

import unittest

import numpy as np

from transformers import is_flax_available
from transformers.testing_utils import require_flax

from ..test_modeling_flax_common import ids_tensor


if is_flax_available():
						import jax
						import jax.numpy as jnp

						from transformers.generation import (
						    FlaxForcedBOSTokenLogitsProcessor,
						    FlaxForcedEOSTokenLogitsProcessor,
						    FlaxLogitsProcessorList,
						    FlaxMinLengthLogitsProcessor,
						    FlaxTemperatureLogitsWarper,
						    FlaxTopKLogitsWarper,
						    FlaxTopPLogitsWarper,
						)



@require_flax
class   __lowercase				( unittest.TestCase	):




			"""simple docstring"""







			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[int]   ,						lowerCAmelCase__  :     int   ,						lowerCAmelCase__  :     int):
									SCREAMING_SNAKE_CASE_: str  		=       jnp.ones((batch_size, length)) / length
									return scores



			def        _SCREAMING_SNAKE_CASE			( self  :     Union[str, Any]):
									SCREAMING_SNAKE_CASE_: Dict  		=       None
									SCREAMING_SNAKE_CASE_: str  		=       20

									SCREAMING_SNAKE_CASE_: List[Any]  		=       self._get_uniform_logits(batch_size=2   ,						length=lowerCAmelCase__)

									# tweak scores to not be uniform anymore
									SCREAMING_SNAKE_CASE_: List[str]  		=       scores.at[1, 5].set((1 / length) + 0.1)  # peak, 1st batch
									SCREAMING_SNAKE_CASE_: Any  		=       scores.at[1, 10].set((1 / length) - 0.4)  # valley, 1st batch

									# compute softmax
									SCREAMING_SNAKE_CASE_: Dict  		=       jax.nn.softmax(lowerCAmelCase__   ,						axis=-1)

									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       FlaxTemperatureLogitsWarper(temperature=0.5)
									SCREAMING_SNAKE_CASE_: List[str]  		=       FlaxTemperatureLogitsWarper(temperature=1.3)

									SCREAMING_SNAKE_CASE_: str  		=       jax.nn.softmax(temp_dist_warper_sharper(lowerCAmelCase__   ,						scores.copy()   ,						cur_len=lowerCAmelCase__)   ,						axis=-1)
									SCREAMING_SNAKE_CASE_: int  		=       jax.nn.softmax(temp_dist_warper_smoother(lowerCAmelCase__   ,						scores.copy()   ,						cur_len=lowerCAmelCase__)   ,						axis=-1)

									# uniform distribution stays uniform
									self.assertTrue(jnp.allclose(probs[0, :]   ,						warped_prob_sharp[0, :]   ,						atol=1E-3))
									self.assertTrue(jnp.allclose(probs[0, :]   ,						warped_prob_smooth[0, :]   ,						atol=1E-3))

									# sharp peaks get higher, valleys get lower
									self.assertLess(probs[1, :].max()   ,						warped_prob_sharp[1, :].max())
									self.assertGreater(probs[1, :].min()   ,						warped_prob_sharp[1, :].min())

									# smooth peaks get lower, valleys get higher
									self.assertGreater(probs[1, :].max()   ,						warped_prob_smooth[1, :].max())
									self.assertLess(probs[1, :].min()   ,						warped_prob_smooth[1, :].min())



			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[int]):
									SCREAMING_SNAKE_CASE_: List[str]  		=       None
									SCREAMING_SNAKE_CASE_: str  		=       10
									SCREAMING_SNAKE_CASE_: Tuple  		=       2

									# create ramp distribution
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       np.broadcast_to(np.arange(lowerCAmelCase__)[None, :]   ,						(batch_size, vocab_size)).copy()
									SCREAMING_SNAKE_CASE_: Dict  		=       ramp_logits[1:, : vocab_size // 2] + vocab_size

									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       FlaxTopKLogitsWarper(3)

									SCREAMING_SNAKE_CASE_: Dict  		=       top_k_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)

									# check that correct tokens are filtered
									self.assertListEqual(jnp.isinf(scores[0]).tolist()   ,						7 * [True] + 3 * [False])
									self.assertListEqual(jnp.isinf(scores[1]).tolist()   ,						2 * [True] + 3 * [False] + 5 * [True])

