






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


lowerCamelCase__							=     get_tests_dir("""fixtures/test_sentencepiece.model""")


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

lowerCamelCase__							=     5_0003
lowerCamelCase__							=     5_0002




@require_sentencepiece
@require_tokenizers
class 			snake_case__   (							lowercase_	,    unittest.TestCase):

       '''simple docstring'''
       lowerCamelCase							:				Optional[int] 				= PLBartTokenizer
       lowerCamelCase							:				Tuple 				= None
       lowerCamelCase							:				Dict 				= False



       def 					__lowercase						(							self    ) ->      Optional[int]:






            '''simple docstring'''





            super().setUp()

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



       def 					__lowercase						(							self    ) ->      Optional[Any]:






            '''simple docstring'''





            __snake_case			:List[str]          =						PLBartTokenizer(a__			,						language_codes="""base"""			,						keep_accents=a__    )

            __snake_case			:str          =						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 [2_85, 46, 10, 1_70, 3_82]]			,						)

            __snake_case			:Union[str, Any]          =						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""",
                    """.""",
                ]			,						)
            __snake_case			:Union[str, Any]          =						tokenizer.convert_tokens_to_ids(a__    )
            self.assertListEqual(
                a__			,						[
                    value + tokenizer.fairseq_offset
                    for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                ]			,						)

            __snake_case			: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>""",
                    """.""",
                ]			,						)

            __snake_case			:int          =						tokenizer.vocab_size
            __snake_case			:List[Any]          =						[tokenizer.convert_ids_to_tokens(a__    ) for x in range(end - 4			,						a__    )]

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

            __snake_case			:Optional[Any]          =						"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
            __snake_case			:Union[str, Any]          =						tokenizer(a__    ).input_ids
            self.assertEqual(
                tokenizer.decode(a__			,						skip_special_tokens=a__			,						clean_up_tokenization_spaces=a__    )			,						a__			,						)



       def 					__lowercase						(							self    ) ->      Union[str, Any]:






            '''simple docstring'''





            __snake_case			:Optional[Any]          =						PLBartTokenizer(a__			,						language_codes="""multi"""			,						keep_accents=a__    )

            __snake_case			:str          =						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 [2_85, 46, 10, 1_70, 3_82]]			,						)

            __snake_case			:Optional[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""",
                    """.""",
                ]			,						)
            __snake_case			:List[str]          =						tokenizer.convert_tokens_to_ids(a__    )
            self.assertListEqual(
                a__			,						[
                    value + tokenizer.fairseq_offset
                    for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                ]			,						)

            __snake_case			:str          =						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>""",
                    """.""",
                ]			,						)
            __snake_case			:int          =						tokenizer.vocab_size
            __snake_case			:str          =						[tokenizer.convert_ids_to_tokens(a__    ) for x in range(end - 7			,						a__    )]

            self.assertListEqual(
                a__			,						["""__java__""", """__python__""", """__en_XX__""", """__javascript__""", """__php__""", """__ruby__""", """__go__"""]    )
            __snake_case			:List[str]          =						"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
            __snake_case			: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 			snake_case__   (							unittest.TestCase):

       '''simple docstring'''
       lowerCamelCase							:				Optional[int] 				= "uclanlp/plbart-python-en_XX"
       lowerCamelCase							:				Tuple 				= [
           "def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])",
           "def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])",
       ]
       lowerCamelCase							:				Any 				= [
           "Returns the maximum value of a b c.",
           "Sums the values of a b c.",
       ]
       lowerCamelCase							:				Tuple 				= [
           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 					__lowercase						(							cls    ) ->      List[Any]:






            '''simple docstring'''





            __snake_case			:PLBartTokenizer          =						PLBartTokenizer.from_pretrained(
                cls.checkpoint_name			,						language_codes="""base"""			,						src_lang="""python"""			,						tgt_lang="""en_XX"""    )
            __snake_case			:Any          =						1
            return cls



       def 					__lowercase						(							self    ) ->      List[str]:






