





class SCREAMING_SNAKE_CASE_			:





					"""simple docstring"""


					def __init__(			self						,	_lowerCAmelCase						):
										lowerCamelCase__      =							data
										lowerCamelCase__      =							None
										lowerCamelCase__      =							None





def  __UpperCamelCase   (     a,  a)			->BinaryTreeNode | None:
					if node is None:
										lowerCamelCase__      =							BinaryTreeNode(a)
										return node

					# binary search tree is not empty,
					# so we will insert it into the tree
					# if new_value is less than value of data in node,
					#  add it to left subtree and proceed recursively
					if new_value < node.data:
										lowerCamelCase__      =							insert(node.left_child,  a)
					else:
										# if new_value is greater than value of data in node,
										#  add it to right subtree and proceed recursively
										lowerCamelCase__      =							insert(node.right_child,  a)
					return node





def  __UpperCamelCase   (     a)			->list[int]:  # if node is None,return
					if node:
										lowerCamelCase__      =							inorder(node.left_child)
										lowerCamelCase__      =							[*inorder_array, node.data]
										lowerCamelCase__      =							inorder_array + inorder(node.right_child)
					else:
										lowerCamelCase__      =							[]
					return inorder_array





def  __UpperCamelCase   (     )			->BinaryTreeNode | None:
					lowerCamelCase__      =							insert(a,  15)
					insert(a,  10)
					insert(a,  25)
					insert(a,  6)
					insert(a,  14)
					insert(a,  20)
					insert(a,  60)
					return root





def  __UpperCamelCase   (     )			->None:
					# main function
					lowerCamelCase__      =							make_tree()
					print("Printing values of binary search tree in Inorder Traversal.")
					inorder(a)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()








# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    "--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000"
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/

