



import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_snake_case		=  "src/diffusers"

# Matches is_xxx_available()
_snake_case		=  re.compile(R"is\_([a-z_]*)_available\(\)")
# Matches from xxx import bla
_snake_case		=  re.compile(R"\s+from\s+\S*\s+import\s+([^\(\s].*)\n")


_snake_case		=  "\n{0} = None\n"

_snake_case		=  "\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n"


_snake_case		=  "\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Tuple    =    _re_backend.findall(_lowerCamelCase  )
							if len(_lowerCamelCase  ) == 0:
														return None

							return "_and_".join(_lowerCamelCase  )






def 				A				(					):





							'''simple docstring'''




							with open(os.path.join(_lowerCamelCase				, "__init__.py"  )				, "r"				, encoding="utf-8"				, newline="\n"  ) as f:
														_lowerCAmelCase     :							int    =    f.readlines()

							# Get to the point we do the actual imports for type checking
							_lowerCAmelCase     :							Dict    =    0
							_lowerCAmelCase     :							Optional[int]    =    {}
							# Go through the end of the file
							while line_index < len(_lowerCamelCase  ):
														# If the line contains is_backend_available, we grab all objects associated with the `else` block
														_lowerCAmelCase     :							str    =    find_backend(lines[line_index]  )
														if backend is not None:
																					while not lines[line_index].startswith("else:"  ):
																												line_index += 1
																					line_index += 1
																					_lowerCAmelCase     :							Tuple    =    []
																					# Until we unindent, add backend objects to the list
																					while line_index < len(_lowerCamelCase  ) and len(lines[line_index]  ) > 1:
																												_lowerCAmelCase     :							List[Any]    =    lines[line_index]
																												_lowerCAmelCase     :							Optional[Any]    =    _re_single_line_import.search(_lowerCamelCase  )
																												if single_line_import_search is not None:
																																			objects.extend(single_line_import_search.groups()[0].split(", "  )  )
																												elif line.startswith(" " * 8  ):
																																			objects.append(line[8:-2]  )
																												line_index += 1

																					if len(_lowerCamelCase  ) > 0:
																												_lowerCAmelCase     :							List[Any]    =    objects
														else:
																					line_index += 1

							return backend_specific_objects






def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							if name.isupper():
														return DUMMY_CONSTANT.format(_lowerCamelCase  )
							elif name.islower():
														return DUMMY_FUNCTION.format(_lowerCamelCase				, _lowerCamelCase  )
							else:
														return DUMMY_CLASS.format(_lowerCamelCase				, _lowerCamelCase  )






def 				A				(					_lowerCamelCase=None  ):





							'''simple docstring'''




							if backend_specific_objects is None:
														_lowerCAmelCase     :							Tuple    =    read_init()
							# For special correspondence backend to module name as used in the function requires_modulename
							_lowerCAmelCase     :							List[Any]    =    {}

							for backend, objects in backend_specific_objects.items():
														_lowerCAmelCase     :							int    =    "[" + ", ".join(F"\"{b}\"" for b in backend.split("_and_"  )  ) + "]"
														_lowerCAmelCase     :							int    =    "# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
														dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
														dummy_file += "\n".join([create_dummy_object(_lowerCamelCase				, _lowerCamelCase  ) for o in objects]  )
														_lowerCAmelCase     :							Dict    =    dummy_file

							return dummy_files






def 				A				(					_lowerCamelCase=False  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Union[str, Any]    =    create_dummy_files()
							# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
							_lowerCAmelCase     :							Union[str, Any]    =    {"torch": "pt"}

							# Locate actual dummy modules and read their content.
							_lowerCAmelCase     :							Optional[int]    =    os.path.join(_lowerCamelCase				, "utils"  )
							_lowerCAmelCase     :							Tuple    =    {
							    backend: os.path.join(_lowerCamelCase				, F"dummy_{short_names.get(_lowerCamelCase				, _lowerCamelCase  )}_objects.py"  )
							    for backend in dummy_files.keys()
							}