            '''simple docstring'''





            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__java__"""]			,						5_00_01    )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__python__"""]			,						5_00_02    )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__en_XX__"""]			,						5_00_03    )



       def 					__lowercase						(							self    ) ->      Tuple:






            '''simple docstring'''





            __snake_case			:Any          =						self.tokenizer.batch_encode_plus(self.src_text    ).input_ids[0]
            self.assertListEqual(self.expected_src_tokens			,						a__    )



       def 					__lowercase						(							self    ) ->      int:






            '''simple docstring'''





            self.assertIn(a__			,						self.tokenizer.all_special_ids    )
            __snake_case			:Dict          =						[EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
            __snake_case			:List[Any]          =						self.tokenizer.decode(a__			,						skip_special_tokens=a__    )
            __snake_case			:Union[str, Any]          =						self.tokenizer.decode(generated_ids[1:]			,						skip_special_tokens=a__    )
            self.assertEqual(a__			,						a__    )
            self.assertNotIn(self.tokenizer.eos_token			,						a__    )



       def 					__lowercase						(							self    ) ->      List[Any]:






            '''simple docstring'''





            __snake_case			:Optional[int]          =						["""def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""" * 20]
            self.assertIsInstance(src_text[0]			,						a__    )
            __snake_case			:Optional[Any]          =						10
            __snake_case			:Tuple          =						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 					__lowercase						(							self    ) ->      Tuple:






            '''simple docstring'''





            self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]    )			,						[5_00_04, 5_00_01]    )



       def 					__lowercase						(							self    ) ->      Any:






            '''simple docstring'''





            __snake_case			:Optional[int]          =						tempfile.mkdtemp()
            __snake_case			:List[str]          =						self.tokenizer.fairseq_tokens_to_ids
            self.tokenizer.save_pretrained(a__    )
            __snake_case			:List[str]          =						PLBartTokenizer.from_pretrained(a__    )
            self.assertDictEqual(new_tok.fairseq_tokens_to_ids			,						a__    )



       @require_torch
       def 					__lowercase						(							self    ) ->      Any:






            '''simple docstring'''





            __snake_case			:str          =						self.tokenizer(self.src_text			,						text_target=self.tgt_text			,						padding=a__			,						return_tensors="""pt"""    )
            __snake_case			:Any          =						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 					__lowercase						(							self    ) ->      Any:






            '''simple docstring'''





            __snake_case			:Optional[int]          =						self.tokenizer(
                self.src_text			,						text_target=self.tgt_text			,						padding=a__			,						truncation=a__			,						max_length=len(self.expected_src_tokens    )			,						return_tensors="""pt"""			,						)
            __snake_case			:List[Any]          =						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    )
            __snake_case			:str          =						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 					__lowercase						(							self    ) ->      List[str]:






            '''simple docstring'''





            __snake_case			:List[str]          =						self.tokenizer(self.src_text			,						padding=a__			,						truncation=a__			,						max_length=3			,						return_tensors="""pt"""    )
            __snake_case			:int          =						self.tokenizer(
                text_target=self.tgt_text			,						padding=a__			,						truncation=a__			,						max_length=10			,						return_tensors="""pt"""    )
            __snake_case			:Dict          =						targets["""input_ids"""]
            __snake_case			:Union[str, Any]          =						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 					__lowercase						(							self    ) ->      Optional[Any]:






            '''simple docstring'''





            __snake_case			: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""": [[1_50, 2_42, 2, 5_00_03]],
                    """attention_mask""": [[1, 1, 1, 1]],
                    # java
                    """forced_bos_token_id""": 5_00_01,
                }			,						)










from __future__ import annotations

import time

import numpy as np

lowerCamelCase__							=     [8, 5, 9, 7]
lowerCamelCase__							=     [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
lowerCamelCase__							=     [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]




class 			snake_case__   :

