import sys
from random import randint



class 			UpperCamelCase					:

     '''simple docstring'''

     def __init__(       self					,					A_					,					A_    )			->					List[str]:






           """simple docstring"""
           _lowerCamelCase           =					key
           _lowerCamelCase           =					freq





     def __str__(       self    )			->					Dict:






           """simple docstring"""
           return F'Node(key={self.key}, freq={self.freq})'





def    __magic_name__(	__UpperCAmelCase			,    __UpperCAmelCase			,    __UpperCAmelCase			,    __UpperCAmelCase			,    __UpperCAmelCase			,    __UpperCAmelCase		)    ->     Any:



      '''simple docstring'''

      if i > j or i < 0 or j > len(lowercase__		) - 1:
            return

      _lowerCamelCase           =					root[i][j]
      if parent == -1:  # root does not have a parent
            print(F'{key[node]} is the root of the binary search tree.'		)
      elif is_left:
            print(F'{key[node]} is the left child of key {parent}.'		)
      else:
            print(F'{key[node]} is the right child of key {parent}.'		)

      print_binary_search_tree(lowercase__			,    lowercase__			,    lowercase__			,    node - 1			,    key[node]			,    lowercase__		)
      print_binary_search_tree(lowercase__			,    lowercase__			,    node + 1			,    lowercase__			,    key[node]			,    lowercase__		)
def    __magic_name__(	__UpperCAmelCase		)    ->     str:



      '''simple docstring'''

      nodes.sort(key=lambda __UpperCAmelCase		: node.key		)

      _lowerCamelCase           =					len(lowercase__		)

      _lowerCamelCase           =					[nodes[i].key for i in range(lowercase__		)]
      _lowerCamelCase           =					[nodes[i].freq for i in range(lowercase__		)]

      # This 2D array stores the overall tree cost (which's as minimized as possible);
      # for a single key, cost is equal to frequency of the key.
      _lowerCamelCase           =					[[freqs[i] if i == j else 0 for j in range(lowercase__		)] for i in range(lowercase__		)]
      # sum[i][j] stores the sum of key frequencies between i and j inclusive in nodes
      # array
      _lowerCamelCase           =					[[freqs[i] if i == j else 0 for j in range(lowercase__		)] for i in range(lowercase__		)]
      # stores tree roots that will be used later for constructing binary search tree
      _lowerCamelCase           =					[[i if i == j else 0 for j in range(lowercase__		)] for i in range(lowercase__		)]

      for interval_length in range(2			,    n + 1		):
            for i in range(n - interval_length + 1		):
                  _lowerCamelCase           =					i + interval_length - 1

                  _lowerCamelCase           =					sys.maxsize  # set the value to "infinity"
                  _lowerCamelCase           =					total[i][j - 1] + freqs[j]

                  # Apply Knuth's optimization
                  # Loop without optimization: for r in range(i, j + 1):
                  for r in range(root[i][j - 1]			,    root[i + 1][j] + 1		):  # r is a temporal root
                        _lowerCamelCase           =					dp[i][r - 1] if r != i else 0  # optimal cost for left subtree
                        _lowerCamelCase           =					dp[r + 1][j] if r != j else 0  # optimal cost for right subtree
                        _lowerCamelCase           =					left + total[i][j] + right

                        if dp[i][j] > cost:
                              _lowerCamelCase           =					cost
                              _lowerCamelCase           =					r

      print('''Binary search tree nodes:'''		)
      for node in nodes:
            print(lowercase__		)

      print(F'\nThe cost of optimal BST for given tree nodes is {dp[0][n - 1]}.'		)
      print_binary_search_tree(lowercase__			,    lowercase__			,    0			,    n - 1			,    -1			,    lowercase__		)
def    __magic_name__(	)    ->     str:



      '''simple docstring'''

      _lowerCamelCase           =					[Node(lowercase__			,    randint(1			,    50		)		) for i in range(10			,    0			,    -1		)]
      find_optimal_binary_search_tree(lowercase__		)


if __name__ == "__main__":
     main()


"""simple docstring"""




import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin





class      __UpperCamelCase					(  _A	,						unittest.TestCase		):
		SCREAMING_SNAKE_CASE														=       SpeechaTextaTokenizer
		SCREAMING_SNAKE_CASE														=       False


		def    SCREAMING_SNAKE_CASE__  (self					:						Tuple):
							super().setUp()

							A     =   "<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" ")
							A     =   ["he re</w> 123", "here a 1456"]
							A     =   dict(zip(__SCREAMING_SNAKE_CASE	,	range(len(__SCREAMING_SNAKE_CASE))))

							A     =   {"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

							A     =   tempfile.mkdtemp()
							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(__SCREAMING_SNAKE_CASE) + "\n")

							with open(self.merges_file	,	"w") as fp:
												fp.write("\n".join(__SCREAMING_SNAKE_CASE))


		def    SCREAMING_SNAKE_CASE__  (self					:						Union[str, Any]):
							A     =   list(self.get_tokenizer().get_vocab().keys())

							self.assertEqual(vocab_keys[0]	,	"<s>")
							self.assertEqual(vocab_keys[1]	,	"<pad>")
							self.assertEqual(vocab_keys[-1]	,	"vocab")
							self.assertEqual(len(__SCREAMING_SNAKE_CASE)	,	1_4)


		def    SCREAMING_SNAKE_CASE__  (self					:						Any):
							self.assertEqual(self.get_tokenizer().vocab_size	,	1_4)


		def    SCREAMING_SNAKE_CASE__  (self					:						Union[str, Any]):
							A     =   SpeechaTextaTokenizer.from_pretrained(self.tmpdirname)

							# make sure @@ is correctly concatenated
							A     =   [4, 6, 8, 7, 1_0]  # ["here@@", "couple", "words", "of@@", "the"]
							A     =   tokenizer.decode(__SCREAMING_SNAKE_CASE)

							self.assertTrue(output_string == "herecouple words ofthe")


		def    SCREAMING_SNAKE_CASE__  (self					:						str):
							A     =   SpeechaTextaTokenizer.from_pretrained(self.tmpdirname)

							with tempfile.TemporaryDirectory() as tmp_dirname:
												tokenizer.save_pretrained(__SCREAMING_SNAKE_CASE)
												os.remove(os.path.join(__SCREAMING_SNAKE_CASE	,	"merges.txt"))

												# load tokenizer without merges file should not throw an error
												A     =   SpeechaTextaTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE)

							with tempfile.TemporaryDirectory() as tmp_dirname:
												# save tokenizer and load again
												tokenizer.save_pretrained(__SCREAMING_SNAKE_CASE)
												A     =   SpeechaTextaTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE)

							self.assertIsNotNone(__SCREAMING_SNAKE_CASE)


		def    SCREAMING_SNAKE_CASE__  (self					:						Tuple):
							if not self.test_slow_tokenizer:
												return

							A     =   inspect.signature(self.tokenizer_class.__init__)
							A     =   self.get_tokenizer()

							for parameter_name, parameter in signature.parameters.items():
												if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
																	self.assertIn(__SCREAMING_SNAKE_CASE	,	tokenizer.init_kwargs)





