



'''simple docstring'''


import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







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


 '''simple docstring'''




 __magic_name__					: int  =      CodeGenTokenizer
 __magic_name__					: Any  =      CodeGenTokenizerFast
 __magic_name__					: Union[str, Any]  =      True
 __magic_name__					: List[str]  =      {"add_prefix_space": True}
 __magic_name__					: Dict  =      False




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



      """simple docstring"""







      super().setUp()

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

      a_       		=os.path.join(self.tmpdirname							,  VOCAB_FILES_NAMES["vocab_file"])
      a_       		=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(lowerCAmelCase_) + "\n")
      with open(self.merges_file							,  "w"							,  encoding="utf-8") as fp:
           fp.write("\n".join(lowerCAmelCase_))




 def       lowercase_  (   self							,  **lowerCAmelCase_) ->      List[Any]:



      """simple docstring"""







      kwargs.update(self.special_tokens_map)
      return CodeGenTokenizer.from_pretrained(self.tmpdirname							,  **lowerCAmelCase_)




 def       lowercase_  (   self							,  **lowerCAmelCase_) ->      List[str]:



      """simple docstring"""







      kwargs.update(self.special_tokens_map)
      return CodeGenTokenizerFast.from_pretrained(self.tmpdirname							,  **lowerCAmelCase_)




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      Optional[Any]:



      """simple docstring"""







      a_       		="lower newer"
      a_       		="lower newer"
      return input_text, output_text




 def       lowercase_  (   self) ->      Any:



      """simple docstring"""







      a_       		=CodeGenTokenizer(self.vocab_file							,  self.merges_file							,  **self.special_tokens_map)
      a_       		="lower newer"
      a_       		=["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
      a_       		=tokenizer.tokenize(lowerCAmelCase_							,  add_prefix_space=lowerCAmelCase_)
      self.assertListEqual(lowerCAmelCase_							,  lowerCAmelCase_)

      a_       		=tokens + [tokenizer.unk_token]
      a_       		=[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_)							,  lowerCAmelCase_)




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



      """simple docstring"""







      if not self.test_rust_tokenizer:
           return

      a_       		=self.get_tokenizer()
      a_       		=self.get_rust_tokenizer(add_prefix_space=lowerCAmelCase_)

      a_       		="lower newer"

      # Testing tokenization
      a_       		=tokenizer.tokenize(lowerCAmelCase_							,  add_prefix_space=lowerCAmelCase_)
      a_       		=rust_tokenizer.tokenize(lowerCAmelCase_)
      self.assertListEqual(lowerCAmelCase_							,  lowerCAmelCase_)

      # Testing conversion to ids without special tokens
      a_       		=tokenizer.encode(lowerCAmelCase_							,  add_special_tokens=lowerCAmelCase_							,  add_prefix_space=lowerCAmelCase_)
      a_       		=rust_tokenizer.encode(lowerCAmelCase_							,  add_special_tokens=lowerCAmelCase_)
      self.assertListEqual(lowerCAmelCase_							,  lowerCAmelCase_)

      # Testing conversion to ids with special tokens
      a_       		=self.get_rust_tokenizer(add_prefix_space=lowerCAmelCase_)
      a_       		=tokenizer.encode(lowerCAmelCase_							,  add_prefix_space=lowerCAmelCase_)
      a_       		=rust_tokenizer.encode(lowerCAmelCase_)
      self.assertListEqual(lowerCAmelCase_							,  lowerCAmelCase_)

      # Testing the unknown token
      a_       		=tokens + [rust_tokenizer.unk_token]
      a_       		=[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
      self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowerCAmelCase_)							,  lowerCAmelCase_)




 def       lowercase_  (   self							,  *lowerCAmelCase_							,  **lowerCAmelCase_) ->      List[Any]:



      """simple docstring"""







      pass




 def       lowercase_  (   self							,  lowerCAmelCase_=1_5) ->      Union[str, Any]:



      """simple docstring"""







      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                a_       		=self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_							,  **lowerCAmelCase_)