       '''simple docstring'''



       def __init__(							self			,						a__			,						a__			,						a__			,						) ->      None:






            '''simple docstring'''





            __snake_case			:Dict          =						claim_vector
            __snake_case			:Optional[int]          =						allocated_resources_table
            __snake_case			:Optional[int]          =						maximum_claim_table



       def 					__lowercase						(							self    ) ->      list[int]:






            '''simple docstring'''





            return [
                sum(p_item[i] for p_item in self.__allocated_resources_table    )
                for i in range(len(self.__allocated_resources_table[0]    )    )
            ]



       def 					__lowercase						(							self    ) ->      list[int]:






            '''simple docstring'''





            return np.array(self.__claim_vector    ) - np.array(
                self.__processes_resource_summation()    )



       def 					__lowercase						(							self    ) ->      list[list[int]]:






            '''simple docstring'''





            return [
                list(np.array(self.__maximum_claim_table[i]    ) - np.array(a__    )    )
                for i, allocated_resource in enumerate(self.__allocated_resources_table    )
            ]



       def 					__lowercase						(							self    ) ->      dict[int, list[int]]:






            '''simple docstring'''





            return {self.__need().index(a__    ): i for i in self.__need()}



       def 					__lowercase						(							self			,						**a__    ) ->      None:






            '''simple docstring'''





            __snake_case			:Optional[int]          =						self.__need()
            __snake_case			:List[Any]          =						self.__allocated_resources_table
            __snake_case			:str          =						self.__available_resources()
            __snake_case			:List[Any]          =						self.__need_index_manager()
            for kw, val in kwargs.items():
                 if kw and val is True:
                      self.__pretty_data()
            print("""_""" * 50 + """\n"""    )
            while need_list:
                 __snake_case			:Dict          =						False
                 for each_need in need_list:
                      __snake_case			:Dict          =						True
                      for index, need in enumerate(a__    ):
                           if need > available_resources[index]:
                                __snake_case			:Dict          =						False
                                break
                      if execution:
                           __snake_case			:Any          =						True
                           # get the original index of the process from ind_ctrl db
                           for original_need_index, need_clone in need_index_manager.items():
                                if each_need == need_clone:
                                     __snake_case			:List[str]          =						original_need_index
                           print(F'''Process {process_number + 1} is executing.'''    )
                           # remove the process run from stack
                           need_list.remove(a__    )
                           # update available/freed resources stack
                           __snake_case			:Tuple          =						np.array(a__    ) + np.array(
                               alloc_resources_table[process_number]    )
                           print(
                               """Updated available resource stack for processes: """
                               + """ """.join([str(a__    ) for x in available_resources]    )    )
                           break
                 if safe:
                      print("""The process is in a safe state.\n"""    )
                 else:
                      print("""System in unsafe state. Aborting...\n"""    )
                      break



       def 					__lowercase						(							self    ) ->      Dict:






            '''simple docstring'''





            print(""" """ * 9 + """Allocated Resource Table"""    )
            for item in self.__allocated_resources_table:
                 print(
                     F'''P{self.__allocated_resources_table.index(a__    ) + 1}'''
                     + """ """.join(F'''{it:>8}''' for it in item    )
                     + """\n"""    )
            print(""" """ * 9 + """System Resource Table"""    )
            for item in self.__maximum_claim_table:
                 print(
                     F'''P{self.__maximum_claim_table.index(a__    ) + 1}'''
                     + """ """.join(F'''{it:>8}''' for it in item    )
                     + """\n"""    )
            print(
                """Current Usage by Active Processes: """
                + """ """.join(str(a__    ) for x in self.__claim_vector    )    )
            print(
                """Initial Available Resources:       """
                + """ """.join(str(a__    ) for x in self.__available_resources()    )    )
            time.sleep(1    )


if __name__ == "__main__":
     import doctest

     doctest.testmod()


