



'''simple docstring'''



import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
							lowerCAmelCase_     :       int								=						'pt'
elif is_tf_available():
							lowerCAmelCase_     :       int								=						'tf'
else:
							lowerCAmelCase_     :       Tuple								=						'jax'
class 	lowerCamelCase_							(					snake_case_    ,				unittest.TestCase			):
						_lowerCAmelCase     :   Dict	     =				ByTaTokenizer
						_lowerCAmelCase     :   Union[str, Any]	     =				False







						def 					__lowercase    (  self   :      List[Any]				):

													"""simple docstring"""
													super().setUp()
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			ByTaTokenizer()
													tokenizer.save_pretrained(self.tmpdirname				)







						@cached_property
						def 					__lowercase    (  self   :      str				):

													"""simple docstring"""
													return ByTaTokenizer.from_pretrained('''google/byt5-small'''				)







						def 					__lowercase    (  self   :      Union[str, Any]				,    **lowerCAmelCase__   :      List[str]				):

													"""simple docstring"""
													return self.tokenizer_class.from_pretrained(self.tmpdirname				,    **lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[str]				,    lowerCAmelCase__   :      List[Any]				,    lowerCAmelCase__   :      List[Any]=False				,    lowerCAmelCase__   :      List[Any]=20				,    lowerCAmelCase__   :      List[str]=5				):

													"""simple docstring"""
													# XXX The default common tokenizer tests assume that every ID is decodable on its own.
													# This assumption is invalid for ByT5 because single bytes might not be
													# valid utf-8 (byte 128 for instance).
													# Here we're overriding the smallest possible method to provide
													# a clean sequence without making the same assumption.

													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			[]
													for i in range(len(lowerCAmelCase__				)				):
																				try:
																											SCREAMING_SNAKE_CASE					:      int     					=			tokenizer.decode([i]				,    clean_up_tokenization_spaces=lowerCAmelCase__				)
																				except UnicodeDecodeError:
																											pass
																				toks.append((i, tok)				)

													SCREAMING_SNAKE_CASE					:      int     					=			list(filter(lambda lowerCAmelCase__				: re.match(R'''^[ a-zA-Z]+$'''				,    t[1]				)				,    lowerCAmelCase__				)				)
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			list(filter(lambda lowerCAmelCase__				: [t[0]] == tokenizer.encode(t[1]				,    add_special_tokens=lowerCAmelCase__				)				,    lowerCAmelCase__				)				)
													if max_length is not None and len(lowerCAmelCase__				) > max_length:
																				SCREAMING_SNAKE_CASE					:      Dict     					=			toks[:max_length]
													if min_length is not None and len(lowerCAmelCase__				) < min_length and len(lowerCAmelCase__				) > 0:
																				while len(lowerCAmelCase__				) < min_length:
																											SCREAMING_SNAKE_CASE					:      Dict     					=			toks + toks
        # toks_str = [t[1] for t in toks]
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			[t[0] for t in toks]

													# Ensure consistency
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer.decode(lowerCAmelCase__				,    clean_up_tokenization_spaces=lowerCAmelCase__				)
													if " " not in output_txt and len(lowerCAmelCase__				) > 1:
																				SCREAMING_SNAKE_CASE					:      List[Any]     					=			(
																				    tokenizer.decode([toks_ids[0]]				,    clean_up_tokenization_spaces=lowerCAmelCase__				)
																				    + ''' '''
																				    + tokenizer.decode(toks_ids[1:]				,    clean_up_tokenization_spaces=lowerCAmelCase__				)
																				)
													if with_prefix_space:
																				SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			''' ''' + output_txt
													SCREAMING_SNAKE_CASE					:      Any     					=			tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
													return output_txt, output_ids







						def 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Dict     					=			self.ta_base_tokenizer
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer(['''hi</s>''', '''I went to the gym</s>''', '''</s>''']				)
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer(['''hi''', '''I went to the gym''', '''''']				)
													self.assertListEqual(batch_with_eos_added['''input_ids''']				,    batch_without_eos_added['''input_ids''']				)







						def 					__lowercase    (  self   :      str				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			self.ta_base_tokenizer
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			'''Unicode €.'''
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			tokenizer(lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			[88, 1_13, 1_08, 1_02, 1_14, 1_03, 1_04, 35, 2_29, 1_33, 1_75, 49, 1]
													self.assertEqual(encoded['''input_ids''']				,    lowerCAmelCase__				)

													# decoding
													SCREAMING_SNAKE_CASE					:      int     					=			tokenizer.decode(lowerCAmelCase__				)
													self.assertEqual(lowerCAmelCase__				,    '''Unicode €.</s>'''				)

