
from typing import TYPE_CHECKING

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


__A							={
    '''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FunnelConfig'''],
    '''convert_funnel_original_tf_checkpoint_to_pytorch''': [],
    '''tokenization_funnel''': ['''FunnelTokenizer'''],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A							=['''FunnelTokenizerFast''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A							=[
			    '''FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''FunnelBaseModel''',
			    '''FunnelForMaskedLM''',
			    '''FunnelForMultipleChoice''',
			    '''FunnelForPreTraining''',
			    '''FunnelForQuestionAnswering''',
			    '''FunnelForSequenceClassification''',
			    '''FunnelForTokenClassification''',
			    '''FunnelModel''',
			    '''FunnelPreTrainedModel''',
			    '''load_tf_weights_in_funnel''',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A							=[
			    '''TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''TFFunnelBaseModel''',
			    '''TFFunnelForMaskedLM''',
			    '''TFFunnelForMultipleChoice''',
			    '''TFFunnelForPreTraining''',
			    '''TFFunnelForQuestionAnswering''',
			    '''TFFunnelForSequenceClassification''',
			    '''TFFunnelForTokenClassification''',
			    '''TFFunnelModel''',
			    '''TFFunnelPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig
			from .tokenization_funnel import FunnelTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_funnel_fast import FunnelTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_funnel import (
						    FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    FunnelBaseModel,
						    FunnelForMaskedLM,
						    FunnelForMultipleChoice,
						    FunnelForPreTraining,
						    FunnelForQuestionAnswering,
						    FunnelForSequenceClassification,
						    FunnelForTokenClassification,
						    FunnelModel,
						    FunnelPreTrainedModel,
						    load_tf_weights_in_funnel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_funnel import (
						    TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFFunnelBaseModel,
						    TFFunnelForMaskedLM,
						    TFFunnelForMultipleChoice,
						    TFFunnelForPreTraining,
						    TFFunnelForQuestionAnswering,
						    TFFunnelForSequenceClassification,
						    TFFunnelForTokenClassification,
						    TFFunnelModel,
						    TFFunnelPreTrainedModel,
						)

else:
			import sys

			__A							=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__A							=get_tests_dir('''fixtures/spiece.model''')




@require_sentencepiece
@require_tokenizers
class        _SCREAMING_SNAKE_CASE	( snake_case_     ,			unittest.TestCase		):
	lowerCAmelCase__   =					AlbertTokenizer
	lowerCAmelCase__   =					AlbertTokenizerFast
	lowerCAmelCase__   =					True
	lowerCAmelCase__   =					True
	lowerCAmelCase__   =					True



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Any:
					super().setUp()

					# We have a SentencePiece fixture for testing
					lowerCamelCase_         =     AlbertTokenizer(lowercase					)
					tokenizer.save_pretrained(self.tmpdirname					)



	def        SCREAMING_SNAKE_CASE_(       self		,    lowercase					)							->			str:
					lowerCamelCase_         =     "this is a test"
					lowerCamelCase_         =     "this is a test"
					return input_text, output_text



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Dict:
					lowerCamelCase_         =     "<pad>"
					lowerCamelCase_         =     0

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



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Any:
					lowerCamelCase_         =     list(self.get_tokenizer().get_vocab().keys()					)

					self.assertEqual(vocab_keys[0]		,    "<pad>"					)
					self.assertEqual(vocab_keys[1]		,    "<unk>"					)
					self.assertEqual(vocab_keys[-1]		,    "▁eloquent"					)
					self.assertEqual(len(lowercase					)		,    30000					)



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Union[str, Any]:
					self.assertEqual(self.get_tokenizer().vocab_size		,    30000					)



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Union[str, Any]:
					if not self.test_rust_tokenizer:
									return

					lowerCamelCase_         =     self.get_tokenizer()
					lowerCamelCase_         =     self.get_rust_tokenizer()

					lowerCamelCase_         =     "I was born in 92000, and this is falsé."

