


import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
     import torch


if is_vision_available():
     from PIL import Image

     from transformers import MgpstrProcessor, ViTImageProcessor





@require_torch
@require_vision
class   snake_case					(					unittest.TestCase    ):





  """simple docstring"""




  _lowerCamelCase						=						ViTImageProcessor if is_vision_available() else None






  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   return self.image_processor_tester.prepare_image_processor_dict()






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						(3, 32, 128)
   lowerCamelCase_  				=						tempfile.mkdtemp()

   # fmt: off
   lowerCamelCase_  				=						['''[GO]''', '''[s]''', '''0''', '''1''', '''2''', '''3''', '''4''', '''5''', '''6''', '''7''', '''8''', '''9''', '''a''', '''b''', '''c''', '''d''', '''e''', '''f''', '''g''', '''h''', '''i''', '''j''', '''k''', '''l''', '''m''', '''n''', '''o''', '''p''', '''q''', '''r''', '''s''', '''t''', '''u''', '''v''', '''w''', '''x''', '''y''', '''z''']
   # fmt: on
   lowerCamelCase_  				=						dict(zip(UpperCAmelCase__    ,						range(len(UpperCAmelCase__  )  )  )  )

   lowerCamelCase_  				=						os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["vocab_file"]  )
   with open(self.vocab_file    ,						"w"    ,						encoding="utf-8"  ) as fp:
    fp.write(json.dumps(UpperCAmelCase__  ) + "\n"  )

   lowerCamelCase_  				=						{
       '''do_normalize''': False,
       '''do_resize''': True,
       '''image_processor_type''': '''ViTImageProcessor''',
       '''resample''': 3,
       '''size''': {'''height''': 32, '''width''': 128},
   }
   lowerCamelCase_  				=						os.path.join(self.tmpdirname    ,						UpperCAmelCase__  )
   with open(self.image_processor_file    ,						"w"    ,						encoding="utf-8"  ) as fp:
    json.dump(UpperCAmelCase__    ,						UpperCAmelCase__  )






  def 						snake_case	(					self    ,						**UpperCamelCase  ):







   """simple docstring"""
   return MgpstrTokenizer.from_pretrained(self.tmpdirname    ,						**UpperCAmelCase__  )






  def 						snake_case	(					self    ,						**UpperCamelCase  ):







   """simple docstring"""
   return ViTImageProcessor.from_pretrained(self.tmpdirname    ,						**UpperCAmelCase__  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   shutil.rmtree(self.tmpdirname  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						np.random.randint(255    ,						size=(3, 30, 400)    ,						dtype=np.uinta  )

   lowerCamelCase_  				=						Image.fromarray(np.moveaxis(UpperCAmelCase__    ,						0    ,						-1  )  )

   return image_input






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_tokenizer()
   lowerCamelCase_  				=						self.get_image_processor()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )
   processor.save_pretrained(self.tmpdirname  )
   lowerCamelCase_  				=						MgpstrProcessor.from_pretrained(self.tmpdirname    ,						use_fast=UpperCAmelCase__  )

   self.assertEqual(processor.char_tokenizer.get_vocab()    ,						tokenizer.get_vocab()  )
   self.assertIsInstance(processor.char_tokenizer    ,						UpperCAmelCase__  )

   self.assertEqual(processor.image_processor.to_json_string()    ,						image_processor.to_json_string()  )
   self.assertIsInstance(processor.image_processor    ,						UpperCAmelCase__  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_tokenizer()
   lowerCamelCase_  				=						self.get_image_processor()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )
   processor.save_pretrained(self.tmpdirname  )

   lowerCamelCase_  				=						self.get_tokenizer(bos_token="(BOS)"    ,						eos_token="(EOS)"  )
   lowerCamelCase_  				=						self.get_image_processor(do_normalize=UpperCAmelCase__    ,						padding_value=1.0  )

   lowerCamelCase_  				=						MgpstrProcessor.from_pretrained(
       self.tmpdirname    ,						bos_token="(BOS)"    ,						eos_token="(EOS)"    ,						do_normalize=UpperCAmelCase__    ,						padding_value=1.0  )

   self.assertEqual(processor.char_tokenizer.get_vocab()    ,						tokenizer_add_kwargs.get_vocab()  )
   self.assertIsInstance(processor.char_tokenizer    ,						UpperCAmelCase__  )