									# check special case
									SCREAMING_SNAKE_CASE_: Any  		=       5
									SCREAMING_SNAKE_CASE_: str  		=       FlaxTopKLogitsWarper(top_k=1   ,						filter_value=0.0   ,						min_tokens_to_keep=3)

									SCREAMING_SNAKE_CASE_: Any  		=       np.broadcast_to(np.arange(lowerCAmelCase__)[None, :]   ,						(batch_size, length)).copy()
									SCREAMING_SNAKE_CASE_: Any  		=       top_k_warp_safety_check(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)

									# min_tokens overwrites k: 3 tokens are kept => 2 tokens are nullified
									self.assertListEqual((scores == 0.0).sum(axis=-1).tolist()   ,						[2, 2])



			def        _SCREAMING_SNAKE_CASE			( self  :     int):
									SCREAMING_SNAKE_CASE_: Tuple  		=       None
									SCREAMING_SNAKE_CASE_: Dict  		=       10
									SCREAMING_SNAKE_CASE_: Dict  		=       2

									# create distribution and take log (inverse to Softmax as taken in TopPLogitsWarper)
									SCREAMING_SNAKE_CASE_: Tuple  		=       np.log(np.array([[0.3, 0.1, 0.1, 0.5], [0.15, 0.3, 0.3, 0.25]]))

									SCREAMING_SNAKE_CASE_: int  		=       FlaxTopPLogitsWarper(0.8)
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       np.exp(top_p_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__))

									# dist should be filtered to keep min num values so that sum is >= top_p
									# exp (-inf) => 0
									SCREAMING_SNAKE_CASE_: Dict  		=       np.array([[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.25]])
									self.assertTrue(np.allclose(lowerCAmelCase__   ,						lowerCAmelCase__   ,						atol=1E-3))

									# check edge cases with negative and extreme logits
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       np.broadcast_to(np.arange(lowerCAmelCase__)[None, :]   ,						(batch_size, vocab_size)).copy() - (
									    vocab_size // 2
									)

									# make ramp_logits more extreme
									SCREAMING_SNAKE_CASE_: Dict  		=       ramp_logits[1] * 100.0

									# make sure at least 2 tokens are kept
									SCREAMING_SNAKE_CASE_: str  		=       FlaxTopPLogitsWarper(0.9   ,						min_tokens_to_keep=2   ,						filter_value=0.0)
									SCREAMING_SNAKE_CASE_: Any  		=       top_p_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)

									# first batch should keep three tokens, second batch would keep only 1, but due to `min_tokens_to_keep=2` keeps 2.
									self.assertListEqual((filtered_dist != 0.0).sum(axis=-1).tolist()   ,						[3, 2])



			def        _SCREAMING_SNAKE_CASE			( self  :     Tuple):
									SCREAMING_SNAKE_CASE_: Tuple  		=       20
									SCREAMING_SNAKE_CASE_: List[str]  		=       4
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       0

									SCREAMING_SNAKE_CASE_: str  		=       FlaxMinLengthLogitsProcessor(min_length=10   ,						eos_token_id=lowerCAmelCase__)

									# check that min length is applied at length 5
									SCREAMING_SNAKE_CASE_: str  		=       ids_tensor((batch_size, 20)   ,						vocab_size=20)
									SCREAMING_SNAKE_CASE_: int  		=       5
									SCREAMING_SNAKE_CASE_: List[Any]  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: str  		=       min_dist_processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									self.assertListEqual(scores_before_min_length[:, eos_token_id].tolist()   ,						4 * [-float("inf")])

									# check that min length is not applied anymore at length 15
									SCREAMING_SNAKE_CASE_: List[str]  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       15
									SCREAMING_SNAKE_CASE_: Any  		=       min_dist_processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									self.assertFalse(jnp.isinf(lowerCAmelCase__).any())



			def        _SCREAMING_SNAKE_CASE			( self  :     Union[str, Any]):
									SCREAMING_SNAKE_CASE_: int  		=       20
									SCREAMING_SNAKE_CASE_: str  		=       4
									SCREAMING_SNAKE_CASE_: List[Any]  		=       0

									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCAmelCase__)

