


import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
			from transformers.models.rag.configuration_rag import RagConfig
			from transformers.models.rag.tokenization_rag import RagTokenizer

@require_faiss
@require_torch
class        a	(_lowerCAmelCase   ):




							"""simple docstring"""


							def 					__snake_case      (							self :						Dict       )			->					List[str]:
									__snake_case	:    Union[str, Any]											=     tempfile.mkdtemp()
									__snake_case	:    Dict											=     8

									# DPR tok
									__snake_case	:    Any											=     [
									    "[UNK]",
									    "[CLS]",
									    "[SEP]",
									    "[PAD]",
									    "[MASK]",
									    "want",
									    "##want",
									    "##ed",
									    "wa",
									    "un",
									    "runn",
									    "##ing",
									    ",",
									    "low",
									    "lowest",
									]
									__snake_case	:    int											=     os.path.join(self.tmpdirname					,			"dpr_tokenizer"       )
									os.makedirs(lowerCamelCase					,			exist_ok=lowerCamelCase       )
									__snake_case	:    Union[str, Any]											=     os.path.join(lowerCamelCase					,			DPR_VOCAB_FILES_NAMES["vocab_file"]       )
									with open(self.vocab_file					,			"w"					,			encoding="utf-8"       ) as vocab_writer:
											vocab_writer.write("".join([x + "\n" for x in vocab_tokens]       )       )

									# BART tok
									__snake_case	:    List[Any]											=     [
									    "l",
									    "o",
									    "w",
									    "e",
									    "r",
									    "s",
									    "t",
									    "i",
									    "d",
									    "n",
									    "\u0120",
									    "\u0120l",
									    "\u0120n",
									    "\u0120lo",
									    "\u0120low",
									    "er",
									    "\u0120lowest",
									    "\u0120newer",
									    "\u0120wider",
									    "<unk>",
									]
									__snake_case	:    int											=     dict(zip(lowerCamelCase					,			range(len(lowerCamelCase       )       )       )       )
									__snake_case	:    Optional[int]											=     ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
									__snake_case	:    Optional[int]											=     {"unk_token": "<unk>"}

									__snake_case	:    str											=     os.path.join(self.tmpdirname					,			"bart_tokenizer"       )
									os.makedirs(lowerCamelCase					,			exist_ok=lowerCamelCase       )
									__snake_case	:    Union[str, Any]											=     os.path.join(lowerCamelCase					,			BART_VOCAB_FILES_NAMES["vocab_file"]       )
									__snake_case	:    List[Any]											=     os.path.join(lowerCamelCase					,			BART_VOCAB_FILES_NAMES["merges_file"]       )
									with open(self.vocab_file					,			"w"					,			encoding="utf-8"       ) as fp:
											fp.write(json.dumps(lowerCamelCase       ) + "\n"       )
									with open(self.merges_file					,			"w"					,			encoding="utf-8"       ) as fp:
											fp.write("\n".join(lowerCamelCase       )       )

							def 					__snake_case      (							self :						Union[str, Any]       )			->					DPRQuestionEncoderTokenizer:
									return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname					,			"dpr_tokenizer"       )       )

							def 					__snake_case      (							self :						Any       )			->					BartTokenizer:
									return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname					,			"bart_tokenizer"       )       )

							def 					__snake_case      (							self :						Union[str, Any]       )			->					str:
									shutil.rmtree(self.tmpdirname       )

							@require_tokenizers
							def 					__snake_case      (							self :						List[Any]       )			->					Optional[Any]:
									__snake_case	:    Union[str, Any]											=     os.path.join(self.tmpdirname					,			"rag_tokenizer"       )
									__snake_case	:    Optional[Any]											=     RagConfig(question_encoder=DPRConfig().to_dict()					,			generator=BartConfig().to_dict()       )
									__snake_case	:    Tuple											=     RagTokenizer(question_encoder=self.get_dpr_tokenizer()					,			generator=self.get_bart_tokenizer()       )
									rag_config.save_pretrained(lowerCamelCase       )
									rag_tokenizer.save_pretrained(lowerCamelCase       )
									__snake_case	:    List[str]											=     RagTokenizer.from_pretrained(lowerCamelCase					,			config=lowerCamelCase       )
									self.assertIsInstance(new_rag_tokenizer.question_encoder					,			lowerCamelCase       )
									self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()					,			rag_tokenizer.question_encoder.get_vocab()       )
									self.assertIsInstance(new_rag_tokenizer.generator					,			lowerCamelCase       )
									self.assertEqual(new_rag_tokenizer.generator.get_vocab()					,			rag_tokenizer.generator.get_vocab()       )

							@slow
							def 					__snake_case      (							self :						Any       )			->					Optional[Any]:
									__snake_case	:    Dict											=     RagTokenizer.from_pretrained("facebook/rag-token-nq"       )
									__snake_case	:    List[str]											=     [
									    "who got the first nobel prize in physics",
									    "when is the next deadpool movie being released",
									    "which mode is used for short wave broadcast service",
									    "who is the owner of reading football club",
									    "when is the next scandal episode coming out",
									    "when is the last time the philadelphia won the superbowl",
									    "what is the most current adobe flash player version",
									    "how many episodes are there in dragon ball z",
									    "what is the first step in the evolution of the eye",
									    "where is gall bladder situated in human body",
									    "what is the main mineral in lithium batteries",
									    "who is the president of usa right now",
									    "where do the greasers live in the outsiders",
									    "panda is a national animal of which country",
									    "what is the name of manchester united stadium",
									]
									__snake_case	:    str											=     tokenizer(lowerCamelCase       )
									self.assertIsNotNone(lowerCamelCase       )






							@slow
							def 					__snake_case      (							self :						List[Any]       )			->					Dict:
									__snake_case	:    Optional[int]											=     RagTokenizer.from_pretrained("facebook/rag-sequence-nq"       )
									__snake_case	:    List[Any]											=     [
									    "who got the first nobel prize in physics",
									    "when is the next deadpool movie being released",
									    "which mode is used for short wave broadcast service",
									    "who is the owner of reading football club",
									    "when is the next scandal episode coming out",
									    "when is the last time the philadelphia won the superbowl",
									    "what is the most current adobe flash player version",
									    "how many episodes are there in dragon ball z",
									    "what is the first step in the evolution of the eye",
									    "where is gall bladder situated in human body",
									    "what is the main mineral in lithium batteries",
									    "who is the president of usa right now",
									    "where do the greasers live in the outsiders",
									    "panda is a national animal of which country",
									    "what is the name of manchester united stadium",
									]
									__snake_case	:    Tuple											=     tokenizer(lowerCamelCase       )
									self.assertIsNotNone(lowerCamelCase       )





import math







def        lowerCAmelCase_  (      __lowerCamelCase							,			__lowerCamelCase			):

							if initial_intensity < 0:
														raise ValueError("The value of intensity cannot be negative"			)
														# handling of negative values of initial intensity
							if angle < 0 or angle > 3_6_0:
														raise ValueError("In Malus Law, the angle is in the range 0-360 degrees"			)
														# handling of values out of allowed range
							return initial_intensity * (math.cos(math.radians(__lowerCamelCase			)			) ** 2)


if __name__ == "__main__":
			import doctest

			doctest.testmod(name="malus_law")