   self.assertEqual(processor.image_processor.to_json_string()    ,						image_processor_add_kwargs.to_json_string()  )
   self.assertIsInstance(processor.image_processor    ,						UpperCAmelCase__  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_image_processor()
   lowerCamelCase_  				=						self.get_tokenizer()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )

   lowerCamelCase_  				=						self.prepare_image_inputs()

   lowerCamelCase_  				=						image_processor(UpperCAmelCase__    ,						return_tensors="np"  )
   lowerCamelCase_  				=						processor(images=UpperCAmelCase__    ,						return_tensors="np"  )

   for key in input_image_proc.keys():
    self.assertAlmostEqual(input_image_proc[key].sum()    ,						input_processor[key].sum()    ,						delta=1e-2  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_image_processor()
   lowerCamelCase_  				=						self.get_tokenizer()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )

   lowerCamelCase_  				=						'''test'''

   lowerCamelCase_  				=						processor(text=UpperCAmelCase__  )

   lowerCamelCase_  				=						tokenizer(UpperCAmelCase__  )
   for key in encoded_tok.keys():
    self.assertListEqual(encoded_tok[key]    ,						encoded_processor[key]  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_image_processor()
   lowerCamelCase_  				=						self.get_tokenizer()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )

   lowerCamelCase_  				=						'''test'''
   lowerCamelCase_  				=						self.prepare_image_inputs()

   lowerCamelCase_  				=						processor(text=UpperCAmelCase__    ,						images=UpperCAmelCase__  )

   self.assertListEqual(list(inputs.keys()  )    ,						["pixel_values", "labels"]  )

   # test if it raises when no input is passed
   with pytest.raises(UpperCAmelCase__  ):
    processor()






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_image_processor()
   lowerCamelCase_  				=						self.get_tokenizer()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )

   lowerCamelCase_  				=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

   lowerCamelCase_  				=						processor.char_decode(UpperCAmelCase__  )
   lowerCamelCase_  				=						tokenizer.batch_decode(UpperCAmelCase__  )
   lowerCamelCase_  				=						[seq.replace(" "    ,						""  ) for seq in decoded_tok]

   self.assertListEqual(UpperCAmelCase__    ,						UpperCAmelCase__  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_image_processor()
   lowerCamelCase_  				=						self.get_tokenizer()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )

   lowerCamelCase_  				=						None
   lowerCamelCase_  				=						self.prepare_image_inputs()

   lowerCamelCase_  				=						processor(text=UpperCAmelCase__    ,						images=UpperCAmelCase__  )

   self.assertListEqual(list(inputs.keys()  )    ,						processor.model_input_names  )







  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_image_processor()
   lowerCamelCase_  				=						self.get_tokenizer()

   lowerCamelCase_  				=						MgpstrProcessor(tokenizer=UpperCAmelCase__    ,						image_processor=UpperCAmelCase__  )

   lowerCamelCase_  				=						torch.randn(1    ,						27    ,						38  )
   lowerCamelCase_  				=						torch.randn(1    ,						27    ,						5_0257  )
   lowerCamelCase_  				=						torch.randn(1    ,						27    ,						3_0522  )

   lowerCamelCase_  				=						processor.batch_decode([char_input, bpe_input, wp_input]  )

   self.assertListEqual(list(results.keys()  )    ,						["generated_text", "scores", "char_preds", "bpe_preds", "wp_preds"]  )







'''simple docstring'''

# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


a_						:       Dict      			=				get_logger(__name__)





class   snake_case					:





  """simple docstring"""




  _lowerCamelCase						=						"dummy_data"
  _lowerCamelCase						=						"datasets"
  _lowerCamelCase						=						False






  def __init__(					self    ,						UpperCamelCase    ,						UpperCamelCase    ,						UpperCamelCase    ,						UpperCamelCase = None    ,						UpperCamelCase = False    ,						UpperCamelCase = True    ,						UpperCamelCase = None    ,						):







