

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

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

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
							lowercase__	:Dict										=					"pt"
elif is_tf_available():
							lowercase__	:List[Any]										=					"tf"
else:
							lowercase__	:int										=					"jax"







class        lowercase	(      _a ,						unittest.TestCase	):
							lowercase_ : Union[str, Any]       =PerceiverTokenizer
							lowercase_ : List[str]       =False




							def 				A__   (       self):
												super().setUp()
												lowercase					=		PerceiverTokenizer()
												tokenizer.save_pretrained(self.tmpdirname)




							@cached_property
							def 				A__   (       self):
												return PerceiverTokenizer.from_pretrained('''deepmind/language-perceiver''')




							def 				A__   (       self     ,**A__):
												return self.tokenizer_class.from_pretrained(self.tmpdirname     ,**_A)




							def 				A__   (       self     ,A__     ,A__=False     ,A__=2_0     ,A__=5):
												# XXX The default common tokenizer tests assume that every ID is decodable on its own.
												# This assumption is invalid for Perceiver 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.

												lowercase					=		[]
												for i in range(len(_A)):
																	try:
																						lowercase					=		tokenizer.decode([i]     ,clean_up_tokenization_spaces=_A)
																	except UnicodeDecodeError:
																						pass
																	toks.append((i, tok))

												lowercase					=		list(filter(lambda A__: re.match(r'''^[ a-zA-Z]+$'''     ,t[1])     ,_A))
												lowercase					=		list(filter(lambda A__: [t[0]] == tokenizer.encode(t[1]     ,add_special_tokens=_A)     ,_A))
												if max_length is not None and len(_A) > max_length:
																	lowercase					=		toks[:max_length]
												if min_length is not None and len(_A) < min_length and len(_A) > 0:
																	while len(_A) < min_length:
																						lowercase					=		toks + toks
        # toks_str = [t[1] for t in toks]
												lowercase					=		[t[0] for t in toks]

												# Ensure consistency
												lowercase					=		tokenizer.decode(_A     ,clean_up_tokenization_spaces=_A)
												if " " not in output_txt and len(_A) > 1:
																	lowercase					=		(
																	    tokenizer.decode([toks_ids[0]]     ,clean_up_tokenization_spaces=_A)
																	    + ''' '''
																	    + tokenizer.decode(toks_ids[1:]     ,clean_up_tokenization_spaces=_A)
																	)
												if with_prefix_space:
																	lowercase					=		''' ''' + output_txt
												lowercase					=		tokenizer.encode(_A     ,add_special_tokens=_A)
												return output_txt, output_ids




							def 				A__   (       self):
												lowercase					=		self.perceiver_tokenizer
												lowercase					=		'''Unicode €.'''
												lowercase					=		tokenizer(_A)
												lowercase					=		[4, 9_1, 1_1_6, 1_1_1, 1_0_5, 1_1_7, 1_0_6, 1_0_7, 3_8, 2_3_2, 1_3_6, 1_7_8, 5_2, 5]
												self.assertEqual(encoded['''input_ids''']     ,_A)

												# decoding
												lowercase					=		tokenizer.decode(_A)
												self.assertEqual(_A     ,'''[CLS]Unicode €.[SEP]''')

												lowercase					=		tokenizer('''e è é ê ë''')
												lowercase					=		[4, 1_0_7, 3_8, 2_0_1, 1_7_4, 3_8, 2_0_1, 1_7_5, 3_8, 2_0_1, 1_7_6, 3_8, 2_0_1, 1_7_7, 5]
												self.assertEqual(encoded['''input_ids''']     ,_A)
												# decoding
												lowercase					=		tokenizer.decode(_A)
												self.assertEqual(_A     ,'''[CLS]e è é ê ë[SEP]''')