					lowerCamelCase_         =     tokenizer.tokenize(lowercase					)
					lowerCamelCase_         =     rust_tokenizer.tokenize(lowercase					)
					self.assertListEqual(lowercase		,    lowercase					)

					lowerCamelCase_         =     tokenizer.encode(lowercase		,    add_special_tokens=lowercase					)
					lowerCamelCase_         =     rust_tokenizer.encode(lowercase		,    add_special_tokens=lowercase					)
					self.assertListEqual(lowercase		,    lowercase					)

					lowerCamelCase_         =     self.get_rust_tokenizer()
					lowerCamelCase_         =     tokenizer.encode(lowercase					)
					lowerCamelCase_         =     rust_tokenizer.encode(lowercase					)
					self.assertListEqual(lowercase		,    lowercase					)



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Optional[Any]:
					lowerCamelCase_         =     AlbertTokenizer(lowercase		,    keep_accents=lowercase					)

					lowerCamelCase_         =     tokenizer.tokenize("This is a test"					)
					self.assertListEqual(lowercase		,    ["▁this", "▁is", "▁a", "▁test"]					)

					self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase					)		,    [48, 25, 21, 1289]					)

					lowerCamelCase_         =     tokenizer.tokenize("I was born in 92000, and this is falsé."					)
					self.assertListEqual(
					    lowercase		,    ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]					)
					lowerCamelCase_         =     tokenizer.convert_tokens_to_ids(lowercase					)
					self.assertListEqual(lowercase		,    [31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]					)

					lowerCamelCase_         =     tokenizer.convert_ids_to_tokens(lowercase					)
					self.assertListEqual(
					    lowercase		,    ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."]		,    )



	def        SCREAMING_SNAKE_CASE_(       self					)							->			Any:
					lowerCamelCase_         =     AlbertTokenizer(lowercase					)

					lowerCamelCase_         =     tokenizer.encode("sequence builders"					)
					lowerCamelCase_         =     tokenizer.encode("multi-sequence build"					)

					lowerCamelCase_         =     tokenizer.build_inputs_with_special_tokens(lowercase					)
					lowerCamelCase_         =     tokenizer.build_inputs_with_special_tokens(lowercase		,    lowercase					)

					assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
					assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
					    tokenizer.sep_token_id
					]



	@slow
	def        SCREAMING_SNAKE_CASE_(       self					)							->			Optional[Any]:
					# fmt: off
					lowerCamelCase_         =     {"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, 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, 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, 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, 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], [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, 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]], "input_ids": [[2, 21970, 13, 5, 6092, 167, 28, 7103, 2153, 673, 8, 7028, 12051, 18, 17, 7103, 2153, 673, 8, 3515, 18684, 8, 4461, 6, 1927, 297, 8, 12060, 2607, 18, 13, 5, 4461, 15, 10538, 38, 8, 135, 15, 822, 58, 15, 993, 10363, 15, 1460, 8005, 4461, 15, 993, 255, 2328, 9, 9, 9, 6, 26, 1112, 816, 3260, 13, 5, 103, 2377, 6, 17, 1112, 816, 2782, 13, 5, 103, 10641, 6, 29, 84, 2512, 2430, 782, 18684, 2761, 19, 808, 2430, 2556, 17, 855, 1480, 9477, 4091, 128, 11712, 15, 7103, 2153, 673, 17, 24883, 9990, 9, 3], [2, 11502, 25, 1006, 20, 782, 8, 11809, 855, 1732, 19393, 18667, 37, 367, 21018, 69, 1854, 34, 11860, 19124, 27, 156, 225, 17, 193, 4141, 19, 65, 9124, 9, 3, 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], [2, 14, 2231, 886, 2385, 17659, 84, 14, 16792, 1952, 9, 3, 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]], "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, 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, 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]]}  # noqa: E501
					# fmt: on

					self.tokenizer_integration_test_util(
					    expected_encoding=lowercase		,    model_name="albert-base-v2"		,    revision="6b6560eaf5ff2e250b00c50f380c5389a9c2d82e"		,    )


