






from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
lowerCamelCase : str						   =       1.054571817E-34  # unit of ℏ : J * s

lowerCamelCase : Union[str, Any]						   =       3E8  # unit of c : m * s^-1
def       snake_case_		(     lowerCAmelCase_       :						float       ,       lowerCAmelCase_       :						float       ,       lowerCAmelCase_       :						float      ):

							if (force, area, distance).count(0      ) != 1:
														raise ValueError("""One and only one argument must be 0"""      )
							if force < 0:
														raise ValueError("""Magnitude of force can not be negative"""      )
							if distance < 0:
														raise ValueError("""Distance can not be negative"""      )
							if area < 0:
														raise ValueError("""Area can not be negative"""      )
							if force == 0:
														__lowercase      :							List[Any]				=     (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
														    240 * (distance) ** 4
														)
														return {"force": force}
							elif area == 0:
														__lowercase      :							Optional[Any]				=     (240 * force * (distance) ** 4) / (
														    REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
														)
														return {"area": area}
							elif distance == 0:
														__lowercase      :							Any				=     (
														    (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (240 * force)
														) ** (1 / 4)
														return {"distance": distance}
							raise ValueError("""One and only one argument must be 0"""      )


# Run doctest
if __name__ == "__main__":
	import doctest

	doctest.testmod()







import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 		lowerCAmelCase     ( __a      ,       unittest.TestCase			):

					'''simple docstring'''

					_A						:			str									=      LongformerTokenizer
					_A						:			int									=      True
					_A						:			Optional[int]									=      LongformerTokenizerFast
					_A						:			int									=      True



					def       lowerCAmelCase				(  self				:	Any							)			->  List[str]:


												"""simple docstring"""

												super().setUp()

												# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
												__lowercase      :							Union[str, Any]				=     [
												    """l""",
												    """o""",
												    """w""",
												    """e""",
												    """r""",
												    """s""",
												    """t""",
												    """i""",
												    """d""",
												    """n""",
												    """\u0120""",
												    """\u0120l""",
												    """\u0120n""",
												    """\u0120lo""",
												    """\u0120low""",
												    """er""",
												    """\u0120lowest""",
												    """\u0120newer""",
												    """\u0120wider""",
												    """<unk>""",
												]
												__lowercase      :							Union[str, Any]				=     dict(zip(__a		,     range(len(__a							)							)							)							)
												__lowercase      :							Any				=     ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
												__lowercase      :							Optional[int]				=     {"""unk_token""": """<unk>"""}

												__lowercase      :							Dict				=     os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES["""vocab_file"""]							)
												__lowercase      :							str				=     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				:	Optional[Any]							)			->  str:


												"""simple docstring"""

												kwargs.update(self.special_tokens_map							)
												return self.tokenizer_class.from_pretrained(self.tmpdirname		,     **__a							)



					def       lowerCAmelCase				(  self				:	Tuple		,     **__a				:	Tuple							)			->  str:


												"""simple docstring"""

												kwargs.update(self.special_tokens_map							)
												return self.rust_tokenizer_class.from_pretrained(self.tmpdirname		,     **__a							)



					def       lowerCAmelCase				(  self				:	str		,     __a				:	Optional[int]							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     """lower newer"""
												__lowercase      :							int				=     """lower newer"""
												return input_text, output_text



					def       lowerCAmelCase				(  self				:	List[Any]							)			->  Optional[int]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     self.tokenizer_class(self.vocab_file		,     self.merges_file		,     **self.special_tokens_map							)
												__lowercase      :							Dict				=     """lower newer"""
												__lowercase      :							Optional[Any]				=     ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
												__lowercase      :							str				=     tokenizer.tokenize(__a							)  # , add_prefix_space=True)
												self.assertListEqual(__a		,     __a							)

												__lowercase      :							int				=     tokens + [tokenizer.unk_token]
												__lowercase      :							str				=     [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(__a							)		,     __a							)



					def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  List[Any]:


												"""simple docstring"""

												__lowercase      :							Optional[Any]				=     self.get_tokenizer()

												self.assertListEqual(tokenizer.encode("""Hello world!"""		,     add_special_tokens=__a							)		,     [0, 31414, 232, 328, 2]							)
												self.assertListEqual(
												    tokenizer.encode("""Hello world! cécé herlolip 418"""		,     add_special_tokens=__a							)		,     [0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]		,     )



					@slow
					def       lowerCAmelCase				(  self				:	Tuple							)			->  str:


												"""simple docstring"""

												__lowercase      :							Any				=     self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""							)

												__lowercase      :							Optional[Any]				=     tokenizer.encode("""sequence builders"""		,     add_special_tokens=__a							)
												__lowercase      :							List[str]				=     tokenizer.encode("""multi-sequence build"""		,     add_special_tokens=__a							)