												# encode/decode, but with `encode` instead of `__call__`
												self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë'''))     ,'''[CLS]e è é ê ë[SEP]''')




							def 				A__   (       self):
												lowercase					=		self.perceiver_tokenizer
												lowercase					=		['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
												# fmt: off
												lowercase					=		[4, 7_1, 3_8, 1_1_4, 1_1_7, 1_1_6, 1_0_9, 3_8, 1_1_8, 1_0_3, 1_2_0, 1_0_3, 1_0_9, 1_2_0, 1_0_3, 1_1_8, 1_1_0, 3_8, 1_0_8, 1_1_7, 1_2_0, 3_8, 1_2_1, 1_2_3, 1_1_5, 1_1_5, 1_0_3, 1_2_0, 1_1_1, 1_2_8, 1_0_3, 1_2_2, 1_1_1, 1_1_7, 1_1_6, 5_2, 5, 0]
												# fmt: on
												lowercase					=		tokenizer(_A     ,padding=_A     ,return_tensors=_A)
												self.assertIsInstance(_A     ,_A)

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

												self.assertListEqual(_A     ,_A)

												self.assertEqual((2, 3_8)     ,batch.input_ids.shape)
												self.assertEqual((2, 3_8)     ,batch.attention_mask.shape)




							def 				A__   (       self):
												lowercase					=		self.perceiver_tokenizer
												lowercase					=		['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
												lowercase					=		tokenizer(_A     ,padding=_A     ,return_tensors=_A)
												# check if input_ids are returned and no decoder_input_ids
												self.assertIn('''input_ids'''     ,_A)
												self.assertIn('''attention_mask'''     ,_A)
												self.assertNotIn('''decoder_input_ids'''     ,_A)
												self.assertNotIn('''decoder_attention_mask'''     ,_A)




							def 				A__   (       self):
												lowercase					=		self.perceiver_tokenizer
												lowercase					=		[
												    '''Summary of the text.''',
												    '''Another summary.''',
												]
												lowercase					=		tokenizer(
												    text_target=_A     ,max_length=3_2     ,padding='''max_length'''     ,truncation=_A     ,return_tensors=_A)
												self.assertEqual(3_2     ,targets['''input_ids'''].shape[1])




							def 				A__   (       self):
												# safety check on max_len default value so we are sure the test works
												lowercase					=		self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(f'{tokenizer.__class__.__name__}'):
																						self.assertNotEqual(tokenizer.model_max_length     ,4_2)

        # Now let's start the test
												lowercase					=		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
																						lowercase					=		tempfile.mkdtemp()

																						lowercase					=		''' He is very happy, UNwant\u00E9d,running'''
																						lowercase					=		tokenizer.encode(_A     ,add_special_tokens=_A)
																						tokenizer.save_pretrained(_A)

																						lowercase					=		tokenizer.__class__.from_pretrained(_A)
																						lowercase					=		after_tokenizer.encode(_A     ,add_special_tokens=_A)
																						self.assertListEqual(_A     ,_A)

																						shutil.rmtree(_A)

												lowercase					=		self.get_tokenizers(model_max_length=4_2)
												for tokenizer in tokenizers:
																	with self.subTest(f'{tokenizer.__class__.__name__}'):
																						# Isolate this from the other tests because we save additional tokens/etc
																						lowercase					=		tempfile.mkdtemp()

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

																						lowercase					=		tokenizer.__class__.from_pretrained(_A)
																						lowercase					=		after_tokenizer.encode(_A     ,add_special_tokens=_A)
																						self.assertListEqual(_A     ,_A)
																						self.assertIn('''new_additional_special_token'''     ,after_tokenizer.additional_special_tokens)
																						self.assertEqual(after_tokenizer.model_max_length     ,4_2)

																						lowercase					=		tokenizer.__class__.from_pretrained(_A     ,model_max_length=4_3)
																						self.assertEqual(tokenizer.model_max_length     ,4_3)

																						shutil.rmtree(_A)




							def 				A__   (       self):
												lowercase					=		[]
												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(_A)

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

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

																						lowercase					=		[f'<extra_id_{i}>' for i in range(1_2_5)]

																						lowercase					=		added_tokens_extra_ids + [
																						    '''an_additional_special_token'''
																						]
																						lowercase					=		added_tokens_extra_ids + [
																						    '''an_additional_special_token'''
																						]

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

																						# 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
																						lowercase					=		tokenizer_class.from_pretrained(
																						    _A     ,)
																						self.assertIn(
																						    '''an_additional_special_token'''     ,tokenizer_without_change_in_init.additional_special_tokens)
																						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
																						lowercase					=		added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''     ,lstrip=_A)]
																						lowercase					=		tokenizer_class.from_pretrained(
																						    _A     ,additional_special_tokens=_A     ,)