									# check that all scores are -inf except the bos_token_id score
									SCREAMING_SNAKE_CASE_: int  		=       ids_tensor((batch_size, 1)   ,						vocab_size=20)
									SCREAMING_SNAKE_CASE_: List[str]  		=       1
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: int  		=       logits_processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									self.assertTrue(jnp.isneginf(scores[:, bos_token_id + 1 :]).all())
									self.assertListEqual(scores[:, bos_token_id].tolist()   ,						4 * [0])  # score for bos_token_id shold be zero

									# check that bos_token_id is not forced if current length is greater than 1
									SCREAMING_SNAKE_CASE_: List[Any]  		=       3
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: int  		=       logits_processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									self.assertFalse(jnp.isinf(lowerCAmelCase__).any())



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]):
									SCREAMING_SNAKE_CASE_: Any  		=       20
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       4
									SCREAMING_SNAKE_CASE_: Dict  		=       0
									SCREAMING_SNAKE_CASE_: List[Any]  		=       5

									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCAmelCase__   ,						eos_token_id=lowerCAmelCase__)

									# check that all scores are -inf except the eos_token_id when max_length is reached
									SCREAMING_SNAKE_CASE_: List[Any]  		=       ids_tensor((batch_size, 4)   ,						vocab_size=20)
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       4
									SCREAMING_SNAKE_CASE_: Dict  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       logits_processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									self.assertTrue(jnp.isneginf(scores[:, eos_token_id + 1 :]).all())
									self.assertListEqual(scores[:, eos_token_id].tolist()   ,						4 * [0])  # score for eos_token_id should be zero

									# check that eos_token_id is not forced if max_length is not reached
									SCREAMING_SNAKE_CASE_: List[str]  		=       3
									SCREAMING_SNAKE_CASE_: str  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: int  		=       logits_processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									self.assertFalse(jnp.isinf(lowerCAmelCase__).any())



			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[int]):
									SCREAMING_SNAKE_CASE_: int  		=       4
									SCREAMING_SNAKE_CASE_: List[Any]  		=       10
									SCREAMING_SNAKE_CASE_: int  		=       15
									SCREAMING_SNAKE_CASE_: Dict  		=       2
									SCREAMING_SNAKE_CASE_: int  		=       1
									SCREAMING_SNAKE_CASE_: List[Any]  		=       15

									# dummy input_ids and scores
									SCREAMING_SNAKE_CASE_: int  		=       ids_tensor((batch_size, sequence_length)   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: str  		=       input_ids.copy()

									SCREAMING_SNAKE_CASE_: List[Any]  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       scores.copy()

									# instantiate all dist processors
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       FlaxTemperatureLogitsWarper(temperature=0.5)
									SCREAMING_SNAKE_CASE_: Tuple  		=       FlaxTopKLogitsWarper(3)
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       FlaxTopPLogitsWarper(0.8)

									# instantiate all logits processors
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       FlaxMinLengthLogitsProcessor(min_length=10   ,						eos_token_id=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: List[Any]  		=       FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Dict  		=       FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCAmelCase__   ,						eos_token_id=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: str  		=       10

									# no processor list
									SCREAMING_SNAKE_CASE_: Dict  		=       temp_dist_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Tuple  		=       top_k_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Any  		=       top_p_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: int  		=       min_dist_proc(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       bos_dist_proc(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Tuple  		=       eos_dist_proc(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)

									# with processor list
									SCREAMING_SNAKE_CASE_: str  		=       FlaxLogitsProcessorList(
									    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc])
									SCREAMING_SNAKE_CASE_: Tuple  		=       processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)

									# scores should be equal
									self.assertTrue(jnp.allclose(lowerCAmelCase__   ,						lowerCAmelCase__   ,						atol=1E-3))

									# input_ids should never be changed
									self.assertListEqual(input_ids.tolist()   ,						input_ids_comp.tolist())




			def        _SCREAMING_SNAKE_CASE			( self  :     Any):
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       4
									SCREAMING_SNAKE_CASE_: int  		=       10
									SCREAMING_SNAKE_CASE_: List[str]  		=       15
									SCREAMING_SNAKE_CASE_: List[Any]  		=       2
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       1
									SCREAMING_SNAKE_CASE_: str  		=       15

									# dummy input_ids and scores
									SCREAMING_SNAKE_CASE_: Tuple  		=       ids_tensor((batch_size, sequence_length)   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: List[Any]  		=       input_ids.copy()

