


'''simple docstring'''







import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase     :  Optional[Any]											=    get_tests_dir("""fixtures/test_sentencepiece.model""")

if is_torch_available():
       from transformers.models.mbart.modeling_mbart import shift_tokens_right

lowerCAmelCase     :  Any											=    25_00_04
lowerCAmelCase     :  Union[str, Any]											=    25_00_20
@require_sentencepiece
@require_tokenizers
class 						UpperCamelCase__       (			SCREAMING_SNAKE_CASE_     ,       unittest.TestCase						):



     """simple docstring"""






     __magic_name__           =     MBartaaTokenizer
     __magic_name__           =     MBartaaTokenizerFast
     __magic_name__           =     True
     __magic_name__           =     True







     def a						(			self ):

            '''simple docstring'''

            super().setUp()

            # We have a SentencePiece fixture for testing
            _lowerCAmelCase     :				int       =							MBartaaTokenizer(snake_case__   ,						src_lang='en_XX'   ,						tgt_lang='ro_RO'   ,						keep_accents=snake_case__ )
            tokenizer.save_pretrained(self.tmpdirname )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Tuple       =							'<s>'
            _lowerCAmelCase     :				List[Any]       =							0

            self.assertEqual(self.get_tokenizer()._convert_token_to_id(snake_case__ )   ,						snake_case__ )
            self.assertEqual(self.get_tokenizer()._convert_id_to_token(snake_case__ )   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[str]       =							list(self.get_tokenizer().get_vocab().keys() )

            self.assertEqual(vocab_keys[0]   ,						'<s>' )
            self.assertEqual(vocab_keys[1]   ,						'<pad>' )
            self.assertEqual(vocab_keys[-1]   ,						'<mask>' )
            self.assertEqual(len(snake_case__ )   ,						1054 )







     def a						(			self ):

            '''simple docstring'''

            self.assertEqual(self.get_tokenizer().vocab_size   ,						1054 )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				int       =							MBartaaTokenizer(snake_case__   ,						src_lang='en_XX'   ,						tgt_lang='ro_RO'   ,						keep_accents=snake_case__ )

            _lowerCAmelCase     :				str       =							tokenizer.tokenize('This is a test' )
            self.assertListEqual(snake_case__   ,						['▁This', '▁is', '▁a', '▁t', 'est'] )

            self.assertListEqual(
                tokenizer.convert_tokens_to_ids(snake_case__ )   ,						[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,						)

            _lowerCAmelCase     :				str       =							tokenizer.tokenize('I was born in 92000, and this is falsé.' )
            self.assertListEqual(
                snake_case__   ,						[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']   ,						)
            _lowerCAmelCase     :				List[Any]       =							tokenizer.convert_tokens_to_ids(snake_case__ )
            self.assertListEqual(
                snake_case__   ,						[
                    value + tokenizer.fairseq_offset
                    for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                ]   ,						)

            _lowerCAmelCase     :				List[str]       =							tokenizer.convert_ids_to_tokens(snake_case__ )
            self.assertListEqual(
                snake_case__   ,						[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']   ,						)







     @slow
     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[Any]       =							{'input_ids': [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 5, 2, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 5, 2, 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]], '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, 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, 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, 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, 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=snake_case__   ,						model_name='facebook/mbart-large-50'   ,						revision='d3913889c59cd5c9e456b269c376325eabad57e2'   ,						)







     def a						(			self ):

            '''simple docstring'''

            if not self.test_slow_tokenizer:
                   # as we don't have a slow version, we can't compare the outputs between slow and fast versions
                   return

            _lowerCAmelCase     :				Any       =							(self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                   with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})' ):
                          _lowerCAmelCase     :				List[Any]       =							self.rust_tokenizer_class.from_pretrained(snake_case__   ,						**snake_case__ )
                          _lowerCAmelCase     :				Optional[int]       =							self.tokenizer_class.from_pretrained(snake_case__   ,						**snake_case__ )