																						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 				A__   (       self):
												lowercase					=		self.perceiver_tokenizer
												self.assertEqual(tokenizer.decode([1_7_8])     ,'''�''')




							def 				A__   (       self):
												pass




							def 				A__   (       self):
												pass




							def 				A__   (       self):
												pass




							def 				A__   (       self):
												pass





							def 				A__   (       self):
												# The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
												# strings and special added tokens as tokens
												lowercase					=		self.get_tokenizers(fast=_A     ,do_lower_case=_A)
												for tokenizer in tokenizers:
																	with self.subTest(f'{tokenizer.__class__.__name__}'):
																						lowercase					=		['''[CLS]''', '''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''s''', '''t''', '''[SEP]''']
																						lowercase					=		tokenizer.convert_tokens_to_string(_A)

																						self.assertIsInstance(_A     ,_A)






import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock

import torch

from ..state import AcceleratorState, PartialState
from ..utils import (
    gather,
    is_bnb_available,
    is_comet_ml_available,
    is_datasets_available,
    is_deepspeed_available,
    is_mps_available,
    is_safetensors_available,
    is_tensorboard_available,
    is_torch_version,
    is_tpu_available,
    is_transformers_available,
    is_wandb_available,
    is_xpu_available,
)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					try:
										lowercase					=		os.environ[key]
					except KeyError:
										# KEY isn't set, default to `default`.
										lowercase					=		default
					else:
										# KEY is set, convert it to True or False.
										try:
															lowercase					=		strtobool(lowerCAmelCase__	)
										except ValueError:
															# More values are supported, but let's keep the message simple.
															raise ValueError(f'If set, {key} must be yes or no.'	)
					return _value


lowercase__	:Dict										=					parse_flag_from_env("RUN_SLOW", default=False)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skip('''Test was skipped'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(_run_slow_tests				,    '''test is slow'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(not torch.cuda.is_available()				,    '''test requires only a CPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.is_available()				,    '''test requires a GPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_xpu_available()				,    '''test requires a XPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_mps_available()				,    '''test requires a `mps` backend support in `torch`'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(
					    is_transformers_available() and is_datasets_available()				,    '''test requires the Hugging Face suite'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_bnb_available()				,    '''test requires the bitsandbytes library'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_tpu_available()				,    '''test requires TPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.device_count() == 1				,    '''test requires a GPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.xpu.device_count() == 1				,    '''test requires a XPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.device_count() > 1				,    '''test requires multiple GPUs'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.xpu.device_count() > 1				,    '''test requires multiple XPUs'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_safetensors_available()				,    '''test requires safetensors'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_deepspeed_available()				,    '''test requires DeepSpeed'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_torch_version('''>='''				,    '''1.12.0'''	)				,    '''test requires torch version >= 1.12.0'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__=None				,    lowerCAmelCase__=None	):
					'''simple docstring'''
					if test_case is None:
										return partial(lowerCAmelCase__				,    version=lowerCAmelCase__	)
					return unittest.skipUnless(is_torch_version('''>='''				,    lowerCAmelCase__	)				,    f'test requires torch version >= {version}'	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_tensorboard_available()				,    '''test requires Tensorboard'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_wandb_available()				,    '''test requires wandb'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_comet_ml_available()				,    '''test requires comet_ml'''	)(lowerCAmelCase__	)


lowercase__	:Dict										=					(
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(
					    _atleast_one_tracker_available				,    '''test requires at least one tracker to be available and for `comet_ml` to not be installed'''				,    )(lowerCAmelCase__	)







class        lowercase	(      unittest.TestCase	):
							lowercase_ : int       =True




							@classmethod
							def 				A__   (       cls):
												lowercase					=		tempfile.mkdtemp()