									SCREAMING_SNAKE_CASE_: List[Any]  		=       self._get_uniform_logits(lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: List[Any]  		=       scores.copy()

									# instantiate all dist processors
									SCREAMING_SNAKE_CASE_: Dict  		=       FlaxTemperatureLogitsWarper(temperature=0.5)
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       FlaxTopKLogitsWarper(3)
									SCREAMING_SNAKE_CASE_: Dict  		=       FlaxTopPLogitsWarper(0.8)

									# instantiate all logits processors
									SCREAMING_SNAKE_CASE_: int  		=       FlaxMinLengthLogitsProcessor(min_length=10   ,						eos_token_id=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: List[str]  		=       FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: List[Any]  		=       FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCAmelCase__   ,						eos_token_id=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: str  		=       10

									# no processor list
									def run_no_processor_list(lowerCAmelCase__  :     Union[str, Any]   ,						lowerCAmelCase__  :     List[Any]   ,						lowerCAmelCase__  :     Dict):
															SCREAMING_SNAKE_CASE_: Any  		=       temp_dist_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
															SCREAMING_SNAKE_CASE_: Optional[int]  		=       top_k_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
															SCREAMING_SNAKE_CASE_: Optional[int]  		=       top_p_warp(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
															SCREAMING_SNAKE_CASE_: List[Any]  		=       min_dist_proc(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
															SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       bos_dist_proc(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
															SCREAMING_SNAKE_CASE_: Optional[int]  		=       eos_dist_proc(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
															return scores

									# with processor list
									def run_processor_list(lowerCAmelCase__  :     int   ,						lowerCAmelCase__  :     List[Any]   ,						lowerCAmelCase__  :     Union[str, Any]):
															SCREAMING_SNAKE_CASE_: List[str]  		=       FlaxLogitsProcessorList(
															    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc])
															SCREAMING_SNAKE_CASE_: Dict  		=       processor(lowerCAmelCase__   ,						lowerCAmelCase__   ,						cur_len=lowerCAmelCase__)
															return scores

									SCREAMING_SNAKE_CASE_: str  		=       jax.jit(lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       jax.jit(lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: Dict  		=       jitted_run_no_processor_list(lowerCAmelCase__   ,						lowerCAmelCase__   ,						lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: List[Any]  		=       jitted_run_processor_list(lowerCAmelCase__   ,						lowerCAmelCase__   ,						lowerCAmelCase__)

									# scores should be equal
									self.assertTrue(jnp.allclose(lowerCAmelCase__   ,						lowerCAmelCase__   ,						atol=1E-3))

									# input_ids should never be changed
									self.assertListEqual(input_ids.tolist()   ,						input_ids_comp.tolist())









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


lowerCAmelCase							:  Optional[Any]   	=						get_tests_dir("""fixtures/test_sentencepiece.model""")



@require_sentencepiece
@require_tokenizers
class   __lowercase				( UpperCAmelCase_		,       unittest.TestCase	):




			"""simple docstring"""







			_UpperCAmelCase   :							Optional[Any]										=     XGLMTokenizer
			_UpperCAmelCase   :							List[Any]										=     XGLMTokenizerFast
			_UpperCAmelCase   :							Optional[int]										=     True
			_UpperCAmelCase   :							Tuple										=     True



			def        _SCREAMING_SNAKE_CASE			( self  :     Tuple):
									super().setUp()

									# We have a SentencePiece fixture for testing
									SCREAMING_SNAKE_CASE_: List[Any]  		=       XGLMTokenizer(lowerCAmelCase__   ,						keep_accents=lowerCAmelCase__)
									tokenizer.save_pretrained(self.tmpdirname)



			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[Any]):
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       "<pad>"
									SCREAMING_SNAKE_CASE_: int  		=       1

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



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]):
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       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        _SCREAMING_SNAKE_CASE			( self  :     Any):
									self.assertEqual(self.get_tokenizer().vocab_size   ,						1008)



			def        _SCREAMING_SNAKE_CASE			( self  :     Tuple):
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       XGLMTokenizer(lowerCAmelCase__   ,						keep_accents=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       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]]   ,						)

