


import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase			=							get_tests_dir('''fixtures/test_sentencepiece_no_bos.model''')





@require_sentencepiece
@require_tokenizers
class   __a      (   __UpperCamelCase	,	unittest.TestCase				):
 __lowercase			:							Tuple       					=			PegasusTokenizer
 __lowercase			:							str       					=			PegasusTokenizerFast
 __lowercase			:							Optional[Any]       					=			True
 __lowercase			:							Dict       					=			True
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase__:       int        =       PegasusTokenizer(lowerCAmelCase__			)
        tokenizer.save_pretrained(self.tmpdirname			)
 @cached_property
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Dict:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained('google/pegasus-large'			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			**lowerCAmelCase__			) ->    PegasusTokenizer:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained(self.tmpdirname    ,			**lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__			) ->    Union[str, Any]:




        '''simple docstring'''
        return ("This is a test", "This is a test")
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[str]:




        '''simple docstring'''
        lowercase__:       str        =       '</s>'
        lowercase__:       Any        =       1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase__			)    ,			lowerCAmelCase__			)
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase__			)    ,			lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Dict:




        '''simple docstring'''
        lowercase__:       int        =       list(self.get_tokenizer().get_vocab().keys()			)

        self.assertEqual(vocab_keys[0]    ,			'<pad>'			)
        self.assertEqual(vocab_keys[1]    ,			'</s>'			)
        self.assertEqual(vocab_keys[-1]    ,			'v'			)
        self.assertEqual(len(lowerCAmelCase__			)    ,			1_103			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Tuple:




        '''simple docstring'''
        self.assertEqual(self.get_tokenizer().vocab_size    ,			1_103			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[Any]:




        '''simple docstring'''
        lowercase__:       Optional[int]        =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname			)
        lowercase__:       Optional[Any]        =       self.tokenizer_class.from_pretrained(self.tmpdirname			)
        lowercase__:       Optional[int]        =       (
            'Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important'
            ' </s> <pad> <pad> <pad>'
        )
        lowercase__:       Tuple        =       rust_tokenizer([raw_input_str]    ,			return_tensors=lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			).input_ids[0]
        lowercase__:       str        =       py_tokenizer([raw_input_str]    ,			return_tensors=lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			).input_ids[0]
        self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Union[str, Any]:




        '''simple docstring'''
        lowercase__:       List[Any]        =       self._large_tokenizer
        # <mask_1> masks whole sentence while <mask_2> masks single word
        lowercase__:       Union[str, Any]        =       '<mask_1> To ensure a <mask_2> flow of bank resolutions.'
        lowercase__:       str        =       [2, 413, 615, 114, 3, 1_971, 113, 1_679, 10_710, 107, 1]
        lowercase__:       Tuple        =       tokenizer([raw_input_str]    ,			return_tensors=lowerCAmelCase__			).input_ids[0]
        self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        lowercase__:       int        =       self._large_tokenizer
        # The tracebacks for the following asserts are **better** without messages or self.assertEqual
        assert tokenizer.vocab_size == 96_103
        assert tokenizer.pad_token_id == 0
        assert tokenizer.eos_token_id == 1
        assert tokenizer.offset == 103
        assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
        assert tokenizer.unk_token == "<unk>"
        assert tokenizer.model_max_length == 1_024
        lowercase__:       int        =       'To ensure a smooth flow of bank resolutions.'
        lowercase__:       Optional[int]        =       [413, 615, 114, 2_291, 1_971, 113, 1_679, 10_710, 107, 1]
        lowercase__:       Dict        =       tokenizer([raw_input_str]    ,			return_tensors=lowerCAmelCase__			).input_ids[0]
        self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)
        assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]			) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]
 @require_torch
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[Any]:




        '''simple docstring'''
        lowercase__:       Dict        =       ['This is going to be way too long.' * 150, 'short example']
        lowercase__:       Dict        =       ['not super long but more than 5 tokens', 'tiny']
        lowercase__:       Optional[Any]        =       self._large_tokenizer(lowerCAmelCase__    ,			padding=lowerCAmelCase__    ,			truncation=lowerCAmelCase__    ,			return_tensors='pt'			)
        lowercase__:       Optional[int]        =       self._large_tokenizer(
            text_target=lowerCAmelCase__    ,			max_length=5    ,			padding=lowerCAmelCase__    ,			truncation=lowerCAmelCase__    ,			return_tensors='pt'			)

        assert batch.input_ids.shape == (2, 1_024)
        assert batch.attention_mask.shape == (2, 1_024)
        assert targets["input_ids"].shape == (2, 5)
        assert len(lowerCAmelCase__			) == 2  # input_ids, attention_mask.
 @slow
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Tuple:




        '''simple docstring'''
        # fmt: off
        lowercase__:       Optional[Any]        =       {'input_ids': [[38_979, 143, 18_485, 606, 130, 26_669, 87_686, 121, 54_189, 1_129, 111, 26_669, 87_686, 121, 9_114, 14_787, 121, 13_249, 158, 592, 956, 121, 14_621, 31_576, 143, 62_613, 108, 9_688, 930, 43_430, 11_562, 62_613, 304, 108, 11_443, 897, 108, 9_314, 17_415, 63_399, 108, 11_443, 7_614, 18_316, 118, 4_284, 7_148, 12_430, 143, 1_400, 25_703, 158, 111, 4_284, 7_148, 11_772, 143, 21_297, 1_064, 158, 122, 204, 3_506, 1_754, 1_133, 14_787, 1_581, 115, 33_224, 4_482, 111, 1_355, 110, 29_173, 317, 50_833, 108, 20_147, 94_665, 111, 77_198, 107, 1], [110, 62_613, 117, 638, 112, 1_133, 121, 20_098, 1_355, 79_050, 13_872, 135, 1_596, 53_541, 1_352, 141, 13_039, 5_542, 124, 302, 518, 111, 268, 2_956, 115, 149, 4_427, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [139, 1_235, 2_799, 18_289, 17_780, 204, 109, 9_474, 1_296, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
        # fmt: on

        self.tokenizer_integration_test_util(
            expected_encoding=lowerCAmelCase__    ,			model_name='google/bigbird-pegasus-large-arxiv'    ,			revision='ba85d0851d708441f91440d509690f1ab6353415'    ,			)





