



import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 		_lowercase		(							UpperCAmelCase__, unittest.TestCase						):
   _UpperCAmelCase  						=      HerbertTokenizer
   _UpperCAmelCase  						=      HerbertTokenizerFast
   _UpperCAmelCase  						=      True

   def 		A				(   self      :							Any				)							->					List[str]:


    """simple docstring"""






    super().setUp()

    # Use a simpler test file without japanese/chinese characters
    with open(f"""{get_tests_dir()}/fixtures/sample_text_no_unicode.txt"""				, encoding="utf-8"				) as f_data:
     a							=		f_data.read().replace("\n\n"				, "\n"				).strip()

    a							=		[
        "<s>",
        "</s>",
        "l",
        "o",
        "w",
        "e",
        "r",
        "s",
        "t",
        "i",
        "d",
        "n",
        "w</w>",
        "r</w>",
        "t</w>",
        "lo",
        "low",
        "er</w>",
        "low</w>",
        "lowest</w>",
        "newer</w>",
        "wider</w>",
        ",</w>",
        "<unk>",
    ]
    a							=		dict(zip(__lowerCAmelCase				, range(len(__lowerCAmelCase				)				)				)				)
    a							=		["l o 123", "lo w 1456", "e r</w> 1789", ""]

    a							=		os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES["vocab_file"]				)
    a							=		os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES["merges_file"]				)
    with open(self.vocab_file				, "w"				) as fp:
     fp.write(json.dumps(__lowerCAmelCase				)				)
    with open(self.merges_file				, "w"				) as fp:
     fp.write("\n".join(__lowerCAmelCase				)				)

   def 		A				(   self      :							Optional[Any]				, __lowerCAmelCase      :							Union[str, Any]				)							->					int:


    """simple docstring"""






    a							=		"lower newer"
    a							=		"lower newer"
    return input_text, output_text

   def 		A				(   self      :							Tuple				)							->					int:


    """simple docstring"""






    a							=		self.tokenizer_class(vocab_file=self.vocab_file				, merges_file=self.merges_file				)

    a							=		"lower"
    a							=		["low", "er</w>"]
    a							=		tokenizer.tokenize(__lowerCAmelCase				)
    self.assertListEqual(__lowerCAmelCase				, __lowerCAmelCase				)

    a							=		tokens + ["<unk>"]
    a							=		[16, 17, 23]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase				)				, __lowerCAmelCase				)

   def 		A				(   self      :							Optional[Any]				)							->					List[str]:


    """simple docstring"""






    if not self.test_rust_tokenizer:
     return

    a							=		self.get_tokenizer()
    a							=		self.get_rust_tokenizer()

    a							=		"lower,newer"

    a							=		tokenizer.tokenize(__lowerCAmelCase				)
    a							=		rust_tokenizer.tokenize(__lowerCAmelCase				)
    self.assertListEqual(__lowerCAmelCase				, __lowerCAmelCase				)

    a							=		tokenizer.encode(__lowerCAmelCase				, add_special_tokens=__lowerCAmelCase				)
    a							=		rust_tokenizer.encode(__lowerCAmelCase				, add_special_tokens=__lowerCAmelCase				)
    self.assertListEqual(__lowerCAmelCase				, __lowerCAmelCase				)

    a							=		self.get_rust_tokenizer()
    a							=		tokenizer.encode(__lowerCAmelCase				)
    a							=		rust_tokenizer.encode(__lowerCAmelCase				)
    self.assertListEqual(__lowerCAmelCase				, __lowerCAmelCase				)




   @slow
   def 		A				(   self      :							Union[str, Any]				)							->					Union[str, Any]:


    """simple docstring"""






    a							=		self.tokenizer_class.from_pretrained("allegro/herbert-base-cased"				)

    a							=		tokenizer.encode("konstruowanie sekwencji"				, add_special_tokens=__lowerCAmelCase				)
    a							=		tokenizer.encode("konstruowanie wielu sekwencji"				, add_special_tokens=__lowerCAmelCase				)

    a							=		tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase				)
    a							=		tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase				, __lowerCAmelCase				)

    assert encoded_sentence == [0] + text + [2]
    assert encoded_pair == [0] + text + [2] + text_a + [2]




# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from typing import List


def 							__lowercase     (	UpperCAmelCase__		,       UpperCAmelCase__   ):