												__lowercase      :							Optional[Any]				=     tokenizer.encode(
												    """sequence builders"""		,     add_special_tokens=__a		,     add_prefix_space=__a							)
												__lowercase      :							Union[str, Any]				=     tokenizer.encode(
												    """sequence builders"""		,     """multi-sequence build"""		,     add_special_tokens=__a		,     add_prefix_space=__a							)

												__lowercase      :							List[Any]				=     tokenizer.build_inputs_with_special_tokens(__a							)
												__lowercase      :							Any				=     tokenizer.build_inputs_with_special_tokens(__a		,     __a							)

												assert encoded_sentence == encoded_text_from_decode
												assert encoded_pair == encoded_pair_from_decode



					def       lowerCAmelCase				(  self				:	Dict							)			->  Tuple:


												"""simple docstring"""

												__lowercase      :							Optional[Any]				=     self.get_tokenizer()

												__lowercase      :							Tuple				=     """Encode this sequence."""
												__lowercase      :							Optional[Any]				=     tokenizer.byte_encoder[""" """.encode("""utf-8"""							)[0]]

												# Testing encoder arguments
												__lowercase      :							Dict				=     tokenizer.encode(__a		,     add_special_tokens=__a		,     add_prefix_space=__a							)
												__lowercase      :							Tuple				=     tokenizer.convert_ids_to_tokens(encoded[0]							)[0]
												self.assertNotEqual(__a		,     __a							)

												__lowercase      :							List[str]				=     tokenizer.encode(__a		,     add_special_tokens=__a		,     add_prefix_space=__a							)
												__lowercase      :							Any				=     tokenizer.convert_ids_to_tokens(encoded[0]							)[0]
												self.assertEqual(__a		,     __a							)

												tokenizer.add_special_tokens({"""bos_token""": """<s>"""}							)
												__lowercase      :							str				=     tokenizer.encode(__a		,     add_special_tokens=__a							)
												__lowercase      :							Dict				=     tokenizer.convert_ids_to_tokens(encoded[1]							)[0]
												self.assertNotEqual(__a		,     __a							)

												# Testing spaces after special tokens
												__lowercase      :							List[Any]				=     """<mask>"""
												tokenizer.add_special_tokens(
												    {"""mask_token""": AddedToken(__a		,     lstrip=__a		,     rstrip=__a							)}							)  # mask token has a left space
												__lowercase      :							Dict				=     tokenizer.convert_tokens_to_ids(__a							)

												__lowercase      :							List[str]				=     """Encode <mask> sequence"""
												__lowercase      :							List[str]				=     """Encode <mask>sequence"""

												__lowercase      :							Union[str, Any]				=     tokenizer.encode(__a							)
												__lowercase      :							Dict				=     encoded.index(__a							)
												__lowercase      :							List[Any]				=     tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]							)[0]
												self.assertEqual(__a		,     __a							)

												__lowercase      :							int				=     tokenizer.encode(__a							)
												__lowercase      :							Union[str, Any]				=     encoded.index(__a							)
												__lowercase      :							List[Any]				=     tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]							)[0]
												self.assertNotEqual(__a		,     __a							)



					def       lowerCAmelCase				(  self				:	int							)			->  str:


												"""simple docstring"""

												pass



					def       lowerCAmelCase				(  self				:	int							)			->  Dict:


												"""simple docstring"""

												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																			with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"							):
																										__lowercase      :							List[str]				=     self.rust_tokenizer_class.from_pretrained(__a		,     **__a							)
																										__lowercase      :							List[Any]				=     self.tokenizer_class.from_pretrained(__a		,     **__a							)
																										__lowercase      :							Optional[Any]				=     """A, <mask> AllenNLP sentence."""
																										__lowercase      :							Union[str, Any]				=     tokenizer_r.encode_plus(__a		,     add_special_tokens=__a		,     return_token_type_ids=__a							)
																										__lowercase      :							Optional[Any]				=     tokenizer_p.encode_plus(__a		,     add_special_tokens=__a		,     return_token_type_ids=__a							)

																										# token_type_ids should put 0 everywhere
																										self.assertEqual(sum(tokens_r["""token_type_ids"""]							)		,     sum(tokens_p["""token_type_ids"""]							)							)

																										# attention_mask should put 1 everywhere, so sum over length should be 1
																										self.assertEqual(
																										    sum(tokens_r["""attention_mask"""]							) / len(tokens_r["""attention_mask"""]							)		,     sum(tokens_p["""attention_mask"""]							) / len(tokens_p["""attention_mask"""]							)		,     )

																										__lowercase      :							Dict				=     tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]							)
																										__lowercase      :							str				=     tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]							)

																										# Rust correctly handles the space before the mask while python doesnt
																										self.assertSequenceEqual(tokens_p["""input_ids"""]		,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)
																										self.assertSequenceEqual(tokens_r["""input_ids"""]		,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)

