import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase_								=							'▁'

UpperCAmelCase_								=							get_tests_dir('''fixtures/test_sentencepiece.model''')





@require_sentencepiece
class      lowerCAmelCase						(					lowerCamelCase__			,		unittest.TestCase			):
     _SCREAMING_SNAKE_CASE     :     Dict		=BertGenerationTokenizer
     _SCREAMING_SNAKE_CASE     :     Optional[int]		=False
     _SCREAMING_SNAKE_CASE     :     Optional[int]		=True



     def 			a__  (					self       ):
            super().setUp()

            _A=	BertGenerationTokenizer(__lowerCamelCase				,      keep_accents=__lowerCamelCase       )
            tokenizer.save_pretrained(self.tmpdirname       )



     def 			a__  (					self       ):
            _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 			a__  (					self       ):
            _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]				,      '<pad>'       )
            self.assertEqual(len(__lowerCamelCase       )				,      1002       )



     def 			a__  (					self       ):
            self.assertEqual(self.get_tokenizer().vocab_size				,      1000       )



     def 			a__  (					self       ):
            _A=	BertGenerationTokenizer(__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       )				,      [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				,      [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 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 			a__  (					self       ):
            return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'       )



     @slow
     def 			a__  (					self       ):
            _A=	'''Hello World!'''
            _A=	[18536, 2260, 101]

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



     @slow
     def 			a__  (					self       ):
            _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'''
            )
            _A=	[
                871,
                419,
                358,
                946,
                991,
                2521,
                452,
                358,
                1357,
                387,
                7751,
                3536,
                112,
                985,
                456,
                126,
                865,
                938,
                5400,
                5734,
                458,
                1368,
                467,
                786,
                2462,
                5246,
                1159,
                633,
                865,
                4519,
                457,
                582,
                852,
                2557,
                427,
                916,
                508,
                405,
                34324,
                497,
                391,
                408,
                11342,
                1244,
                385,
                100,
                938,
                985,
                456,
                574,
                362,
                12597,
                3200,
                3129,
                1172,
            ]

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



     @require_torch
     @slow
     def 			a__  (					self       ):
            import torch

            from transformers import BertGenerationConfig, BertGenerationEncoder

            # Build sequence
            _A=	list(self.big_tokenizer.get_vocab().keys()       )[:10]
            _A=	''' '''.join(__lowerCamelCase       )
            _A=	self.big_tokenizer.encode_plus(__lowerCamelCase				,      return_tensors='pt'				,      return_token_type_ids=__lowerCamelCase       )
            _A=	self.big_tokenizer.batch_encode_plus(
                [sequence + ' ' + sequence]				,      return_tensors='pt'				,      return_token_type_ids=__lowerCamelCase       )

            _A=	BertGenerationConfig()
            _A=	BertGenerationEncoder(__lowerCamelCase       )

            assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

            with torch.no_grad():
                   model(**__lowerCamelCase       )
                   model(**__lowerCamelCase       )





     @slow
     def 			a__  (					self       ):
            _A=	{'''input_ids''': [[39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114], [448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 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], [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]]}  # noqa: E501
            # fmt: on

            self.tokenizer_integration_test_util(
                expected_encoding=__lowerCamelCase				,      model_name='google/bert_for_seq_generation_L-24_bbc_encoder'				,      revision='c817d1fd1be2ffa69431227a1fe320544943d4db'				,      )
import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
      import torch

if is_soundfile_availble():
      import soundfile as sf

if is_vision_available():
      from PIL import Image

def 							UpperCamelCase				(    lowerCAmelCase_=""   )		->						str:




       '''simple docstring'''






       _A=	tempfile.mkdtemp()
       return os.path.join(lowerCAmelCase_       ,					str(uuid.uuida()   ) + suffix   )





@require_soundfile
@require_torch
class      lowerCAmelCase						(					unittest.TestCase			):



     def 			a__  (					self       ):
            _A=	torch.rand(12				,      dtype=torch.floataa       ) - 0.5
            _A=	AgentAudio(lowerCAmelCase__       )
            _A=	str(agent_type.to_string()       )

            # Ensure that the tensor and the agent_type's tensor are the same
            self.assertTrue(torch.allclose(lowerCAmelCase__				,      agent_type.to_raw()				,      atol=1E-4       )       )

            del agent_type

            # Ensure the path remains even after the object deletion
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )

            # Ensure that the file contains the same value as the original tensor
            _A,			_A=	sf.read(lowerCAmelCase__       )
            self.assertTrue(torch.allclose(lowerCAmelCase__				,      torch.tensor(lowerCAmelCase__       )				,      atol=1E-4       )       )





     def 			a__  (					self       ):
            _A=	torch.rand(12				,      dtype=torch.floataa       ) - 0.5
            _A=	get_new_path(suffix='.wav'       )
            sf.write(lowerCAmelCase__				,      lowerCAmelCase__				,      16000       )

            _A=	AgentAudio(lowerCAmelCase__       )

            self.assertTrue(torch.allclose(lowerCAmelCase__				,      agent_type.to_raw()				,      atol=1E-4       )       )
            self.assertEqual(agent_type.to_string()				,      lowerCAmelCase__       )





@require_vision
@require_torch
class      lowerCAmelCase						(					unittest.TestCase			):



     def 			a__  (					self       ):
            _A=	torch.randint(0				,      256				,      (64, 64, 3)       )
            _A=	AgentImage(lowerCAmelCase__       )
            _A=	str(agent_type.to_string()       )

            # Ensure that the tensor and the agent_type's tensor are the same
            self.assertTrue(torch.allclose(lowerCAmelCase__				,      agent_type._tensor				,      atol=1E-4       )       )

            self.assertIsInstance(agent_type.to_raw()				,      Image.Image       )

            # Ensure the path remains even after the object deletion
            del agent_type
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )



     def 			a__  (					self       ):
            _A=	Path(get_tests_dir('fixtures/tests_samples/COCO'       )       ) / '000000039769.png'
            _A=	Image.open(lowerCAmelCase__       )
            _A=	AgentImage(lowerCAmelCase__       )

            self.assertTrue(path.samefile(agent_type.to_string()       )       )
            self.assertTrue(image == agent_type.to_raw()       )

            # Ensure the path remains even after the object deletion
            del agent_type
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )





     def 			a__  (					self       ):
            _A=	Path(get_tests_dir('fixtures/tests_samples/COCO'       )       ) / '000000039769.png'
            _A=	Image.open(lowerCAmelCase__       )
            _A=	AgentImage(lowerCAmelCase__       )

            self.assertFalse(path.samefile(agent_type.to_string()       )       )
            self.assertTrue(image == agent_type.to_raw()       )

            # Ensure the path remains even after the object deletion
            del agent_type
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )





class      lowerCAmelCase						(					unittest.TestCase			):



     def 			a__  (					self       ):
            _A=	'Hey!'
            _A=	AgentText(lowerCAmelCase__       )

            self.assertEqual(lowerCAmelCase__				,      agent_type.to_string()       )
            self.assertEqual(lowerCAmelCase__				,      agent_type.to_raw()       )
            self.assertEqual(lowerCAmelCase__				,      lowerCAmelCase__       )