							_lowerCAmelCase     :							Tuple    =    {}
							for backend, file_path in dummy_file_paths.items():
														if os.path.isfile(_lowerCamelCase  ):
																					with open(_lowerCamelCase				, "r"				, encoding="utf-8"				, newline="\n"  ) as f:
																												_lowerCAmelCase     :							Dict    =    f.read()
														else:
																					_lowerCAmelCase     :							Any    =    ""

							for backend in dummy_files.keys():
														if dummy_files[backend] != actual_dummies[backend]:
																					if overwrite:
																												print(
																												    F"Updating diffusers.utils.dummy_{short_names.get(_lowerCamelCase				, _lowerCamelCase  )}_objects.py as the main "
																												    "__init__ has new objects."  )
																												with open(dummy_file_paths[backend]				, "w"				, encoding="utf-8"				, newline="\n"  ) as f:
																																			f.write(dummy_files[backend]  )
																					else:
																												raise ValueError(
																												    "The main __init__ has objects that are not present in "
																												    F"diffusers.utils.dummy_{short_names.get(_lowerCamelCase				, _lowerCamelCase  )}_objects.py. Run `make fix-copies` "
																												    "to fix this."  )


if __name__ == "__main__":
						_snake_case		=  argparse.ArgumentParser()
						parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
						_snake_case		=  parser.parse_args()

						check_dummies(args.fix_and_overwrite)






import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase		:				List[Any]       			=		get_tests_dir('fixtures/test_sentencepiece_with_bytefallback.model')




@require_sentencepiece
@require_tokenizers
class     snake_case__							(_UpperCamelCase    ,       unittest.TestCase   ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_       :							Any							 =					GPTSwaTokenizer
				SCREAMING_SNAKE_CASE_       :							int							 =					False
				SCREAMING_SNAKE_CASE_       :							Union[str, Any]							 =					True
				SCREAMING_SNAKE_CASE_       :							Any							 =					False





				def 							__UpperCAmelCase							(      self				:     Tuple							)					->     Any:
							super().setUp()

							# We have a SentencePiece fixture for testing
							a    =			GPTSwaTokenizer(__lowerCamelCase					,      eos_token="<unk>"					,      bos_token="<unk>"					,      pad_token="<unk>"							)

							tokenizer.save_pretrained(self.tmpdirname							)





				def 							__UpperCAmelCase							(      self				:     Union[str, Any]					,      __lowerCamelCase				:     Optional[Any]							)					->     Any:
							a    =			"This is a test"
							a    =			"This is a test"
							return input_text, output_text





				def 							__UpperCAmelCase							(      self				:     List[Any]							)					->     List[str]:
							a    =			"<s>"
							a    =			1

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCamelCase							)					,      __lowerCamelCase							)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCamelCase							)					,      __lowerCamelCase							)





				def 							__UpperCAmelCase							(      self				:     List[Any]							)					->     int:
							a    =			list(self.get_tokenizer().get_vocab().keys()							)

							self.assertEqual(vocab_keys[0]					,      "<unk>"							)
							self.assertEqual(vocab_keys[1]					,      "<s>"							)
							self.assertEqual(vocab_keys[-1]					,      "j"							)
							self.assertEqual(len(__lowerCamelCase							)					,      20_00							)





				def 							__UpperCAmelCase							(      self				:     Optional[int]							)					->     Dict:
							self.assertEqual(self.get_tokenizer().vocab_size					,      20_00							)





				def 							__UpperCAmelCase							(      self				:     Optional[int]							)					->     Union[str, Any]:
							a    =			GPTSwaTokenizer(__lowerCamelCase							)

							a    =			tokenizer.tokenize("This is a test"							)
							self.assertListEqual(__lowerCamelCase					,      ["▁This", "▁is", "▁a", "▁t", "est"]							)

							self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase							)					,      [4_65, 2_87, 2_65, 6_31, 8_42]							)