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



					def       lowerCAmelCase				(  self				:	List[Any]							)			->  Dict:


												"""simple docstring"""

												for trim_offsets, add_prefix_space in itertools.product([True, False]		,     repeat=2							):
																			__lowercase      :							Dict				=     self.rust_tokenizer_class.from_pretrained(
																			    self.tmpdirname		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)

																			__lowercase      :							Optional[int]				=     json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()							)
																			__lowercase      :							Any				=     json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()							)

																			self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]		,     __a							)

																			self.assertEqual(post_processor_state["""add_prefix_space"""]		,     __a							)
																			self.assertEqual(post_processor_state["""trim_offsets"""]		,     __a							)



					def       lowerCAmelCase				(  self				:	int							)			->  Tuple:


												"""simple docstring"""

												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																			with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"							):
																										__lowercase      :							List[str]				=     """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
																										__lowercase      :							int				=     F"{text_of_1_token} {text_of_1_token}"

																										__lowercase      :							List[str]				=     self.rust_tokenizer_class.from_pretrained(
																										    __a		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)
																										__lowercase      :							Any				=     tokenizer_r(__a		,     return_offsets_mapping=__a		,     add_special_tokens=__a							)
																										self.assertEqual(encoding.offset_mapping[0]		,     (0, len(__a							))							)
																										self.assertEqual(
																										    encoding.offset_mapping[1]		,     (len(__a							) + 1, len(__a							) + 1 + len(__a							))		,     )

																										__lowercase      :							str				=     self.rust_tokenizer_class.from_pretrained(
																										    __a		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)
																										__lowercase      :							Tuple				=     tokenizer_r(__a		,     return_offsets_mapping=__a		,     add_special_tokens=__a							)
																										self.assertEqual(encoding.offset_mapping[0]		,     (0, len(__a							))							)
																										self.assertEqual(
																										    encoding.offset_mapping[1]		,     (len(__a							) + 1, len(__a							) + 1 + len(__a							))		,     )

																										__lowercase      :							Optional[int]				=     self.rust_tokenizer_class.from_pretrained(
																										    __a		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)
																										__lowercase      :							str				=     tokenizer_r(__a		,     return_offsets_mapping=__a		,     add_special_tokens=__a							)
																										self.assertEqual(encoding.offset_mapping[0]		,     (0, len(__a							))							)
																										self.assertEqual(
																										    encoding.offset_mapping[1]		,     (len(__a							), len(__a							) + 1 + len(__a							))		,     )

																										__lowercase      :							str				=     self.rust_tokenizer_class.from_pretrained(
																										    __a		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)
																										__lowercase      :							int				=     tokenizer_r(__a		,     return_offsets_mapping=__a		,     add_special_tokens=__a							)
																										self.assertEqual(encoding.offset_mapping[0]		,     (0, len(__a							))							)
																										self.assertEqual(
																										    encoding.offset_mapping[1]		,     (len(__a							), len(__a							) + 1 + len(__a							))		,     )

																										__lowercase      :							Any				=     F" {text}"

																										# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																										#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																										# )
																										# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																										# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																										# self.assertEqual(
																										#     encoding.offset_mapping[1],
																										#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																										# )

																										__lowercase      :							Optional[Any]				=     self.rust_tokenizer_class.from_pretrained(
																										    __a		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)
																										__lowercase      :							str				=     tokenizer_r(__a		,     return_offsets_mapping=__a		,     add_special_tokens=__a							)
																										self.assertEqual(encoding.offset_mapping[0]		,     (1, 1 + len(__a							))							)
																										self.assertEqual(
																										    encoding.offset_mapping[1]		,     (1 + len(__a							) + 1, 1 + len(__a							) + 1 + len(__a							))		,     )

																										__lowercase      :							int				=     self.rust_tokenizer_class.from_pretrained(
																										    __a		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)
																										__lowercase      :							Dict				=     tokenizer_r(__a		,     return_offsets_mapping=__a		,     add_special_tokens=__a							)
																										self.assertEqual(encoding.offset_mapping[0]		,     (0, 1 + len(__a							))							)
																										self.assertEqual(
																										    encoding.offset_mapping[1]		,     (1 + len(__a							), 1 + len(__a							) + 1 + len(__a							))		,     )

																										__lowercase      :							int				=     self.rust_tokenizer_class.from_pretrained(
																										    __a		,     use_fast=__a		,     add_prefix_space=__a		,     trim_offsets=__a							)
																										__lowercase      :							Tuple				=     tokenizer_r(__a		,     return_offsets_mapping=__a		,     add_special_tokens=__a							)
																										self.assertEqual(encoding.offset_mapping[0]		,     (0, 1 + len(__a							))							)
																										self.assertEqual(
																										    encoding.offset_mapping[1]		,     (1 + len(__a							), 1 + len(__a							) + 1 + len(__a							))		,     )