                          _lowerCAmelCase     :				Optional[int]       =							tempfile.mkdtemp()

                          _lowerCAmelCase     :				Optional[int]       =							tokenizer_r.save_pretrained(snake_case__ )
                          _lowerCAmelCase     :				List[str]       =							tokenizer_p.save_pretrained(snake_case__ )

                          # Checks it save with the same files + the tokenizer.json file for the fast one
                          self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files ) )
                          _lowerCAmelCase     :				Union[str, Any]       =							tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f )
                          self.assertSequenceEqual(snake_case__   ,						snake_case__ )

                          # Checks everything loads correctly in the same way
                          _lowerCAmelCase     :				Dict       =							tokenizer_r.from_pretrained(snake_case__ )
                          _lowerCAmelCase     :				Dict       =							tokenizer_p.from_pretrained(snake_case__ )

                          # Check special tokens are set accordingly on Rust and Python
                          for key in tokenizer_pp.special_tokens_map:
                                 self.assertTrue(hasattr(snake_case__   ,						snake_case__ ) )
                                 # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                                 # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                          shutil.rmtree(snake_case__ )

                          # Save tokenizer rust, legacy_format=True
                          _lowerCAmelCase     :				Dict       =							tempfile.mkdtemp()

                          _lowerCAmelCase     :				Union[str, Any]       =							tokenizer_r.save_pretrained(snake_case__   ,						legacy_format=snake_case__ )
                          _lowerCAmelCase     :				List[Any]       =							tokenizer_p.save_pretrained(snake_case__ )

                          # Checks it save with the same files
                          self.assertSequenceEqual(snake_case__   ,						snake_case__ )

                          # Checks everything loads correctly in the same way
                          _lowerCAmelCase     :				Union[str, Any]       =							tokenizer_r.from_pretrained(snake_case__ )
                          _lowerCAmelCase     :				Optional[Any]       =							tokenizer_p.from_pretrained(snake_case__ )

                          # Check special tokens are set accordingly on Rust and Python
                          for key in tokenizer_pp.special_tokens_map:
                                 self.assertTrue(hasattr(snake_case__   ,						snake_case__ ) )

                          shutil.rmtree(snake_case__ )

                          # Save tokenizer rust, legacy_format=False
                          _lowerCAmelCase     :				Optional[Any]       =							tempfile.mkdtemp()

                          _lowerCAmelCase     :				List[str]       =							tokenizer_r.save_pretrained(snake_case__   ,						legacy_format=snake_case__ )
                          _lowerCAmelCase     :				Optional[Any]       =							tokenizer_p.save_pretrained(snake_case__ )

                          # Checks it saved the tokenizer.json file
                          self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files ) )

                          # Checks everything loads correctly in the same way
                          _lowerCAmelCase     :				List[str]       =							tokenizer_r.from_pretrained(snake_case__ )
                          _lowerCAmelCase     :				Tuple       =							tokenizer_p.from_pretrained(snake_case__ )

                          # Check special tokens are set accordingly on Rust and Python
                          for key in tokenizer_pp.special_tokens_map:
                                 self.assertTrue(hasattr(snake_case__   ,						snake_case__ ) )

                          shutil.rmtree(snake_case__ )
@require_torch
@require_sentencepiece
@require_tokenizers
class 						UpperCamelCase__       (			unittest.TestCase						):



     """simple docstring"""






     __magic_name__           =     "facebook/mbart-large-50-one-to-many-mmt"
     __magic_name__           =     [
         " UN Chief Says There Is No Military Solution in Syria",
         " Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.",
     ]
     __magic_name__           =     [
         "Şeful ONU declară că nu există o soluţie militară în Siria",
         "Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"
         " pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"
         " face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.",
     ]
     __magic_name__           =     [EN_CODE, 8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2]







     @classmethod
     def a						(			cls ):

