



import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_lowercase: List[str]      			=		get_tests_dir("fixtures/test_sentencepiece.model")



@require_sentencepiece
@require_tokenizers
class 	_lowercase							(   lowerCAmelCase,      unittest.TestCase	):





	"""simple docstring"""
	__A							=							XGLMTokenizer
	__A							=							XGLMTokenizerFast
	__A							=							True
	__A							=							True




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						super().setUp()

						# We have a SentencePiece fixture for testing
						a					     =   XGLMTokenizer(lowerCamelCase_		,       keep_accents=lowerCamelCase_		)
						tokenizer.save_pretrained(self.tmpdirname		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   "<pad>"
						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		):
						"""simple docstring"""

						a					     =   list(self.get_tokenizer().get_vocab().keys()		)

						self.assertEqual(vocab_keys[0]		,       "<s>"		)
						self.assertEqual(vocab_keys[1]		,       "<pad>"		)
						self.assertEqual(len(lowerCamelCase_		)		,       1008		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						self.assertEqual(self.get_tokenizer().vocab_size		,       1008		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   XGLMTokenizer(lowerCamelCase_		,       keep_accents=lowerCamelCase_		)

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

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(lowerCamelCase_		)		,       [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]		,       )

						a					     =   tokenizer.tokenize("I was born in 92000, and this is falsé."		)
						self.assertListEqual(
						    lowerCamelCase_		,       [
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "9",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "é",
						        ".",
						    ]		,       )
						a					     =   tokenizer.convert_tokens_to_ids(lowerCamelCase_		)
						self.assertListEqual(
						    lowerCamelCase_		,       [
						        value + tokenizer.fairseq_offset
						        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
						    ]		,       )

						a					     =   tokenizer.convert_ids_to_tokens(lowerCamelCase_		)
						self.assertListEqual(
						    lowerCamelCase_		,       [
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "<unk>",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "<unk>",
						        ".",
						    ]		,       )




	@cached_property
	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						return XGLMTokenizer.from_pretrained("facebook/xglm-564M"		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						with tempfile.NamedTemporaryFile() as f:
											shutil.copyfile(lowerCamelCase_		,       f.name		)
											a					     =   XGLMTokenizer(f.name		,       keep_accents=lowerCamelCase_		)
											a					     =   pickle.dumps(lowerCamelCase_		)
						pickle.loads(lowerCamelCase_		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						if not self.test_rust_tokenizer:
											return

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

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

						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      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   "Hello World!"
						a					     =   [2, 31227, 4447, 35]

						self.assertListEqual(lowerCamelCase_		,       self.big_tokenizer.encode(lowerCamelCase_		)		)




	@slow
	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   (
						    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
						    " add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth"
						)
						# fmt: off
						a					     =   [2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 71630, 28085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 13675, 377, 652, 7580, 10341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 202277, 17892, 33, 60, 87, 4, 3234, 157, 61, 2667, 52376, 19, 88, 23, 735]
						# fmt: on

						self.assertListEqual(lowerCamelCase_		,       self.big_tokenizer.encode(lowerCamelCase_		)		)




	@slow
	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   {
						    "input_ids": [[2, 108825, 1163, 15, 88010, 473, 15898, 157, 13672, 1857, 312, 8, 238021, 1163, 53, 13672, 1857, 312, 8, 53283, 182396, 8, 18566, 16, 36733, 4101, 8, 230, 244017, 122553, 7, 15, 132597, 4, 293, 12511, 7610, 4, 3414, 132597, 9, 4, 32361, 362, 4, 734, 28512, 32569, 18, 4, 32361, 26096, 14982, 73, 18715, 21433, 235261, 15, 492, 12427, 16, 53, 18715, 21433, 65454, 15, 23659, 563, 16, 278, 597, 2843, 595, 7931, 182396, 64186, 22, 886, 595, 132981, 53, 25540, 3449, 43982, 39901, 5951, 878, 330, 4, 27694, 80269, 312, 53, 6517, 11780, 611, 20408, 5], [2, 6, 132597, 67, 42897, 33, 592, 8, 163729, 25540, 361, 136997, 109514, 173230, 7, 501, 60, 102913, 196, 5631, 235, 63243, 473, 6, 231757, 74, 5277, 7905, 53, 3095, 37317, 22, 454, 183874, 5], [2, 268, 31298, 46530, 6, 132935, 43831, 7, 597, 32, 24, 3688, 9865, 5]],
						    "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, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
						}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=lowerCamelCase_		,       model_name="facebook/xglm-564M"		,       padding=lowerCamelCase_		,       )





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowercase: Union[str, Any]      			=		{
    "configuration_bridgetower": [
        "BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BridgeTowerConfig",
        "BridgeTowerTextConfig",
        "BridgeTowerVisionConfig",
    ],
    "processing_bridgetower": ["BridgeTowerProcessor"],
}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase: Dict      			=		["BridgeTowerImageProcessor"]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase: int      			=		[
				    "BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "BridgeTowerForContrastiveLearning",
				    "BridgeTowerForImageAndTextRetrieval",
				    "BridgeTowerForMaskedLM",
				    "BridgeTowerModel",
				    "BridgeTowerPreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_bridgetower import (
				    BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    BridgeTowerConfig,
				    BridgeTowerTextConfig,
				    BridgeTowerVisionConfig,
				)
				from .processing_bridgetower import BridgeTowerProcessor

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .image_processing_bridgetower import BridgeTowerImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_bridgetower import (
								    BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BridgeTowerForContrastiveLearning,
								    BridgeTowerForImageAndTextRetrieval,
								    BridgeTowerForMaskedLM,
								    BridgeTowerModel,
								    BridgeTowerPreTrainedModel,
								)


else:
				import sys

				_lowercase: Optional[Any]      			=		_LazyModule(__name__, globals()["__file__"], _import_structure)