							a    =			tokenizer.tokenize("I was born in 92000, and this is falsé."							)
							# fmt: off
							self.assertListEqual(
							    __lowerCamelCase					,      ["▁I", "▁was", "▁bor", "n", "▁in", "▁", "<0x39>", "2", "0", "0", "0", ",", "▁and", "▁this", "▁is", "▁f", "al", "s", "<0xC3>", "<0xA9>", "."]					,      )
							# fmt: on

							a    =			tokenizer.convert_tokens_to_ids(__lowerCamelCase							)
							self.assertListEqual(
							    __lowerCamelCase					,      [2_62, 2_72, 15_25, 2_86, 2_71, 2_68, 60, 9_16, 6_33, 6_33, 6_33, 2_59, 2_66, 3_01, 2_87, 3_84, 3_67, 2_63, 1_98, 1_72, 2_60]					,      )

							a    =			tokenizer.convert_ids_to_tokens(__lowerCamelCase							)
							# fmt: off
							self.assertListEqual(
							    __lowerCamelCase					,      ["▁I", "▁was", "▁bor", "n", "▁in", "▁", "<0x39>", "2", "0", "0", "0", ",", "▁and", "▁this", "▁is", "▁f", "al", "s", "<0xC3>", "<0xA9>", "."]							)
							# fmt: on





				def 							__UpperCAmelCase							(      self				:     List[Any]							)					->     str:
							a    =			GPTSwaTokenizer(__lowerCamelCase							)
							a    =			["This is a test", "I was born in 92000, and this is falsé."]
							a    =			[
							    [4_65, 2_87, 2_65, 6_31, 8_42],
							    [2_62, 2_72, 15_25, 2_86, 2_71, 2_68, 60, 9_16, 6_33, 6_33, 6_33, 2_59, 2_66, 3_01, 2_87, 3_84, 3_67, 2_63, 1_98, 1_72, 2_60],
							]

							# Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
							for text, expected_ids in zip(__lowerCamelCase					,      __lowerCamelCase							):
										self.assertListEqual(tokenizer.encode_fast(__lowerCamelCase							)					,      __lowerCamelCase							)

							# Test that decode_fast returns the input text
							for text, token_ids in zip(__lowerCamelCase					,      __lowerCamelCase							):
										self.assertEqual(tokenizer.decode_fast(__lowerCamelCase							)					,      __lowerCamelCase							)





				@slow
				def 							__UpperCAmelCase							(      self				:     Optional[int]							)					->     List[Any]:
							a    =			[
							    "<|python|>def fibonacci(n)\n    if n < 0:\n        print('Incorrect input')",
							    "Hey there, how are you doing this fine day?",
							    "This is a text with a trailing spaces followed by a dot     .",
							    "Häj sväjs lillebrör! =)",
							    "Det är inget fel på Mr. Cool",
							]

							# fmt: off
							a    =			{"input_ids": [[6_34_23, 5, 68_11, 1_49_54, 2_82, 8_16, 38_21, 6_34_66, 6_34_25, 6_34_62, 18, 6_39_78, 6_78, 3_01, 13_20, 6_34_23, 6_34_55, 6_34_58, 18, 6_39_82, 42_46, 39_40, 19_01, 4_77_89, 55_47, 1_89_94], [1_96_30, 11_00, 6_34_46, 13_42, 6_33, 5_44, 44_88, 5_93, 51_02, 24_16, 6_34_95, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [16_52, 4_28, 2_68, 19_36, 5_15, 2_68, 5_85_93, 2_24_13, 91_06, 5_46, 2_68, 3_32_13, 6_39_79, 6_98, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_51_30, 6_34_50, 9_24, 6_34_49, 22_49, 40_62, 15_58, 3_18, 6_35_04, 2_14_98, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_09, 3_77, 28_27, 25_59, 3_32, 65_75, 6_34_43, 2_68_01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "token_type_ids": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}
							# fmt: on
							self.tokenizer_integration_test_util(
							    expected_encoding=__lowerCamelCase					,      model_name="AI-Sweden/gpt-sw3-126m"					,      sequences=__lowerCamelCase					,      )






