



import tempfile
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin


_lowercase  				=    get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
				from transformers.models.plbart.modeling_plbart import shift_tokens_right

_lowercase  				=    5_00_03
_lowercase  				=    5_00_02
@require_sentencepiece
@require_tokenizers
class 					__A       (			__lowercase       ,			unittest.TestCase   ):
			UpperCamelCase       :Dict	 =      PLBartTokenizer
			UpperCamelCase       :str	 =      None
			UpperCamelCase       :Tuple	 =      False





			def 							_snake_case     (self					):
						super().setUp()

						# We have a SentencePiece fixture for testing
						lowerCamelCase__			:   int										=		PLBartTokenizer(_a				,     language_codes="""base"""				,     keep_accents=_a					)
						tokenizer.save_pretrained(self.tmpdirname					)





			def 							_snake_case     (self					):
						lowerCamelCase__			:   str										=		PLBartTokenizer(_a				,     language_codes="""base"""				,     keep_accents=_a					)

						lowerCamelCase__			:   Optional[Any]										=		tokenizer.tokenize("""This is a test"""					)
						self.assertListEqual(_a				,     ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]					)

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

						lowerCamelCase__			:   int										=		tokenizer.tokenize("""I was born in 92000, and this is falsé."""					)
						self.assertListEqual(
						    _a				,     [
						        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__			:   Optional[int]										=		tokenizer.convert_tokens_to_ids(_a					)
						self.assertListEqual(
						    _a				,     [
						        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__			:   int										=		tokenizer.convert_ids_to_tokens(_a					)
						self.assertListEqual(
						    _a				,     [
						        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>""",
						        """.""",
						    ]				,     )

						lowerCamelCase__			:   Any										=		tokenizer.vocab_size
						lowerCamelCase__			:   Any										=		[tokenizer.convert_ids_to_tokens(_a					) for x in range(end - 4				,     _a					)]

						self.assertListEqual(_a				,     ["""__java__""", """__python__""", """__en_XX__""", """<mask>"""]					)

						lowerCamelCase__			:   List[Any]										=		'''java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'''
						lowerCamelCase__			:   str										=		tokenizer(_a					).input_ids
						self.assertEqual(
						    tokenizer.decode(_a				,     skip_special_tokens=_a				,     clean_up_tokenization_spaces=_a					)				,     _a				,     )





			def 							_snake_case     (self					):
						lowerCamelCase__			:   int										=		PLBartTokenizer(_a				,     language_codes="""multi"""				,     keep_accents=_a					)

						lowerCamelCase__			:   Optional[int]										=		tokenizer.tokenize("""This is a test"""					)
						self.assertListEqual(_a				,     ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]					)

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

						lowerCamelCase__			:   Dict										=		tokenizer.tokenize("""I was born in 92000, and this is falsé."""					)
						self.assertListEqual(
						    _a				,     [
						        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__			:   Tuple										=		tokenizer.convert_tokens_to_ids(_a					)
						self.assertListEqual(
						    _a				,     [
						        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[Any]										=		tokenizer.convert_ids_to_tokens(_a					)
						self.assertListEqual(
						    _a				,     [
						        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>""",
						        """.""",
						    ]				,     )
						lowerCamelCase__			:   Optional[Any]										=		tokenizer.vocab_size
						lowerCamelCase__			:   Dict										=		[tokenizer.convert_ids_to_tokens(_a					) for x in range(end - 7				,     _a					)]

						self.assertListEqual(
						    _a				,     ["""__java__""", """__python__""", """__en_XX__""", """__javascript__""", """__php__""", """__ruby__""", """__go__"""]					)
						lowerCamelCase__			:   Optional[Any]										=		'''java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'''
						lowerCamelCase__			:   str										=		tokenizer(_a					).input_ids
						self.assertEqual(
						    tokenizer.decode(_a				,     skip_special_tokens=_a				,     clean_up_tokenization_spaces=_a					)				,     _a				,     )