            '''simple docstring'''

            _lowerCAmelCase     :				MBartaaTokenizer       =							MBartaaTokenizer.from_pretrained(
                cls.checkpoint_name   ,						src_lang='en_XX'   ,						tgt_lang='ro_RO' )
            _lowerCAmelCase     :				str       =							1
            return cls







     def a						(			self ):

            '''simple docstring'''

            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']   ,						25_0001 )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']   ,						25_0004 )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']   ,						25_0020 )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']   ,						25_0038 )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				int       =							self.tokenizer.batch_encode_plus(self.src_text ).input_ids[0]
            self.assertListEqual(self.expected_src_tokens   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            self.assertIn(snake_case__   ,						self.tokenizer.all_special_ids )
            _lowerCAmelCase     :				List[str]       =							[RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
            _lowerCAmelCase     :				Dict       =							self.tokenizer.decode(snake_case__   ,						skip_special_tokens=snake_case__ )
            _lowerCAmelCase     :				Tuple       =							self.tokenizer.decode(generated_ids[1:]   ,						skip_special_tokens=snake_case__ )
            self.assertEqual(snake_case__   ,						snake_case__ )
            self.assertNotIn(self.tokenizer.eos_token   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[str]       =							['this is gunna be a long sentence ' * 20]
            assert isinstance(src_text[0]   ,						snake_case__ )
            _lowerCAmelCase     :				Union[str, Any]       =							10
            _lowerCAmelCase     :				Any       =							self.tokenizer(snake_case__   ,						max_length=snake_case__   ,						truncation=snake_case__ ).input_ids[0]
            self.assertEqual(ids[0]   ,						snake_case__ )
            self.assertEqual(ids[-1]   ,						2 )
            self.assertEqual(len(snake_case__ )   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR'] )   ,						[25_0053, 25_0001] )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[str]       =							tempfile.mkdtemp()
            _lowerCAmelCase     :				List[str]       =							self.tokenizer.fairseq_tokens_to_ids
            self.tokenizer.save_pretrained(snake_case__ )
            _lowerCAmelCase     :				Union[str, Any]       =							MBartaaTokenizer.from_pretrained(snake_case__ )
            self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,						snake_case__ )







     @require_torch
     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				str       =							self.tokenizer(self.src_text   ,						text_target=self.tgt_text   ,						padding=snake_case__   ,						return_tensors='pt' )
            _lowerCAmelCase     :				List[Any]       =							shift_tokens_right(batch['labels']   ,						self.tokenizer.pad_token_id )

            # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
            assert batch.input_ids[1][0] == EN_CODE
            assert batch.input_ids[1][-1] == 2
            assert batch.labels[1][0] == RO_CODE
            assert batch.labels[1][-1] == 2
            assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]







     @require_torch
     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Any       =							self.tokenizer(
                self.src_text   ,						text_target=self.tgt_text   ,						padding=snake_case__   ,						truncation=snake_case__   ,						max_length=len(self.expected_src_tokens )   ,						return_tensors='pt'   ,						)
            _lowerCAmelCase     :				Dict       =							shift_tokens_right(batch['labels']   ,						self.tokenizer.pad_token_id )

            self.assertIsInstance(snake_case__   ,						snake_case__ )