							@classmethod
							def 				A__   (       cls):
												if os.path.exists(cls.tmpdir):
																	shutil.rmtree(cls.tmpdir)





							def 				A__   (       self):
												if self.clear_on_setup:
																	for path in Path(self.tmpdir).glob('''**/*'''):
																						if path.is_file():
																											path.unlink()
																						elif path.is_dir():
																											shutil.rmtree(A__)







class        lowercase	(      unittest.TestCase	):




							def 				A__   (       self):
												super().tearDown()
												# Reset the state of the AcceleratorState singleton.
												AcceleratorState._reset_state()
												PartialState._reset_state()







class        lowercase	(      unittest.TestCase	):




							def 				A__   (       self     ,A__):
												lowercase					=		mocks if isinstance(A__     ,(tuple, list)) else [mocks]
												for m in self.mocks:
																	m.start()
																	self.addCleanup(m.stop)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		AcceleratorState()
					lowercase					=		tensor[None].clone().to(state.device	)
					lowercase					=		gather(lowerCAmelCase__	).cpu()
					lowercase					=		tensor[0].cpu()
					for i in range(tensors.shape[0]	):
										if not torch.equal(tensors[i]				,    lowerCAmelCase__	):
															return False
					return True







class        lowercase	:




							def __init__(       self     ,A__     ,A__     ,A__):
												lowercase					=		returncode
												lowercase					=		stdout
												lowercase					=		stderr



async def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					while True:
										lowercase					=		await stream.readline()
										if line:
															callback(lowerCAmelCase__	)
										else:
															break



async def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=False				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					if echo:
										print('''\nRunning: '''				,    ''' '''.join(lowerCAmelCase__	)	)

					lowercase					=		await asyncio.create_subprocess_exec(
					    cmd[0]				,    *cmd[1:]				,    stdin=lowerCAmelCase__				,    stdout=asyncio.subprocess.PIPE				,    stderr=asyncio.subprocess.PIPE				,    env=lowerCAmelCase__				,    )

					# note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
					# https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
					#
					# If it starts hanging, will need to switch to the following code. The problem is that no data
					# will be seen until it's done and if it hangs for example there will be no debug info.
					# out, err = await p.communicate()
					# return _RunOutput(p.returncode, out, err)

					lowercase					=		[]
					lowercase					=		[]

					def tee(lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__=""	):
										lowercase					=		line.decode('''utf-8'''	).rstrip()
										sink.append(lowerCAmelCase__	)
										if not quiet:
															print(lowerCAmelCase__				,    lowerCAmelCase__				,    file=lowerCAmelCase__	)

    # XXX: the timeout doesn't seem to make any difference here
					await asyncio.wait(
					    [
					        asyncio.create_task(_read_stream(p.stdout				,    lambda lowerCAmelCase__	: tee(lowerCAmelCase__				,    lowerCAmelCase__				,    sys.stdout				,    label='''stdout:'''	)	)	),
					        asyncio.create_task(_read_stream(p.stderr				,    lambda lowerCAmelCase__	: tee(lowerCAmelCase__				,    lowerCAmelCase__				,    sys.stderr				,    label='''stderr:'''	)	)	),
					    ]				,    timeout=lowerCAmelCase__				,    )
					return _RunOutput(await p.wait()				,    lowerCAmelCase__				,    lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=180				,    lowerCAmelCase__=False				,    lowerCAmelCase__=True	):
					'''simple docstring'''
					lowercase					=		asyncio.get_event_loop()
					lowercase					=		loop.run_until_complete(
					    _stream_subprocess(lowerCAmelCase__				,    env=lowerCAmelCase__				,    stdin=lowerCAmelCase__				,    timeout=lowerCAmelCase__				,    quiet=lowerCAmelCase__				,    echo=lowerCAmelCase__	)	)

					lowercase					=		''' '''.join(lowerCAmelCase__	)
					if result.returncode > 0:
										lowercase					=		'''\n'''.join(result.stderr	)
										raise RuntimeError(
										    f'\'{cmd_str}\' failed with returncode {result.returncode}\n\n'
										    f'The combined stderr from workers follows:\n{stderr}'	)

					return result







class        lowercase	(      SCREAMING_SNAKE_CASE__	):
							pass



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					try:
										lowercase					=		subprocess.check_output(lowerCAmelCase__				,    stderr=subprocess.STDOUT	)
										if return_stdout:
															if hasattr(lowerCAmelCase__				,    '''decode'''	):
																				lowercase					=		output.decode('''utf-8'''	)
															return output
					except subprocess.CalledProcessError as e:
										raise SubprocessCallException(
										    f'Command `{" ".join(lowerCAmelCase__	)}` failed with the following error:\n\n{e.output.decode()}'	) from e




