



"""simple docstring"""

import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class SCREAMING_SNAKE_CASE__					(		__snake_case     ,					unittest.TestCase      ):
						_lowerCAmelCase							=					MgpstrTokenizer
						_lowerCAmelCase							=					False
						_lowerCAmelCase							=					{}
						_lowerCAmelCase							=					False



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													super().setUp()

													# fmt: off
													__a		:		int									=       ["""[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
													__a		:		List[Any]									=       dict(zip(_lowercase						,     range(len(_lowercase							)							)							)							)

													__a		:		Optional[Any]									=       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(_lowercase							) + """\n"""							)



						def     lowerCAmelCase__(self						,     **_lowercase							):





													'''simple docstring'''

													return MgpstrTokenizer.from_pretrained(self.tmpdirname						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													__a		:		str									=       """tester"""
													__a		:		int									=       """tester"""
													return input_text, output_text



						@unittest.skip("""MGP-STR always lower cases letters."""							)
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													pass



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Optional[int]									=       self.get_tokenizers(do_lower_case=_lowercase							)
													for tokenizer in tokenizers:
																				with self.subTest(F'''{tokenizer.__class__.__name__}'''							):
																											__a		:		Any									=       """[SPECIAL_TOKEN]"""

																											tokenizer.add_special_tokens({"""cls_token""": special_token}							)
																											__a		:		str									=       tokenizer.encode([special_token]						,     add_special_tokens=_lowercase							)
																											self.assertEqual(len(_lowercase							)						,     1							)

																											__a		:		List[Any]									=       tokenizer.decode(_lowercase						,     skip_special_tokens=_lowercase							)
																											self.assertTrue(special_token not in decoded							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Union[str, Any]									=       self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(F'''{tokenizer.__class__.__name__}'''							):
																											__a							,     __a		:		str									=       self.get_input_output_texts(_lowercase							)

																											__a		:		str									=       tokenizer.tokenize(_lowercase							)
																											__a		:		Dict									=       tokenizer.convert_tokens_to_ids(_lowercase							)
																											__a		:		List[Any]									=       tokenizer.encode(_lowercase						,     add_special_tokens=_lowercase							)
																											self.assertListEqual(_lowercase						,     _lowercase							)

																											__a		:		Optional[int]									=       tokenizer.convert_ids_to_tokens(_lowercase							)
																											self.assertNotEqual(len(_lowercase							)						,     0							)
																											__a		:		str									=       tokenizer.decode(_lowercase							)
																											self.assertIsInstance(_lowercase						,     _lowercase							)

																											self.assertEqual(text_a.replace(""" """						,     """"""							)						,     _lowercase							)



						@unittest.skip("""MGP-STR tokenizer only handles one sequence."""							)
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													pass





						@unittest.skip("""inputs cannot be pretokenized in MgpstrTokenizer"""							)
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													pass






"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase__			   =  {
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__			   =  ["LlamaTokenizer"]

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__			   =  ["LlamaTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__			   =  [
	    "LlamaForCausalLM",
	    "LlamaModel",
	    "LlamaPreTrainedModel",
	    "LlamaForSequenceClassification",
	]


if TYPE_CHECKING:
	from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama import LlamaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama_fast import LlamaTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
	import sys

	lowercase__			   =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