@require_torch
@require_sentencepiece
@require_tokenizers
class 					__A       (			unittest.TestCase   ):
			UpperCamelCase       :List[Any]	 =      "uclanlp/plbart-python-en_XX"
			UpperCamelCase       :int	 =      [
			    "def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])",
			    "def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])",
			]
			UpperCamelCase       :Optional[int]	 =      [
			    "Returns the maximum value of a b c.",
			    "Sums the values of a b c.",
			]
			UpperCamelCase       :Optional[int]	 =      [
			    134,
			    5452,
			    3_3460,
			    3_3441,
			    3_3463,
			    3_3465,
			    3_3463,
			    3_3449,
			    988,
			    20,
			    3_3456,
			    19,
			    3_3456,
			    771,
			    39,
			    4258,
			    889,
			    3318,
			    3_3441,
			    3_3463,
			    3_3465,
			    3_3463,
			    3_3449,
			    2471,
			    2,
			    PYTHON_CODE,
			]





			@classmethod
			def 							_snake_case     (cls					):
						lowerCamelCase__			:   PLBartTokenizer										=		PLBartTokenizer.from_pretrained(
						    cls.checkpoint_name				,     language_codes="""base"""				,     src_lang="""python"""				,     tgt_lang="""en_XX"""					)
						lowerCamelCase__			:   Optional[int]										=		1
						return cls





			def 							_snake_case     (self					):
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__java__"""]				,     50001					)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__python__"""]				,     50002					)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__en_XX__"""]				,     50003					)





			def 							_snake_case     (self					):
						lowerCamelCase__			:   Tuple										=		self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
						self.assertListEqual(self.expected_src_tokens				,     _a					)





			def 							_snake_case     (self					):
						self.assertIn(_a				,     self.tokenizer.all_special_ids					)
						lowerCamelCase__			:   Union[str, Any]										=		[EN_CODE, 9037, 33442, 57, 752, 153, 14, 56, 18, 9, 2]
						lowerCamelCase__			:   Tuple										=		self.tokenizer.decode(_a				,     skip_special_tokens=_a					)
						lowerCamelCase__			:   List[Any]										=		self.tokenizer.decode(generated_ids[1:]				,     skip_special_tokens=_a					)
						self.assertEqual(_a				,     _a					)
						self.assertNotIn(self.tokenizer.eos_token				,     _a					)





			def 							_snake_case     (self					):
						lowerCamelCase__			:   Dict										=		['''def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])''' * 20]
						self.assertIsInstance(src_text[0]				,     _a					)
						lowerCamelCase__			:   Optional[Any]										=		10
						lowerCamelCase__			:   List[str]										=		self.tokenizer(_a				,     max_length=_a				,     truncation=_a					).input_ids[0]
						self.assertEqual(ids[-2]				,     2					)
						self.assertEqual(ids[-1]				,     _a					)
						self.assertEqual(len(_a					)				,     _a					)





			def 							_snake_case     (self					):
						self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]					)				,     [50004, 50001]					)





			def 							_snake_case     (self					):
						lowerCamelCase__			:   int										=		tempfile.mkdtemp()
						lowerCamelCase__			:   Dict										=		self.tokenizer.fairseq_tokens_to_ids
						self.tokenizer.save_pretrained(_a					)
						lowerCamelCase__			:   Tuple										=		PLBartTokenizer.from_pretrained(_a					)
						self.assertDictEqual(new_tok.fairseq_tokens_to_ids				,     _a					)





			@require_torch
			def 							_snake_case     (self					):
						lowerCamelCase__			:   Tuple										=		self.tokenizer(self.src_text				,     text_target=self.tgt_text				,     padding=_a				,     return_tensors="""pt"""					)
						lowerCamelCase__			:   Tuple										=		shift_tokens_right(batch["""labels"""]				,     self.tokenizer.pad_token_id					)

						# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
						self.assertEqual(batch.input_ids[1][-2:].tolist()				,     [2, PYTHON_CODE]					)
						self.assertEqual(batch.decoder_input_ids[1][0]				,     _a					)
						self.assertEqual(batch.decoder_input_ids[1][-1]				,     2					)
						self.assertEqual(batch.labels[1][-2:].tolist()				,     [2, EN_CODE]					)