   """simple docstring"""
   lowerCamelCase_  				=						0
   lowerCamelCase_  				=						dataset_name
   lowerCamelCase_  				=						cache_dir
   lowerCamelCase_  				=						use_local_dummy_data
   lowerCamelCase_  				=						config
   # download_callbacks take a single url as input
   lowerCamelCase_  				=						download_callbacks or []
   # if False, it doesn't load existing files and it returns the paths of the dummy files relative
   # to the dummy_data zip file root
   lowerCamelCase_  				=						load_existing_dummy_data

   # TODO(PVP, QL) might need to make this more general
   lowerCamelCase_  				=						str(UpperCamelCase  )
   # to be downloaded
   lowerCamelCase_  				=						None
   lowerCamelCase_  				=						None






  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   if self._dummy_file is None:
    lowerCamelCase_  				=						self.download_dummy_data()
   return self._dummy_file






  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   if self.config is not None:
    # structure is dummy / config_name / version_name
    return os.path.join("dummy"    ,						self.config.name    ,						self.version_name  )
   # structure is dummy / version_name
   return os.path.join("dummy"    ,						self.version_name  )






  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   return os.path.join(self.dummy_data_folder    ,						"dummy_data.zip"  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						(
       self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
   )

   lowerCamelCase_  				=						cached_path(
       UpperCamelCase    ,						cache_dir=self.cache_dir    ,						extract_compressed_file=UpperCamelCase    ,						force_extract=UpperCamelCase  )

   return os.path.join(UpperCamelCase    ,						self.dummy_file_name  )






  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   return os.path.join(self.datasets_scripts_dir    ,						self.dataset_name    ,						self.dummy_zip_file  )






  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   if self._bucket_url is None:
    lowerCamelCase_  				=						hf_github_url(self.dataset_name    ,						self.dummy_zip_file.replace(os.sep    ,						"/"  )  )
   return self._bucket_url






  @property
  def 						snake_case	(					self  ):







   """simple docstring"""
   # return full path if its a dir
   if os.path.isdir(self.dummy_file  ):
    return self.dummy_file
   # else cut off path to file -> example `xsum`.
   return "/".join(self.dummy_file.replace(os.sep    ,						"/"  ).split("/"  )[:-1]  )






  def 						snake_case	(					self    ,						UpperCamelCase    ,						*UpperCamelCase  ):







   """simple docstring"""
   if self.load_existing_dummy_data:
    # dummy data is downloaded and tested
    lowerCamelCase_  				=						self.dummy_file
   else:
    # dummy data cannot be downloaded and only the path to dummy file is returned
    lowerCamelCase_  				=						self.dummy_file_name

   # special case when data_url is a dict
   if isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    return self.create_dummy_data_dict(UpperCamelCase    ,						UpperCamelCase  )
   elif isinstance(UpperCamelCase    ,						(list, tuple)  ):
    return self.create_dummy_data_list(UpperCamelCase    ,						UpperCamelCase  )
   else:
    return self.create_dummy_data_single(UpperCamelCase    ,						UpperCamelCase  )






  def 						snake_case	(					self    ,						UpperCamelCase    ,						*UpperCamelCase  ):







   """simple docstring"""
   return self.download_and_extract(UpperCamelCase  )






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase  ):







   """simple docstring"""
   return self.download_and_extract(UpperCamelCase  )






  def 						snake_case	(					self    ,						UpperCamelCase    ,						*UpperCamelCase    ,						**UpperCamelCase  ):







   """simple docstring"""
   return path






  def 						snake_case	(					self  ):







   """simple docstring"""
   return {}






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase  ):







   """simple docstring"""
   lowerCamelCase_  				=						{}
   for key, single_urls in data_url.items():
    for download_callback in self.download_callbacks:
     if isinstance(UpperCamelCase    ,						UpperCamelCase  ):
      for single_url in single_urls:
       download_callback(UpperCamelCase  )
     else:
      lowerCamelCase_  				=						single_urls
      download_callback(UpperCamelCase  )
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
    if isinstance(UpperCamelCase    ,						UpperCamelCase  ):
     lowerCamelCase_  				=						[os.path.join(UpperCamelCase    ,						urllib.parse.quote_plus(Path(UpperCamelCase  ).name  )  ) for x in single_urls]
    else:
     lowerCamelCase_  				=						single_urls
     lowerCamelCase_  				=						os.path.join(UpperCamelCase    ,						urllib.parse.quote_plus(Path(UpperCamelCase  ).name  )  )
    lowerCamelCase_  				=						value