					"""simple docstring"""






					if name != "training_function" and name != "main":
										raise ValueError(F"""Incorrect function name passed: {name}, choose either 'main' or 'training_function'"""   )
					__lowerCAmelCase,						__lowerCAmelCase       =				[], False
					for line in lines:
										if not found_start and F"""def {name}""" in line:
															__lowerCAmelCase       =				True
															good_lines.append(UpperCAmelCase__   )
															continue
										if found_start:
															if name == "training_function" and "def main" in line:
																				return good_lines
															if name == "main" and "if __name__" in line:
																				return good_lines
															good_lines.append(UpperCAmelCase__   )


def 							__lowercase     (	UpperCAmelCase__   ):

					"""simple docstring"""






					return [line for line in lines if not line.lstrip().startswith('#'   ) and line != "\n"]


def 							__lowercase     (	UpperCAmelCase__		,       UpperCAmelCase__		,       UpperCAmelCase__		,       UpperCAmelCase__ = None   ):

					"""simple docstring"""






					with open(UpperCAmelCase__		,       'r'   ) as f:
										__lowerCAmelCase       =				f.readlines()
					with open(os.path.abspath(os.path.join('examples'		,       'nlp_example.py'   )   )		,       'r'   ) as f:
										__lowerCAmelCase       =				f.readlines()
					with open(UpperCAmelCase__		,       'r'   ) as f:
										__lowerCAmelCase       =				f.readlines()
					if secondary_filename is not None:
										with open(UpperCAmelCase__		,       'r'   ) as f:
															__lowerCAmelCase       =				f.readlines()

    # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
					if parser_only:
										__lowerCAmelCase       =				clean_lines(get_function_contents_by_name(UpperCAmelCase__		,       'main'   )   )
										__lowerCAmelCase       =				clean_lines(get_function_contents_by_name(UpperCAmelCase__		,       'main'   )   )
										__lowerCAmelCase       =				clean_lines(get_function_contents_by_name(UpperCAmelCase__		,       'main'   )   )
										if secondary_filename is not None:
															__lowerCAmelCase       =				clean_lines(get_function_contents_by_name(UpperCAmelCase__		,       'main'   )   )
					else:
										__lowerCAmelCase       =				clean_lines(get_function_contents_by_name(UpperCAmelCase__		,       'training_function'   )   )
										__lowerCAmelCase       =				clean_lines(get_function_contents_by_name(UpperCAmelCase__		,       'training_function'   )   )
										__lowerCAmelCase       =				clean_lines(get_function_contents_by_name(UpperCAmelCase__		,       'training_function'   )   )
										if secondary_filename is not None:
															__lowerCAmelCase       =				clean_lines(
															    get_function_contents_by_name(UpperCAmelCase__		,       'training_function'   )   )

					__lowerCAmelCase       =				'train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n'

					# Specific code in our script that differs from the full version, aka what is new
					__lowerCAmelCase       =				[]
					__lowerCAmelCase       =				[]  # We keep track of the idxs just in case it's a repeated statement
					__lowerCAmelCase       =				iter(UpperCAmelCase__   )
					for i in range(len(UpperCAmelCase__   ) - 1   ):
										if i not in passed_idxs:
															__lowerCAmelCase       =				next(UpperCAmelCase__   )
															if (line not in full_file_func) and (line.lstrip() != _dl_line):
																				if "TESTING_MOCKED_DATALOADERS" not in line:
																									new_feature_code.append(UpperCAmelCase__   )
																									passed_idxs.append(UpperCAmelCase__   )
																				else:
																									# Skip over the `config['num_epochs'] = 2` statement
																									__lowerCAmelCase       =				next(UpperCAmelCase__   )

    # Extract out just the new parts from the full_file_training_func
					__lowerCAmelCase       =				[]
					__lowerCAmelCase       =				[]  # We keep track of the idxs just in case it's a repeated statement
					for i, line in enumerate(UpperCAmelCase__   ):
										if i not in passed_idxs:
															if (line not in full_file_func) and (line.lstrip() != _dl_line):
																				if "TESTING_MOCKED_DATALOADERS" not in line:
																									new_full_example_parts.append(UpperCAmelCase__   )
																									passed_idxs.append(UpperCAmelCase__   )

    # Finally, get the overall diff
					__lowerCAmelCase       =				[line for line in new_feature_code if line not in new_full_example_parts]
					if secondary_filename is not None:
										__lowerCAmelCase       =				[line for line in full_file_contents if line not in secondary_file_func]
										__lowerCAmelCase       =				[line for line in diff_from_example if line not in diff_from_two]

					return diff_from_example