													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer('''e è é ê ë'''				)
													SCREAMING_SNAKE_CASE					:      Dict     					=			[1_04, 35, 1_98, 1_71, 35, 1_98, 1_72, 35, 1_98, 1_73, 35, 1_98, 1_74, 1]
													self.assertEqual(encoded['''input_ids''']				,    lowerCAmelCase__				)
													# decoding
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			tokenizer.decode(lowerCAmelCase__				)
													self.assertEqual(lowerCAmelCase__				,    '''e è é ê ë</s>'''				)

													# encode/decode, but with `encode` instead of `__call__`
													self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë'''				)				)				,    '''e è é ê ë</s>'''				)







						def 					__lowercase    (  self   :      List[str]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Dict     					=			self.ta_base_tokenizer
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
													# fmt: off
													SCREAMING_SNAKE_CASE					:      int     					=			[68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 1, 0]
													# fmt: on
													SCREAMING_SNAKE_CASE					:      Dict     					=			tokenizer(lowerCAmelCase__				,    padding=lowerCAmelCase__				,    return_tensors=lowerCAmelCase__				)
													self.assertIsInstance(lowerCAmelCase__				,    lowerCAmelCase__				)

													if FRAMEWORK != "jax":
																				SCREAMING_SNAKE_CASE					:      Any     					=			list(batch.input_ids.numpy()[0]				)
													else:
																				SCREAMING_SNAKE_CASE					:      List[Any]     					=			list(batch.input_ids.tolist()[0]				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

													self.assertEqual((2, 37)				,    batch.input_ids.shape				)
													self.assertEqual((2, 37)				,    batch.attention_mask.shape				)







						def 					__lowercase    (  self   :      List[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.ta_base_tokenizer
													SCREAMING_SNAKE_CASE					:      str     					=			['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			tokenizer(lowerCAmelCase__				,    padding=lowerCAmelCase__				,    return_tensors=lowerCAmelCase__				)
													# check if input_ids are returned and no decoder_input_ids
													self.assertIn('''input_ids'''				,    lowerCAmelCase__				)
													self.assertIn('''attention_mask'''				,    lowerCAmelCase__				)
													self.assertNotIn('''decoder_input_ids'''				,    lowerCAmelCase__				)
													self.assertNotIn('''decoder_attention_mask'''				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[str]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Any     					=			self.ta_base_tokenizer
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			[
													    '''Summary of the text.''',
													    '''Another summary.''',
													]
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer(
													    text_target=lowerCAmelCase__				,    max_length=32				,    padding='''max_length'''				,    truncation=lowerCAmelCase__				,    return_tensors=lowerCAmelCase__				)
													self.assertEqual(32				,    targets['''input_ids'''].shape[1]				)







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			self.ta_base_tokenizer
													SCREAMING_SNAKE_CASE					:      Tuple     					=			['''A long paragraph for summarization. </s>''']
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			['''Summary of the text. </s>''']
													# fmt: off
													SCREAMING_SNAKE_CASE					:      Dict     					=			[68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 35, 1]
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			[86, 1_20, 1_12, 1_12, 1_00, 1_17, 1_24, 35, 1_14, 1_05, 35, 1_19, 1_07, 1_04, 35, 1_19, 1_04, 1_23, 1_19, 49, 35, 1]
													# fmt: on

													SCREAMING_SNAKE_CASE					:      str     					=			tokenizer(lowerCAmelCase__				,    text_target=lowerCAmelCase__				)

													self.assertEqual(lowerCAmelCase__				,    batch['''input_ids'''][0]				)
													self.assertEqual(lowerCAmelCase__				,    batch['''labels'''][0]				)







						def 					__lowercase    (  self   :      Optional[Any]				):

													"""simple docstring"""
													# safety check on max_len default value so we are sure the test works
													SCREAMING_SNAKE_CASE					:      Any     					=			self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(F"""{tokenizer.__class__.__name__}"""				):
																											self.assertNotEqual(tokenizer.model_max_length				,    42				)

        # Now let's start the test
													SCREAMING_SNAKE_CASE					:      Tuple     					=			self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(F"""{tokenizer.__class__.__name__}"""				):
																											# Isolate this from the other tests because we save additional tokens/etc
																											SCREAMING_SNAKE_CASE					:      Dict     					=			tempfile.mkdtemp()

																											SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			''' He is very happy, UNwant\u00E9d,running'''
																											SCREAMING_SNAKE_CASE					:      str     					=			tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
																											tokenizer.save_pretrained(lowerCAmelCase__				)