                # Simple input
                a_       		="This is a simple input"
                a_       		=["This is a simple input 1", "This is a simple input 2"]
                a_       		=("This is a simple input", "This is a pair")
                a_       		=[
                    ("This is a simple input 1", "This is a simple input 2"),
                    ("This is a simple pair 1", "This is a simple pair 2"),
                ]

                # Simple input tests
                self.assertRaises(lowerCAmelCase_							,  tokenizer_r.encode							,  lowerCAmelCase_							,  max_length=lowerCAmelCase_							,  padding="max_length")

                # Simple input
                self.assertRaises(lowerCAmelCase_							,  tokenizer_r.encode_plus							,  lowerCAmelCase_							,  max_length=lowerCAmelCase_							,  padding="max_length")

                # Simple input
                self.assertRaises(
                    lowerCAmelCase_							,  tokenizer_r.batch_encode_plus							,  lowerCAmelCase_							,  max_length=lowerCAmelCase_							,  padding="max_length"							,  )

                # Pair input
                self.assertRaises(lowerCAmelCase_							,  tokenizer_r.encode							,  lowerCAmelCase_							,  max_length=lowerCAmelCase_							,  padding="max_length")

                # Pair input
                self.assertRaises(lowerCAmelCase_							,  tokenizer_r.encode_plus							,  lowerCAmelCase_							,  max_length=lowerCAmelCase_							,  padding="max_length")

                # Pair input
                self.assertRaises(
                    lowerCAmelCase_							,  tokenizer_r.batch_encode_plus							,  lowerCAmelCase_							,  max_length=lowerCAmelCase_							,  padding="max_length"							,  )




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



      """simple docstring"""







      a_       		=CodeGenTokenizer.from_pretrained(self.tmpdirname							,  pad_token="<pad>")

      # Simple input
      a_       		="This is a simple input"
      a_       		=["This is a simple input looooooooong", "This is a simple input"]
      a_       		=("This is a simple input", "This is a pair")
      a_       		=[
          ("This is a simple input loooooong", "This is a simple input"),
          ("This is a simple pair loooooong", "This is a simple pair"),
      ]

      a_       		=tokenizer.pad_token_id

      a_       		=tokenizer(lowerCAmelCase_							,  padding="max_length"							,  max_length=3_0							,  return_tensors="np")
      a_       		=tokenizer(lowerCAmelCase_							,  padding=lowerCAmelCase_							,  truncate=lowerCAmelCase_							,  return_tensors="np")
      a_       		=tokenizer(*lowerCAmelCase_							,  padding="max_length"							,  max_length=6_0							,  return_tensors="np")
      a_       		=tokenizer(lowerCAmelCase_							,  padding=lowerCAmelCase_							,  truncate=lowerCAmelCase_							,  return_tensors="np")

      # s
      # test single string max_length padding
      self.assertEqual(out_s["input_ids"].shape[-1]							,  3_0)
      self.assertTrue(pad_token_id in out_s["input_ids"])
      self.assertTrue(0 in out_s["attention_mask"])

      # s2
      # test automatic padding
      self.assertEqual(out_sa["input_ids"].shape[-1]							,  3_3)
      # long slice doesn't have padding
      self.assertFalse(pad_token_id in out_sa["input_ids"][0])
      self.assertFalse(0 in out_sa["attention_mask"][0])
      # short slice does have padding
      self.assertTrue(pad_token_id in out_sa["input_ids"][1])
      self.assertTrue(0 in out_sa["attention_mask"][1])

      # p
      # test single pair max_length padding
      self.assertEqual(out_p["input_ids"].shape[-1]							,  6_0)
      self.assertTrue(pad_token_id in out_p["input_ids"])
      self.assertTrue(0 in out_p["attention_mask"])

      # p2
      # test automatic padding pair
      self.assertEqual(out_pa["input_ids"].shape[-1]							,  5_2)
      # long slice pair doesn't have padding
      self.assertFalse(pad_token_id in out_pa["input_ids"][0])
      self.assertFalse(0 in out_pa["attention_mask"][0])
      # short slice pair does have padding
      self.assertTrue(pad_token_id in out_pa["input_ids"][1])
      self.assertTrue(0 in out_pa["attention_mask"][1])




