]
    UpperCAmelCase					      =  F"{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}"
    cva.imwrite(F"/{file_root}.jpg"   ,       __A   ,       [cva.IMWRITE_JPEG_QUALITY, 85]			)
    print(F"Success {index+1}/{len(__A			)} with {file_name}"			)
    UpperCAmelCase					      =  []
    for anno in new_annos[index]:
      UpperCAmelCase					      =  F"{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}"
      annos_list.append(__A			)
    with open(F"/{file_root}.txt"   ,       "w"			) as outfile:
      outfile.write("\n".join(line for line in annos_list			)			)
def      _lowerCAmelCase(	__A   ,       __A			):
  UpperCAmelCase					      =  []
  UpperCAmelCase					      =  []
  for label_file in glob.glob(os.path.join(__A   ,       "*.txt"			)			):
    UpperCAmelCase					      =  label_file.split(os.sep			)[-1].rsplit("."   ,       1			)[0]
    with open(__A			) as in_file:
      UpperCAmelCase					      =  in_file.readlines()
    UpperCAmelCase					      =  os.path.join(__A   ,       F"{label_name}.jpg"			)

    UpperCAmelCase					      =  []
    for obj_list in obj_lists:
      UpperCAmelCase					      =  obj_list.rstrip("\n"			).split(" "			)
      boxes.append(
          [
              int(obj[0]			),
              float(obj[1]			),
              float(obj[2]			),
              float(obj[3]			),
              float(obj[4]			),
          ]			)
    if not boxes:
      continue
    img_paths.append(__A			)
    labels.append(__A			)
  return img_paths, labels
def      _lowerCAmelCase(	__A   ,       __A   ,       __A = 1			):
  UpperCAmelCase					      =  []
  UpperCAmelCase					      =  []
  UpperCAmelCase					      =  []
  for idx in range(len(__A			)			):
    UpperCAmelCase					      =  []
    UpperCAmelCase					      =  img_list[idx]
    path_list.append(__A			)
    UpperCAmelCase					      =  anno_list[idx]
    UpperCAmelCase					      =  cva.imread(__A			)
    if flip_type == 1:
      UpperCAmelCase					      =  cva.flip(__A   ,       __A			)
      for bbox in img_annos:
        UpperCAmelCase					      =  1 - bbox[1]
        new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]			)
    elif flip_type == 0:
      UpperCAmelCase					      =  cva.flip(__A   ,       __A			)
      for bbox in img_annos:
        UpperCAmelCase					      =  1 - bbox[2]
        new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]			)
    new_annos_lists.append(__A			)
    new_imgs_list.append(__A			)
  return new_imgs_list, new_annos_lists, path_list
def      _lowerCAmelCase(	__A = 32			):
  assert number_char > 1, "The number of character should greater than 1"
  UpperCAmelCase					      =  ascii_lowercase + digits
  return "".join(random.choice(__A			) for _ in range(__A			)			)


if __name__ == "__main__":
      main()
      print("DONE ✅")