																											SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			tokenizer.__class__.from_pretrained(lowerCAmelCase__				)
																											SCREAMING_SNAKE_CASE					:      Any     					=			after_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
																											self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)

																											shutil.rmtree(lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			self.get_tokenizers(model_max_length=42				)
													for tokenizer in tokenizers:
																				with self.subTest(F"""{tokenizer.__class__.__name__}"""				):
																											# Isolate this from the other tests because we save additional tokens/etc
																											SCREAMING_SNAKE_CASE					:      Dict     					=			tempfile.mkdtemp()

																											SCREAMING_SNAKE_CASE					:      Tuple     					=			''' He is very happy, UNwant\u00E9d,running'''
																											tokenizer.add_tokens(['''bim''', '''bambam''']				)
																											SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer.additional_special_tokens
																											additional_special_tokens.append('''new_additional_special_token'''				)
																											tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}				)
																											SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
																											tokenizer.save_pretrained(lowerCAmelCase__				)

																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer.__class__.from_pretrained(lowerCAmelCase__				)
																											SCREAMING_SNAKE_CASE					:      List[Any]     					=			after_tokenizer.encode(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				)
																											self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
																											self.assertIn('''new_additional_special_token'''				,    after_tokenizer.additional_special_tokens				)
																											self.assertEqual(after_tokenizer.model_max_length				,    42				)

																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer.__class__.from_pretrained(lowerCAmelCase__				,    model_max_length=43				)
																											self.assertEqual(tokenizer.model_max_length				,    43				)

																											shutil.rmtree(lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Optional[int]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Tuple     					=			[]
													if self.test_slow_tokenizer:
																				tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())				)

													if self.test_rust_tokenizer:
																				tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())				)

													for tokenizer_class, tokenizer_utils in tokenizer_list:
																				with tempfile.TemporaryDirectory() as tmp_dir:
																											tokenizer_utils.save_pretrained(lowerCAmelCase__				)

																											with open(os.path.join(lowerCAmelCase__				,    '''special_tokens_map.json'''				)				,    encoding='''utf-8'''				) as json_file:
																																		SCREAMING_SNAKE_CASE					:      Any     					=			json.load(lowerCAmelCase__				)

																											with open(os.path.join(lowerCAmelCase__				,    '''tokenizer_config.json'''				)				,    encoding='''utf-8'''				) as json_file:
																																		SCREAMING_SNAKE_CASE					:      Tuple     					=			json.load(lowerCAmelCase__				)

																											SCREAMING_SNAKE_CASE					:      int     					=			[F"""<extra_id_{i}>""" for i in range(1_25				)]

																											SCREAMING_SNAKE_CASE					:      List[Any]     					=			added_tokens_extra_ids + [
																											    '''an_additional_special_token'''
																											]
																											SCREAMING_SNAKE_CASE					:      int     					=			added_tokens_extra_ids + [
																											    '''an_additional_special_token'''
																											]

																											with open(os.path.join(lowerCAmelCase__				,    '''special_tokens_map.json'''				)				,    '''w'''				,    encoding='''utf-8'''				) as outfile:
																																		json.dump(lowerCAmelCase__				,    lowerCAmelCase__				)
																											with open(os.path.join(lowerCAmelCase__				,    '''tokenizer_config.json'''				)				,    '''w'''				,    encoding='''utf-8'''				) as outfile:
																																		json.dump(lowerCAmelCase__				,    lowerCAmelCase__				)

																											# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
																											# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
																											# "special_tokens_map.json" files
																											SCREAMING_SNAKE_CASE					:      Any     					=			tokenizer_class.from_pretrained(
																											    lowerCAmelCase__				,    )
																											self.assertIn(
																											    '''an_additional_special_token'''				,    tokenizer_without_change_in_init.additional_special_tokens				)
																											# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
																											self.assertEqual(
																											    ['''an_additional_special_token''']				,    tokenizer_without_change_in_init.convert_ids_to_tokens(
																											        tokenizer_without_change_in_init.convert_tokens_to_ids(['''an_additional_special_token''']				)				)				,    )

																											# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''				,    lstrip=lowerCAmelCase__				)]
																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer_class.from_pretrained(
																											    lowerCAmelCase__				,    additional_special_tokens=lowerCAmelCase__				,    )