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



      """simple docstring"""







      a_       		="$$$"
      a_       		=CodeGenTokenizer.from_pretrained(self.tmpdirname							,  bos_token=lowerCAmelCase_							,  add_bos_token=lowerCAmelCase_)

      a_       		="This is a simple input"
      a_       		=["This is a simple input 1", "This is a simple input 2"]

      a_       		=tokenizer.bos_token_id

      a_       		=tokenizer(lowerCAmelCase_)
      a_       		=tokenizer(lowerCAmelCase_)

      self.assertEqual(out_s.input_ids[0]							,  lowerCAmelCase_)
      self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids))

      a_       		=tokenizer.decode(out_s.input_ids)
      a_       		=tokenizer.batch_decode(out_sa.input_ids)

      self.assertEqual(decode_s.split()[0]							,  lowerCAmelCase_)
      self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa))




 @slow
 def       lowercase_  (   self) ->      int:



      """simple docstring"""







      a_       		=CodeGenTokenizer.from_pretrained("Salesforce/codegen-350M-mono")

      a_       		="\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#"
      a_       		="\nif len_a > len_b:      result = a\nelse:      result = b"

      a_       		=tokenizer.encode(lowerCAmelCase_)
      a_       		=["^#", re.escape("<|endoftext|>"), "^'''", "^\"\"\"", "\n\n\n"]
      a_       		=tokenizer.decode(lowerCAmelCase_							,  truncate_before_pattern=lowerCAmelCase_)
      self.assertEqual(lowerCAmelCase_							,  lowerCAmelCase_)




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



      """simple docstring"""







      pass







'''simple docstring'''


from __future__ import annotations






def  UpperCAmelCase_       (		lowercase__       ,	lowercase__       ):


     '''simple docstring'''







     print(F"""Vertex\tShortest Distance from vertex {src}"""       )
     for i, d in enumerate(lowercase__       ):
          print(F"""{i}\t\t{d}"""       )






def  UpperCAmelCase_       (		lowercase__       ,	lowercase__       ,	lowercase__       ):


     '''simple docstring'''







     for j in range(lowercase__       ):
          a_		,						a_		,						a_       		=(graph[j][k] for k in ["src", "dst", "weight"])
          if distance[u] != float("inf"       ) and distance[u] + w < distance[v]:
               return True
     return False






def  UpperCAmelCase_       (		lowercase__       ,	lowercase__       ,	lowercase__       ,	lowercase__       ):


     '''simple docstring'''







     a_       		=[float("inf"       )] * vertex_count
     a_       		=0.0

     for _ in range(vertex_count - 1       ):
          for j in range(lowercase__       ):
               a_		,						a_		,						a_       		=(graph[j][k] for k in ["src", "dst", "weight"])

               if distance[u] != float("inf"       ) and distance[u] + w < distance[v]:
                    a_       		=distance[u] + w

     a_       		=check_negative_cycle(lowercase__       ,	lowercase__       ,	lowercase__       )
     if negative_cycle_exists:
          raise Exception("Negative cycle found"       )

     return distance


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  lowercase							       =			int(input('''Enter number of vertices: ''').strip())
  lowercase							       =			int(input('''Enter number of edges: ''').strip())

  lowercase							       =			[{} for _ in range(E)]

  for i in range(E):
    print('''Edge ''', i + 1)
    lowercase       ,      lowercase       ,      lowercase							       =			(
        int(x)
        for x in input('''Enter source, destination, weight: ''').strip().split(''' ''')
    )
    lowercase							       =			{'''src''': src, '''dst''': dest, '''weight''': weight}

  lowercase							       =			int(input('''\nEnter shortest path source:''').strip())
  lowercase							       =			bellman_ford(graph, V, E, source)
  print_distance(shortest_distance, 0)