            self.assertEqual((2, 14)   ,						batch.input_ids.shape )
            self.assertEqual((2, 14)   ,						batch.attention_mask.shape )
            _lowerCAmelCase     :				str       =							batch.input_ids.tolist()[0]
            self.assertListEqual(self.expected_src_tokens   ,						snake_case__ )
            self.assertEqual(2   ,						batch.decoder_input_ids[0, 0] )  # decoder_start_token_id
            # Test that special tokens are reset
            self.assertEqual(self.tokenizer.prefix_tokens   ,						[EN_CODE] )
            self.assertEqual(self.tokenizer.suffix_tokens   ,						[self.tokenizer.eos_token_id] )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Any       =							self.tokenizer(self.src_text   ,						padding=snake_case__   ,						truncation=snake_case__   ,						max_length=3   ,						return_tensors='pt' )
            _lowerCAmelCase     :				int       =							self.tokenizer(
                text_target=self.tgt_text   ,						padding=snake_case__   ,						truncation=snake_case__   ,						max_length=10   ,						return_tensors='pt' )
            _lowerCAmelCase     :				Tuple       =							targets['input_ids']
            _lowerCAmelCase     :				Union[str, Any]       =							shift_tokens_right(snake_case__   ,						self.tokenizer.pad_token_id )

            self.assertEqual(batch.input_ids.shape[1]   ,						3 )
            self.assertEqual(batch.decoder_input_ids.shape[1]   ,						10 )







     @require_torch
     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[str]       =							self.tokenizer._build_translation_inputs(
                'A test'   ,						return_tensors='pt'   ,						src_lang='en_XX'   ,						tgt_lang='ar_AR' )

            self.assertEqual(
                nested_simplify(snake_case__ )   ,						{
                    # en_XX, A, test, EOS
                    'input_ids': [[25_0004, 62, 3034, 2]],
                    'attention_mask': [[1, 1, 1, 1]],
                    # ar_AR
                    'forced_bos_token_id': 25_0001,
                }   ,						)





'''simple docstring'''







from math import pi, sqrt, tan






def       lowercase					(_A       ):







       """simple docstring"""







       if side_length < 0:
              raise ValueError('surface_area_cube() only accepts non-negative values'       )
       return 6 * side_length**2






def       lowercase					(_A ,    _A ,    _A       ):







       """simple docstring"""







       if length < 0 or breadth < 0 or height < 0:
              raise ValueError('surface_area_cuboid() only accepts non-negative values'       )
       return 2 * ((length * breadth) + (breadth * height) + (length * height))






def       lowercase					(_A       ):







       """simple docstring"""







       if radius < 0:
              raise ValueError('surface_area_sphere() only accepts non-negative values'       )
       return 4 * pi * radius**2






def       lowercase					(_A       ):







       """simple docstring"""







       if radius < 0:
              raise ValueError('surface_area_hemisphere() only accepts non-negative values'       )
       return 3 * pi * radius**2






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if radius < 0 or height < 0:
              raise ValueError('surface_area_cone() only accepts non-negative values'       )
       return pi * radius * (radius + (height**2 + radius**2) ** 0.5)






def       lowercase					(_A ,    _A ,    _A       ):







       """simple docstring"""







       if radius_a < 0 or radius_a < 0 or height < 0:
              raise ValueError(
                  'surface_area_conical_frustum() only accepts non-negative values'       )
       _lowerCAmelCase     :				int       =							(height**2 + (radius_a - radius_a) ** 2) ** 0.5
       return pi * ((slant_height * (radius_a + radius_a)) + radius_a**2 + radius_a**2)






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if radius < 0 or height < 0:
              raise ValueError('surface_area_cylinder() only accepts non-negative values'       )
       return 2 * pi * radius * (height + radius)






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if torus_radius < 0 or tube_radius < 0:
              raise ValueError('surface_area_torus() only accepts non-negative values'       )
       if torus_radius < tube_radius:
              raise ValueError(
                  'surface_area_torus() does not support spindle or self intersecting tori'       )
       return 4 * pow(_A ,    2       ) * torus_radius * tube_radius






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if length < 0 or width < 0:
              raise ValueError('area_rectangle() only accepts non-negative values'       )
       return length * width






def       lowercase					(_A       ):







       """simple docstring"""







       if side_length < 0:
              raise ValueError('area_square() only accepts non-negative values'       )
       return side_length**2






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if base < 0 or height < 0:
              raise ValueError('area_triangle() only accepts non-negative values'       )
       return (base * height) / 2






def       lowercase					(_A ,    _A ,    _A       ):