			@require_torch
			def 							_snake_case     (self					):
						lowerCamelCase__			:   Tuple										=		self.tokenizer(
						    self.src_text				,     text_target=self.tgt_text				,     padding=_a				,     truncation=_a				,     max_length=len(self.expected_src_tokens					)				,     return_tensors="""pt"""				,     )
						lowerCamelCase__			:   str										=		shift_tokens_right(batch["""labels"""]				,     self.tokenizer.pad_token_id					)

						self.assertIsInstance(_a				,     _a					)

						self.assertEqual((2, 26)				,     batch.input_ids.shape					)
						self.assertEqual((2, 26)				,     batch.attention_mask.shape					)
						lowerCamelCase__			:   Optional[int]										=		batch.input_ids.tolist()[0]
						self.assertListEqual(self.expected_src_tokens				,     _a					)
						self.assertEqual(2				,     batch.decoder_input_ids[0, -1]					)  # EOS
						# Test that special tokens are reset
						self.assertEqual(self.tokenizer.prefix_tokens				,     []					)
						self.assertEqual(self.tokenizer.suffix_tokens				,     [self.tokenizer.eos_token_id, PYTHON_CODE]					)





			def 							_snake_case     (self					):
						lowerCamelCase__			:   List[str]										=		self.tokenizer(self.src_text				,     padding=_a				,     truncation=_a				,     max_length=3				,     return_tensors="""pt"""					)
						lowerCamelCase__			:   str										=		self.tokenizer(
						    text_target=self.tgt_text				,     padding=_a				,     truncation=_a				,     max_length=10				,     return_tensors="""pt"""					)
						lowerCamelCase__			:   Optional[Any]										=		targets['''input_ids''']
						lowerCamelCase__			:   str										=		shift_tokens_right(_a				,     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 							_snake_case     (self					):
						lowerCamelCase__			:   Optional[Any]										=		self.tokenizer._build_translation_inputs(
						    """A test"""				,     return_tensors="""pt"""				,     src_lang="""en_XX"""				,     tgt_lang="""java"""					)

						self.assertEqual(
						    nested_simplify(_a					)				,     {
						        # A, test, EOS, en_XX
						        """input_ids""": [[150, 242, 2, 50003]],
						        """attention_mask""": [[1, 1, 1, 1]],
						        # java
						        """forced_bos_token_id""": 50001,
						    }				,     )






from __future__ import annotations

import matplotlib.pyplot as plt  # type: ignore
import numpy

# initial triangle of Koch snowflake
a__												=						numpy.array([0, 0])
a__												=						numpy.array([0.5, 0.8660254])
a__												=						numpy.array([1, 0])
a__												=						[VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]



def   __UpperCAmelCase					(      __a :     list[numpy.ndarray]						,__a :     int      )     ->	list[numpy.ndarray]:

					"""simple docstring"""

					_a      :       Tuple   =						initial_vectors
					for _ in range(__a      ):
										_a      :       int   =						iteration_step(__a      )
					return vectors



def   __UpperCAmelCase					(      __a :     list[numpy.ndarray]      )     ->	list[numpy.ndarray]:

					"""simple docstring"""

					_a      :       Tuple   =						[]
					for i, start_vector in enumerate(vectors[:-1]      ):
										_a      :       str   =						vectors[i + 1]
										new_vectors.append(__a      )
										_a      :       Optional[int]   =						end_vector - start_vector
										new_vectors.append(start_vector + difference_vector / 3      )
										new_vectors.append(
										    start_vector + difference_vector / 3 + rotate(difference_vector / 3						,60      )      )
										new_vectors.append(start_vector + difference_vector * 2 / 3      )
					new_vectors.append(vectors[-1]      )
					return new_vectors



def   __UpperCAmelCase					(      __a :     numpy.ndarray						,__a :     float      )     ->	numpy.ndarray:

					"""simple docstring"""

					_a      :       Tuple   =						numpy.radians(__a      )
					_a ,   _a      :       List[Any]   =						numpy.cos(__a      ), numpy.sin(__a      )
					_a      :       Dict   =						numpy.array(((c, -s), (s, c))      )
					return numpy.dot(__a						,__a      )



def   __UpperCAmelCase					(      __a :     list[numpy.ndarray]      )     ->	None:

					"""simple docstring"""

					_a      :       str   =						plt.gca()
					axes.set_aspect('''equal'''      )

					# matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
					# y-coordinates as inputs, which are constructed from the vector-list using
					# zip()
					_a ,   _a      :       Optional[int]   =						zip(*__a      )
					plt.plot(__a						,__a      )
					plt.show()


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			a__												=						iterate(INITIAL_VECTORS, 5)
			plot(processed_vectors)