									SCREAMING_SNAKE_CASE_: List[str]  		=       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",
									        ".",
									    ]   ,						)
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       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]
									    ]   ,						)

									SCREAMING_SNAKE_CASE_: List[Any]  		=       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        _SCREAMING_SNAKE_CASE			( self  :     Any):
									return XGLMTokenizer.from_pretrained("facebook/xglm-564M")



			def        _SCREAMING_SNAKE_CASE			( self  :     str):
									with tempfile.NamedTemporaryFile() as f:
															shutil.copyfile(lowerCAmelCase__   ,						f.name)
															SCREAMING_SNAKE_CASE_: Tuple  		=       XGLMTokenizer(f.name   ,						keep_accents=lowerCAmelCase__)
															SCREAMING_SNAKE_CASE_: List[str]  		=       pickle.dumps(lowerCAmelCase__)
									pickle.loads(lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     str):
									if not self.test_rust_tokenizer:
															return

									SCREAMING_SNAKE_CASE_: Dict  		=       self.get_tokenizer()
									SCREAMING_SNAKE_CASE_: List[str]  		=       self.get_rust_tokenizer()

									SCREAMING_SNAKE_CASE_: Any  		=       "I was born in 92000, and this is falsé."

									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       tokenizer.tokenize(lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: int  		=       rust_tokenizer.tokenize(lowerCAmelCase__)
									self.assertListEqual(lowerCAmelCase__   ,						lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: List[str]  		=       tokenizer.encode(lowerCAmelCase__   ,						add_special_tokens=lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       rust_tokenizer.encode(lowerCAmelCase__   ,						add_special_tokens=lowerCAmelCase__)
									self.assertListEqual(lowerCAmelCase__   ,						lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: Optional[int]  		=       self.get_rust_tokenizer()
									SCREAMING_SNAKE_CASE_: str  		=       tokenizer.encode(lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       rust_tokenizer.encode(lowerCAmelCase__)
									self.assertListEqual(lowerCAmelCase__   ,						lowerCAmelCase__)



			@slow
			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[int]):
									SCREAMING_SNAKE_CASE_: Dict  		=       "Hello World!"
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       [2, 3_1227, 4447, 35]

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



			@slow
			def        _SCREAMING_SNAKE_CASE			( self  :     int):
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       (
									    "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
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       [2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 7_1630, 2_8085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 1_3675, 377, 652, 7580, 1_0341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 20_2277, 1_7892, 33, 60, 87, 4, 3234, 157, 61, 2667, 5_2376, 19, 88, 23, 735]
									# fmt: on

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




			@slow
			def        _SCREAMING_SNAKE_CASE			( self  :     int):
									# fmt: off
									SCREAMING_SNAKE_CASE_: str  		=       {
									    "input_ids": [[2, 10_8825, 1163, 15, 8_8010, 473, 1_5898, 157, 1_3672, 1857, 312, 8, 23_8021, 1163, 53, 1_3672, 1857, 312, 8, 5_3283, 18_2396, 8, 1_8566, 16, 3_6733, 4101, 8, 230, 24_4017, 12_2553, 7, 15, 13_2597, 4, 293, 1_2511, 7610, 4, 3414, 13_2597, 9, 4, 3_2361, 362, 4, 734, 2_8512, 3_2569, 18, 4, 3_2361, 2_6096, 1_4982, 73, 1_8715, 2_1433, 23_5261, 15, 492, 1_2427, 16, 53, 1_8715, 2_1433, 6_5454, 15, 2_3659, 563, 16, 278, 597, 2843, 595, 7931, 18_2396, 6_4186, 22, 886, 595, 13_2981, 53, 2_5540, 3449, 4_3982, 3_9901, 5951, 878, 330, 4, 2_7694, 8_0269, 312, 53, 6517, 1_1780, 611, 2_0408, 5], [2, 6, 13_2597, 67, 4_2897, 33, 592, 8, 16_3729, 2_5540, 361, 13_6997, 10_9514, 17_3230, 7, 501, 60, 10_2913, 196, 5631, 235, 6_3243, 473, 6, 23_1757, 74, 5277, 7905, 53, 3095, 3_7317, 22, 454, 18_3874, 5], [2, 268, 3_1298, 4_6530, 6, 13_2935, 4_3831, 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__   ,						)