       """simple docstring"""







       if sidea < 0 or sidea < 0 or sidea < 0:
              raise ValueError('area_triangle_three_sides() only accepts non-negative values'       )
       elif sidea + sidea < sidea or sidea + sidea < sidea or sidea + sidea < sidea:
              raise ValueError('Given three sides do not form a triangle'       )
       _lowerCAmelCase     :				Tuple       =							(sidea + sidea + sidea) / 2
       _lowerCAmelCase     :				Dict       =							sqrt(
           semi_perimeter
           * (semi_perimeter - sidea)
           * (semi_perimeter - sidea)
           * (semi_perimeter - sidea)       )
       return area






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if base < 0 or height < 0:
              raise ValueError('area_parallelogram() only accepts non-negative values'       )
       return base * height






def       lowercase					(_A ,    _A ,    _A       ):







       """simple docstring"""







       if basea < 0 or basea < 0 or height < 0:
              raise ValueError('area_trapezium() only accepts non-negative values'       )
       return 1 / 2 * (basea + basea) * height






def       lowercase					(_A       ):







       """simple docstring"""







       if radius < 0:
              raise ValueError('area_circle() only accepts non-negative values'       )
       return pi * radius**2






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if radius_x < 0 or radius_y < 0:
              raise ValueError('area_ellipse() only accepts non-negative values'       )
       return pi * radius_x * radius_y






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if diagonal_a < 0 or diagonal_a < 0:
              raise ValueError('area_rhombus() only accepts non-negative values'       )
       return 1 / 2 * diagonal_a * diagonal_a






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if not isinstance(_A ,    _A       ) or sides < 3:
              raise ValueError(
                  'area_reg_polygon() only accepts integers greater than or \
equal to three as number of sides'       )
       elif length < 0:
              raise ValueError(
                  'area_reg_polygon() only accepts non-negative values as \
length of a side'       )
       return (sides * length**2) / (4 * tan(pi / sides       ))
       return (sides * length**2) / (4 * tan(pi / sides       ))


if __name__ == "__main__":
       import doctest

       doctest.testmod(verbose=True)  # verbose so we can see methods missing tests

       print("""[DEMO] Areas of various geometric shapes: \n""")
       print(F'''Rectangle: {area_rectangle(10, 20) = }''')
       print(F'''Square: {area_square(10) = }''')
       print(F'''Triangle: {area_triangle(10, 10) = }''')
       print(F'''Triangle: {area_triangle_three_sides(5, 12, 13) = }''')
       print(F'''Parallelogram: {area_parallelogram(10, 20) = }''')
       print(F'''Rhombus: {area_rhombus(10, 20) = }''')
       print(F'''Trapezium: {area_trapezium(10, 20, 30) = }''')
       print(F'''Circle: {area_circle(20) = }''')
       print(F'''Ellipse: {area_ellipse(10, 20) = }''')
       print("""\nSurface Areas of various geometric shapes: \n""")
       print(F'''Cube: {surface_area_cube(20) = }''')
       print(F'''Cuboid: {surface_area_cuboid(10, 20, 30) = }''')
       print(F'''Sphere: {surface_area_sphere(20) = }''')
       print(F'''Hemisphere: {surface_area_hemisphere(20) = }''')
       print(F'''Cone: {surface_area_cone(10, 20) = }''')
       print(F'''Conical Frustum: {surface_area_conical_frustum(10, 20, 30) = }''')
       print(F'''Cylinder: {surface_area_cylinder(10, 20) = }''')
       print(F'''Torus: {surface_area_torus(20, 10) = }''')
       print(F'''Equilateral Triangle: {area_reg_polygon(3, 10) = }''')
       print(F'''Square: {area_reg_polygon(4, 10) = }''')
       print(F'''Reqular Pentagon: {area_reg_polygon(5, 10) = }''')