@require_sentencepiece
@require_tokenizers
class   __a      (   __UpperCamelCase	,	unittest.TestCase				):
 __lowercase			:							List[Any]       					=			PegasusTokenizer
 __lowercase			:							Optional[int]       					=			PegasusTokenizerFast
 __lowercase			:							Optional[Any]       					=			True
 __lowercase			:							Any       					=			True
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[Any]:




        '''simple docstring'''
        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase__:       Dict        =       PegasusTokenizer(lowerCAmelCase__    ,			offset=0    ,			mask_token_sent=lowerCAmelCase__    ,			mask_token='[MASK]'			)
        tokenizer.save_pretrained(self.tmpdirname			)
 @cached_property
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[int]:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained('google/bigbird-pegasus-large-arxiv'			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			**lowerCAmelCase__			) ->    PegasusTokenizer:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained(self.tmpdirname    ,			**lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__			) ->    Union[str, Any]:




        '''simple docstring'''
        return ("This is a test", "This is a test")
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Dict:




        '''simple docstring'''
        lowercase__:       Tuple        =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname			)
        lowercase__:       Optional[int]        =       self.tokenizer_class.from_pretrained(self.tmpdirname			)
        lowercase__:       List[str]        =       (
            'Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'
            ' <pad> <pad> <pad>'
        )
        lowercase__:       List[Any]        =       rust_tokenizer([raw_input_str]    ,			return_tensors=lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			).input_ids[0]
        lowercase__:       Optional[Any]        =       py_tokenizer([raw_input_str]    ,			return_tensors=lowerCAmelCase__    ,			add_special_tokens=lowerCAmelCase__			).input_ids[0]
        self.assertListEqual(lowerCAmelCase__    ,			lowerCAmelCase__			)
 @require_torch
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Union[str, Any]:




        '''simple docstring'''
        lowercase__:       Optional[Any]        =       ['This is going to be way too long.' * 1_000, 'short example']
        lowercase__:       Any        =       ['not super long but more than 5 tokens', 'tiny']
        lowercase__:       Dict        =       self._large_tokenizer(lowerCAmelCase__    ,			padding=lowerCAmelCase__    ,			truncation=lowerCAmelCase__    ,			return_tensors='pt'			)
        lowercase__:       str        =       self._large_tokenizer(
            text_target=lowerCAmelCase__    ,			max_length=5    ,			padding=lowerCAmelCase__    ,			truncation=lowerCAmelCase__    ,			return_tensors='pt'			)

        assert batch.input_ids.shape == (2, 4_096)
        assert batch.attention_mask.shape == (2, 4_096)
        assert targets["input_ids"].shape == (2, 5)
        assert len(lowerCAmelCase__			) == 2  # input_ids, attention_mask.
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Union[str, Any]:




        '''simple docstring'''
        lowercase__:       str        =       (
            'This is an example string that is used to test the original TF implementation against the HF'
            ' implementation'
        )

        lowercase__:       str        =       self._large_tokenizer(lowerCAmelCase__			).input_ids

        self.assertListEqual(
            lowerCAmelCase__    ,			[182, 117, 142, 587, 4_211, 120, 117, 263, 112, 804, 109, 856, 25_016, 3_137, 464, 109, 26_955, 3_137, 1]    ,			)






from __future__ import annotations

from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray




def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case = False					)  ->    list[float]:
       if radian_mode:
              return [magnitude * cos(snake_case					), magnitude * sin(snake_case					)]
       return [magnitude * cos(radians(snake_case					)					), magnitude * sin(radians(snake_case					)					)]




def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case = 10**-1					)  ->    bool:
       lowercase__:       NDArray[floataa]        =       cross(snake_case      ,							snake_case					)
       lowercase__:       float        =       sum(snake_case					)
       return abs(snake_case					) < eps


if __name__ == "__main__":
 # Test to check if it works
 __lowerCAmelCase			=							array(
     [
         polar_force(718.4, 1_80 - 30),
         polar_force(879.54, 45),
         polar_force(1_00, -90),
     ]
 )

 __lowerCAmelCase			=							array([[0, 0], [0, 0], [0, 0]])

 assert in_static_equilibrium(forces, location)

 # Problem 1 in image_data/2D_problems.jpg
 __lowerCAmelCase			=							array(
     [
         polar_force(30 * 9.81, 15),
         polar_force(2_15, 1_80 - 45),
         polar_force(2_64, 90 - 30),
     ]
 )

 __lowerCAmelCase			=							array([[0, 0], [0, 0], [0, 0]])

 assert in_static_equilibrium(forces, location)

 # Problem in image_data/2D_problems_1.jpg
 __lowerCAmelCase			=							array([[0, -20_00], [0, -12_00], [0, 1_56_00], [0, -1_24_00]])

 __lowerCAmelCase			=							array([[0, 0], [6, 0], [10, 0], [12, 0]])

 assert in_static_equilibrium(forces, location)

 import doctest

 doctest.testmod()