   # make sure that values are unique
   if all(isinstance(UpperCamelCase    ,						UpperCamelCase  ) for i in dummy_data_dict.values()  ) and len(set(dummy_data_dict.values()  )  ) < len(
       dummy_data_dict.values()  ):
    # append key to value to make its name unique
    lowerCamelCase_  				=						{key: value + key for key, value in dummy_data_dict.items()}

   return dummy_data_dict






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase  ):







   """simple docstring"""
   lowerCamelCase_  				=						[]
   # trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
   lowerCamelCase_  				=						all(bool(re.findall("[0-9]{3,}-of-[0-9]{3,}"    ,						UpperCamelCase  )  ) for url in data_url  )
   lowerCamelCase_  				=						all(
       url.startswith("https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed"  ) for url in data_url  )
   if data_url and (is_tf_records or is_pubmed_records):
    lowerCamelCase_  				=						[data_url[0]] * len(UpperCamelCase  )
   for single_url in data_url:
    for download_callback in self.download_callbacks:
     download_callback(UpperCamelCase  )
    # we force the name of each key to be the last file / folder name of the url path
    # if the url has arguments, we need to encode them with urllib.parse.quote_plus
    lowerCamelCase_  				=						os.path.join(UpperCamelCase    ,						urllib.parse.quote_plus(single_url.split("/"  )[-1]  )  )
    dummy_data_list.append(UpperCamelCase  )
   return dummy_data_list






  def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase  ):







   """simple docstring"""
   for download_callback in self.download_callbacks:
    download_callback(UpperCamelCase  )
   # we force the name of each key to be the last file / folder name of the url path
   # if the url has arguments, we need to encode them with urllib.parse.quote_plus
   lowerCamelCase_  				=						os.path.join(UpperCamelCase    ,						urllib.parse.quote_plus(data_url.split("/"  )[-1]  )  )
   if os.path.exists(UpperCamelCase  ) or not self.load_existing_dummy_data:
    return value
   else:
    # Backward compatibility, maybe deprecate at one point.
    # For many datasets with single url calls to dl_manager.download_and_extract,
    # the dummy_data.zip file is actually the zipped downloaded file
    # while now we expected the dummy_data.zip file to be a directory containing
    # the downloaded file.
    return path_to_dummy_data






  def 						snake_case	(					self  ):







   """simple docstring"""
   pass






  def 						snake_case	(					self  ):







   """simple docstring"""
   pass






  def 						snake_case	(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   def _iter_archive_members(UpperCamelCase  ):
    # this preserves the order of the members inside the ZIP archive
    lowerCamelCase_  				=						Path(self.dummy_file  ).parent
    lowerCamelCase_  				=						path.relative_to(UpperCamelCase  )
    with ZipFile(self.local_path_to_dummy_data  ) as zip_file:
     lowerCamelCase_  				=						zip_file.namelist()
    for member in members:
     if member.startswith(relative_path.as_posix()  ):
      yield dummy_parent_path.joinpath(UpperCamelCase  )

   lowerCamelCase_  				=						Path(UpperCamelCase  )
   lowerCamelCase_  				=						_iter_archive_members(UpperCamelCase  ) if self.use_local_dummy_data else path.rglob("*"  )
   for file_path in file_paths:
    if file_path.is_file() and not file_path.name.startswith((".", "__")  ):
     yield file_path.relative_to(UpperCamelCase  ).as_posix(), file_path.open("rb"  )







  def 						snake_case	(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   if not isinstance(UpperCamelCase    ,						UpperCamelCase  ):
    lowerCamelCase_  				=						[paths]
   for path in paths:
    if os.path.isfile(UpperCamelCase  ):
     if os.path.basename(UpperCamelCase  ).startswith((".", "__")  ):
      return
     yield path
    else:
     for dirpath, dirnames, filenames in os.walk(UpperCamelCase  ):
      if os.path.basename(UpperCamelCase  ).startswith((".", "__")  ):
       continue
      dirnames.sort()
      for filename in sorted(UpperCamelCase  ):
       if filename.startswith((".", "__")  ):
        continue
       yield os.path.join(UpperCamelCase    ,						UpperCamelCase  )



