


import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin




class 				lowerCamelCase__							(       _UpperCamelCase  ,		unittest.TestCase):




	'''simple docstring'''




	_A			=  CTRLTokenizer
	_A			=  False
	_A			=  False







	def      _lowerCamelCase       (      self	:List[str]		)	->				Any:
								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								__UpperCamelCase			:     Tuple         =      ["adapt", "re@@", "a@@", "apt", "c@@", "t", "<unk>"]
								__UpperCamelCase			:     Union[str, Any]         =      dict(zip(__a  ,     range(len(__a		)		)		)		)
								__UpperCamelCase			:     Any         =      ["#version: 0.2", "a p", "ap t</w>", "r e", "a d", "ad apt</w>", ""]
								__UpperCamelCase			:     List[Any]         =      {"unk_token": "<unk>"}

								__UpperCamelCase			:     List[Any]         =      os.path.join(self.tmpdirname  ,     VOCAB_FILES_NAMES["vocab_file"]		)
								__UpperCamelCase			:     Union[str, Any]         =      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      _lowerCamelCase       (      self	:Optional[int]  ,     **a	:List[Any]		)	->				List[Any]:
								kwargs.update(self.special_tokens_map		)
								return CTRLTokenizer.from_pretrained(self.tmpdirname  ,     **__a		)







	def      _lowerCamelCase       (      self	:str  ,     a	:int		)	->				List[Any]:
								__UpperCamelCase			:     str         =      "adapt react readapt apt"
								__UpperCamelCase			:     str         =      "adapt react readapt apt"
								return input_text, output_text







	def      _lowerCamelCase       (      self	:int		)	->				str:
								__UpperCamelCase			:     Tuple         =      CTRLTokenizer(self.vocab_file  ,     self.merges_file  ,     **self.special_tokens_map		)
								__UpperCamelCase			:     List[str]         =      "adapt react readapt apt"
								__UpperCamelCase			:     Dict         =      "adapt re@@ a@@ c@@ t re@@ adapt apt".split()
								__UpperCamelCase			:     List[Any]         =      tokenizer.tokenize(__a		)
								self.assertListEqual(__a  ,     __a		)

								__UpperCamelCase			:     List[str]         =      tokens + [tokenizer.unk_token]

								__UpperCamelCase			:     List[Any]         =      [0, 1, 2, 4, 5, 1, 0, 3, 6]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(__a		)  ,     __a		)

import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict




@dataclass
class 				lowerCamelCase__							(       __lowercase):




	'''simple docstring'''




	_A			=  ComputeEnvironment.AMAZON_SAGEMAKER
	_A			=  True
	_A			=  'ml.p3.2xlarge'
	_A			=  'accelerate_sagemaker_execution_role'
	_A			=  'hf-sm'
	_A			=  'us-east-1'
	_A			=  1
	_A			=  'accelerate-sagemaker-1'
	_A			=  '1.6'
	_A			=  '4.4'
	_A			=  'train.py'
	_A			=  [
	    '--model_name_or_path',
	    'bert',
	    '--do_train',
	    'False',
	    '--epochs',
	    '3',
	    '--learning_rate',
	    '5e-5',
	    '--max_steps',
	    '50.5',
	]
	_A			=  [
	    '--model_name_or_path',
	    'bert',
	    '--do_train',
	    '--do_test',
	    'False',
	    '--do_predict',
	    '--epochs',
	    '3',
	    '--learning_rate',
	    '5e-5',
	    '--max_steps',
	    '50.5',
	]




class 				lowerCamelCase__							(       unittest.TestCase):




	'''simple docstring'''




	def      _lowerCamelCase       (      self	:Tuple		)	->				str:
								# If no defaults are changed, `to_kwargs` returns an empty dict.
								__UpperCamelCase			:     str         =      _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args		)
								assert isinstance(converted_args["model_name_or_path"]  ,     a		)
								assert isinstance(converted_args["do_train"]  ,     a		)
								assert isinstance(converted_args["epochs"]  ,     a		)
								assert isinstance(converted_args["learning_rate"]  ,     a		)
								assert isinstance(converted_args["max_steps"]  ,     a		)

								with pytest.raises(a		):
															_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args		)