
import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class        lowercase	(      __snake_case ,						unittest.TestCase	):
							lowercase_ : str       =LEDTokenizer
							lowercase_ : Union[str, Any]       =LEDTokenizerFast
							lowercase_ : Tuple       =True




							def 				A__   (       self):
												super().setUp()
												lowercase					=		[
												    "l",
												    "o",
												    "w",
												    "e",
												    "r",
												    "s",
												    "t",
												    "i",
												    "d",
												    "n",
												    "\u0120",
												    "\u0120l",
												    "\u0120n",
												    "\u0120lo",
												    "\u0120low",
												    "er",
												    "\u0120lowest",
												    "\u0120newer",
												    "\u0120wider",
												    "<unk>",
												]
												lowercase					=		dict(zip(A_     ,range(len(A_))))
												lowercase					=		["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
												lowercase					=		{"unk_token": "<unk>"}

												lowercase					=		os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES['''vocab_file'''])
												lowercase					=		os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES['''merges_file'''])
												with open(self.vocab_file     ,'''w'''     ,encoding='''utf-8''') as fp:
																	fp.write(json.dumps(A_) + '''\n''')
												with open(self.merges_file     ,'''w'''     ,encoding='''utf-8''') as fp:
																	fp.write('''\n'''.join(A_))




							def 				A__   (       self     ,**A__):
												kwargs.update(self.special_tokens_map)
												return self.tokenizer_class.from_pretrained(self.tmpdirname     ,**A_)




							def 				A__   (       self     ,**A__):
												kwargs.update(self.special_tokens_map)
												return self.rust_tokenizer_class.from_pretrained(self.tmpdirname     ,**A_)




							def 				A__   (       self     ,A__):
												return "lower newer", "lower newer"




							@cached_property
							def 				A__   (       self):
												return LEDTokenizer.from_pretrained('''allenai/led-base-16384''')




							@cached_property
							def 				A__   (       self):
												return LEDTokenizerFast.from_pretrained('''allenai/led-base-16384''')




							@require_torch
							def 				A__   (       self):
												lowercase					=		["A long paragraph for summarization.", "Another paragraph for summarization."]
												lowercase					=		[0, 2_5_0, 2_5_1, 1_7_8_1_8, 1_3, 3_9_1_8_6, 1_9_3_8, 4, 2]

												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase					=		tokenizer(A_     ,max_length=len(A_)     ,padding=A_     ,return_tensors='''pt''')
																	self.assertIsInstance(A_     ,A_)

																	self.assertEqual((2, 9)     ,batch.input_ids.shape)
																	self.assertEqual((2, 9)     ,batch.attention_mask.shape)
																	lowercase					=		batch.input_ids.tolist()[0]
																	self.assertListEqual(A_     ,A_)




							@require_torch
							def 				A__   (       self):
												lowercase					=		["A long paragraph for summarization.", "Another paragraph for summarization."]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase					=		tokenizer(A_     ,padding=A_     ,return_tensors='''pt''')
																	self.assertIn('''input_ids'''     ,A_)
																	self.assertIn('''attention_mask'''     ,A_)
																	self.assertNotIn('''labels'''     ,A_)
																	self.assertNotIn('''decoder_attention_mask'''     ,A_)




							@require_torch
							def 				A__   (       self):
												lowercase					=		[
												    "Summary of the text.",
												    "Another summary.",
												]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase					=		tokenizer(text_target=A_     ,max_length=3_2     ,padding='''max_length'''     ,return_tensors='''pt''')
																	self.assertEqual(3_2     ,targets['''input_ids'''].shape[1])




							@require_torch
							def 				A__   (       self):




												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase					=		tokenizer(
																	    ['''I am a small frog''' * 1_0_2_4, '''I am a small frog''']     ,padding=A_     ,truncation=A_     ,return_tensors='''pt''')
																	self.assertIsInstance(A_     ,A_)
																	self.assertEqual(batch.input_ids.shape     ,(2, 5_1_2_2))




							@require_torch
							def 				A__   (       self):
												lowercase					=		["A long paragraph for summarization."]
												lowercase					=		[
												    "Summary of the text.",
												]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase					=		tokenizer(A_     ,return_tensors='''pt''')
																	lowercase					=		tokenizer(text_target=A_     ,return_tensors='''pt''')
																	lowercase					=		inputs["input_ids"]
																	lowercase					=		targets["input_ids"]
																	self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item())
																	self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item())
																	self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item())
																	self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item())




							@require_torch
							def 				A__   (       self):




												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase					=		["Summary of the text.", "Another summary."]
																	lowercase					=		[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

																	lowercase					=		tokenizer(A_     ,padding=A_)
																	lowercase					=		[[0] * len(A_) for x in encoded_output["input_ids"]]
																	lowercase					=		tokenizer.pad(A_)
																	self.assertSequenceEqual(outputs['''global_attention_mask''']     ,A_)




							def 				A__   (       self):
												pass





							def 				A__   (       self):




												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
																						lowercase					=		self.rust_tokenizer_class.from_pretrained(A_     ,**A_)
																						lowercase					=		self.tokenizer_class.from_pretrained(A_     ,**A_)
																						lowercase					=		"A, <mask> AllenNLP sentence."
																						lowercase					=		tokenizer_r.encode_plus(A_     ,add_special_tokens=A_     ,return_token_type_ids=A_)
																						lowercase					=		tokenizer_p.encode_plus(A_     ,add_special_tokens=A_     ,return_token_type_ids=A_)
																						self.assertEqual(sum(tokens_r['''token_type_ids'''])     ,sum(tokens_p['''token_type_ids''']))
																						self.assertEqual(
																						    sum(tokens_r['''attention_mask''']) / len(tokens_r['''attention_mask'''])     ,sum(tokens_p['''attention_mask''']) / len(tokens_p['''attention_mask'''])     ,)

																						lowercase					=		tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids'''])
																						lowercase					=		tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids'''])
																						self.assertSequenceEqual(tokens_p['''input_ids''']     ,[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2])
																						self.assertSequenceEqual(tokens_r['''input_ids''']     ,[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2])

																						self.assertSequenceEqual(
																						    A_     ,['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''])
																						self.assertSequenceEqual(
																						    A_     ,['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''])






# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


lowercase__	:Any										=					"Run commands across TPU VMs for initial setup before running `accelerate launch`."



def  UpperCamelCase					(							lowerCAmelCase__=None	):
					'''simple docstring'''
					if subparsers is not None:
										lowercase					=		subparsers.add_parser('''tpu-config'''				,    description=_description	)
					else:
										lowercase					=		argparse.ArgumentParser('''Accelerate tpu-config command'''				,    description=_description	)
					# Core arguments
					lowercase					=		parser.add_argument_group(
					    '''Config Arguments'''				,    '''Arguments that can be configured through `accelerate config`.'''	)
					config_args.add_argument(
					    '''--config_file'''				,    type=lowerCAmelCase__				,    default=lowerCAmelCase__				,    help='''Path to the config file to use for accelerate.'''				,    )
					config_args.add_argument(
					    '''--tpu_name'''				,    default=lowerCAmelCase__				,    help='''The name of the TPU to use. If not specified, will use the TPU specified in the config file.'''				,    )
					config_args.add_argument(
					    '''--tpu_zone'''				,    default=lowerCAmelCase__				,    help='''The zone of the TPU to use. If not specified, will use the zone specified in the config file.'''				,    )
					lowercase					=		parser.add_argument_group('''TPU Arguments'''				,    '''Arguments for options ran inside the TPU.'''	)
					pod_args.add_argument(
					    '''--use_alpha'''				,    action='''store_true'''				,    help='''Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`.'''				,    )
					pod_args.add_argument(
					    '''--command_file'''				,    default=lowerCAmelCase__				,    help='''The path to the file containing the commands to run on the pod on startup.'''				,    )
					pod_args.add_argument(
					    '''--command'''				,    action='''append'''				,    nargs='''+'''				,    help='''A command to run on the pod. Can be passed multiple times.'''				,    )
					pod_args.add_argument(
					    '''--install_accelerate'''				,    action='''store_true'''				,    help='''Whether to install accelerate on the pod. Defaults to False.'''				,    )
					pod_args.add_argument(
					    '''--accelerate_version'''				,    default='''latest'''				,    help='''The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify \'dev\' to install from GitHub.'''				,    )
					pod_args.add_argument(
					    '''--debug'''				,    action='''store_true'''				,    help='''If set, will print the command that would be run instead of running it.'''	)

					if subparsers is not None:
										parser.set_defaults(func=lowerCAmelCase__	)
					return parser



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		None

					# Get the default from the config file if it exists.
					if args.config_file is not None or os.path.isfile(lowerCAmelCase__	):
										lowercase					=		load_config_from_file(args.config_file	)
										if not args.command_file and defaults.command_file is not None and not args.command:
															lowercase					=		defaults.command_file
										if not args.command and defaults.commands is not None:
															lowercase					=		defaults.commands
										if not args.tpu_name:
															lowercase					=		defaults.tpu_name
										if not args.tpu_zone:
															lowercase					=		defaults.tpu_zone
					if args.accelerate_version == "dev":
										lowercase					=		'''git+https://github.com/huggingface/accelerate.git'''
					elif args.accelerate_version == "latest":
										lowercase					=		'''accelerate -U'''
					elif isinstance(parse(args.accelerate_version	)				,    lowerCAmelCase__	):
										lowercase					=		f'accelerate=={args.accelerate_version}'

					if not args.command_file and not args.command:
										raise ValueError('''You must specify either a command file or a command to run on the pod.'''	)

					if args.command_file:
										with open(args.command_file				,    '''r'''	) as f:
															lowercase					=		[f.read().splitlines()]

    # To turn list of lists into list of strings
					if isinstance(args.command[0]				,    lowerCAmelCase__	):
										lowercase					=		[line for cmd in args.command for line in cmd]
					# Default to the shared folder and install accelerate
					lowercase					=		['''cd /usr/share''']
					if args.install_accelerate:
										new_cmd += [f'pip install {args.accelerate_version}']
					new_cmd += args.command
					lowercase					=		'''; '''.join(lowerCAmelCase__	)

					# Then send it to gcloud
					# Eventually try to use google-api-core to do this instead of subprocess
					lowercase					=		['''gcloud''']
					if args.use_alpha:
										cmd += ["alpha"]
					cmd += [
					    "compute",
					    "tpus",
					    "tpu-vm",
					    "ssh",
					    args.tpu_name,
					    "--zone",
					    args.tpu_zone,
					    "--command",
					    args.command,
					    "--worker",
					    "all",
					]
					if args.debug:
										print(f'Running {" ".join(lowerCAmelCase__	)}'	)
										return
					subprocess.run(lowerCAmelCase__	)
					print('''Successfully setup pod.'''	)



def  UpperCamelCase					(							):
					'''simple docstring'''
					lowercase					=		tpu_command_parser()
					lowercase					=		parser.parse_args()

					tpu_command_launcher(lowerCAmelCase__	)