																											self.assertIn('''a_new_additional_special_token'''				,    tokenizer.additional_special_tokens				)
																											self.assertEqual(
																											    ['''a_new_additional_special_token''']				,    tokenizer.convert_ids_to_tokens(
																											        tokenizer.convert_tokens_to_ids(['''a_new_additional_special_token''']				)				)				,    )







						def 					__lowercase    (  self   :      List[str]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Any     					=			[]
													if self.test_slow_tokenizer:
																				tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())				)

													if self.test_rust_tokenizer:
																				tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())				)

													for tokenizer_class, tokenizer_utils in tokenizer_list:
																				with tempfile.TemporaryDirectory() as tmp_dir:
																											tokenizer_utils.save_pretrained(lowerCAmelCase__				)

																											SCREAMING_SNAKE_CASE					:      List[Any]     					=			tokenizer_class.from_pretrained(lowerCAmelCase__				)

																											self.assertTrue(tokenizer.decode([2_55]				) == ''''''				)







						def 					__lowercase    (  self   :      str				):

													"""simple docstring"""
													pass







						def 					__lowercase    (  self   :      int				):

													"""simple docstring"""
													pass







						def 					__lowercase    (  self   :      List[Any]				):

													"""simple docstring"""
													pass







						def 					__lowercase    (  self   :      Union[str, Any]				):

													"""simple docstring"""
													pass







						def 					__lowercase    (  self   :      str				):

													"""simple docstring"""
													# The default common tokenizer tests uses invalid tokens for ByT5 that can only accept one-character strings
													# and special added tokens as tokens
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.get_tokenizers(fast=lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				)
													for tokenizer in tokenizers:
																				with self.subTest(F"""{tokenizer.__class__.__name__}"""				):
																											SCREAMING_SNAKE_CASE					:      List[str]     					=			['''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''x''', '''t''', '''</s>''']
																											SCREAMING_SNAKE_CASE					:      List[str]     					=			tokenizer.convert_tokens_to_string(lowerCAmelCase__				)

																											self.assertIsInstance(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[str]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Dict     					=			self.get_tokenizers()
													for tokenizer in tokenizers:
																				with self.subTest(F"""{tokenizer.__class__.__name__}"""				):
																											SCREAMING_SNAKE_CASE					:      str     					=			[
																											    '''bos_token''',
																											    '''eos_token''',
																											    '''unk_token''',
																											    '''sep_token''',
																											    '''pad_token''',
																											    '''cls_token''',
																											    '''mask_token''',
																											]

																											SCREAMING_SNAKE_CASE					:      Any     					=			0
																											SCREAMING_SNAKE_CASE					:      Any     					=			tokenizer.convert_ids_to_tokens(
																											    lowerCAmelCase__				,    skip_special_tokens=lowerCAmelCase__				)

																											for attr in attributes_list:
																																		setattr(lowerCAmelCase__				,    attr + '''_id'''				,    lowerCAmelCase__				)
																																		self.assertEqual(getattr(lowerCAmelCase__				,    lowerCAmelCase__				)				,    lowerCAmelCase__				)
																																		self.assertEqual(getattr(lowerCAmelCase__				,    attr + '''_id'''				)				,    lowerCAmelCase__				)

																																		setattr(lowerCAmelCase__				,    attr + '''_id'''				,    lowerCAmelCase__				)
																																		self.assertEqual(getattr(lowerCAmelCase__				,    lowerCAmelCase__				)				,    lowerCAmelCase__				)
																																		self.assertEqual(getattr(lowerCAmelCase__				,    attr + '''_id'''				)				,    lowerCAmelCase__				)

																											setattr(lowerCAmelCase__				,    '''additional_special_tokens_ids'''				,    []				)
																											self.assertListEqual(getattr(lowerCAmelCase__				,    '''additional_special_tokens'''				)				,    []				)
																											self.assertListEqual(getattr(lowerCAmelCase__				,    '''additional_special_tokens_ids'''				)				,    []				)

																											setattr(lowerCAmelCase__				,    '''additional_special_tokens_ids'''				,    [token_id_to_test_setters]				)
																											self.assertListEqual(getattr(lowerCAmelCase__				,    '''additional_special_tokens'''				)				,    [token_to_test_setters]				)
																											self.assertListEqual(getattr(lowerCAmelCase__				,    '''additional_special_tokens_ids'''				)				,    [token_id_to_test_setters]				)









'''simple docstring'''



from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
							if not (is_transformers_available() and is_torch_available()):
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							from ...utils.dummy_torch_and_transformers_objects import (
							    ImageTextPipelineOutput,
							    UniDiffuserPipeline,
							)
else:
							from .modeling_text_decoder import UniDiffuserTextDecoder
							from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
							from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline




