

import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
					from PIL import Image

					from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor







@require_vision
class 				lowercase       ( unittest.TestCase    ):




				def 					a							(      self ):
											snake_case_           =					tempfile.mkdtemp()

											snake_case_           =					[
											    '[UNK]',
											    '[CLS]',
											    '[SEP]',
											    '[PAD]',
											    '[MASK]',
											    '的',
											    '价',
											    '格',
											    '是',
											    '15',
											    '便',
											    'alex',
											    '##andra',
											    '，',
											    '。',
											    '-',
											    't',
											    'shirt',
											]
											snake_case_           =					os.path.join(self.tmpdirname   ,     VOCAB_FILES_NAMES['vocab_file'] )
											with open(self.vocab_file   ,     'w'   ,     encoding='utf-8' ) as vocab_writer:
																		vocab_writer.write(''.join([x + '\n' for x in vocab_tokens] ) )

											snake_case_           =					{
											    'do_resize': True,
											    'size': {'height': 224, 'width': 224},
											    'do_center_crop': True,
											    'crop_size': {'height': 18, 'width': 18},
											    'do_normalize': True,
											    'image_mean': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
											    'image_std': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
											    'do_convert_rgb': True,
											}
											snake_case_           =					os.path.join(self.tmpdirname   ,     snake_case )
											with open(self.image_processor_file   ,     'w'   ,     encoding='utf-8' ) as fp:
																		json.dump(snake_case   ,     snake_case )




				def 					a							(      self   ,     **snake_case ):
											return BertTokenizer.from_pretrained(self.tmpdirname   ,     **snake_case )




				def 					a							(      self   ,     **snake_case ):
											return BertTokenizerFast.from_pretrained(self.tmpdirname   ,     **snake_case )




				def 					a							(      self   ,     **snake_case ):
											return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname   ,     **snake_case )




				def 					a							(      self ):
											shutil.rmtree(self.tmpdirname )




				def 					a							(      self ):
											snake_case_           =					[np.random.randint(255   ,     size=(3, 30, 400)   ,     dtype=np.uinta )]

											snake_case_           =					[Image.fromarray(np.moveaxis(snake_case   ,     0   ,     -1 ) ) for x in image_inputs]

											return image_inputs




				def 					a							(      self ):
											snake_case_           =					self.get_tokenizer()
											snake_case_           =					self.get_rust_tokenizer()
											snake_case_           =					self.get_image_processor()

											snake_case_           =					ChineseCLIPProcessor(tokenizer=snake_case   ,     image_processor=snake_case )
											processor_slow.save_pretrained(self.tmpdirname )
											snake_case_           =					ChineseCLIPProcessor.from_pretrained(self.tmpdirname   ,     use_fast=snake_case )

											snake_case_           =					ChineseCLIPProcessor(tokenizer=snake_case   ,     image_processor=snake_case )
											processor_fast.save_pretrained(self.tmpdirname )
											snake_case_           =					ChineseCLIPProcessor.from_pretrained(self.tmpdirname )

											self.assertEqual(processor_slow.tokenizer.get_vocab()   ,     tokenizer_slow.get_vocab() )
											self.assertEqual(processor_fast.tokenizer.get_vocab()   ,     tokenizer_fast.get_vocab() )
											self.assertEqual(tokenizer_slow.get_vocab()   ,     tokenizer_fast.get_vocab() )
											self.assertIsInstance(processor_slow.tokenizer   ,     snake_case )
											self.assertIsInstance(processor_fast.tokenizer   ,     snake_case )

											self.assertEqual(processor_slow.image_processor.to_json_string()   ,     image_processor.to_json_string() )
											self.assertEqual(processor_fast.image_processor.to_json_string()   ,     image_processor.to_json_string() )
											self.assertIsInstance(processor_slow.image_processor   ,     snake_case )
											self.assertIsInstance(processor_fast.image_processor   ,     snake_case )




				def 					a							(      self ):
											snake_case_           =					ChineseCLIPProcessor(tokenizer=self.get_tokenizer()   ,     image_processor=self.get_image_processor() )
											processor.save_pretrained(self.tmpdirname )

											snake_case_           =					self.get_tokenizer(cls_token='(CLS)'   ,     sep_token='(SEP)' )
											snake_case_           =					self.get_image_processor(do_normalize=snake_case )

											snake_case_           =					ChineseCLIPProcessor.from_pretrained(
											    self.tmpdirname   ,     cls_token='(CLS)'   ,     sep_token='(SEP)'   ,     do_normalize=snake_case )

											self.assertEqual(processor.tokenizer.get_vocab()   ,     tokenizer_add_kwargs.get_vocab() )
											self.assertIsInstance(processor.tokenizer   ,     snake_case )

											self.assertEqual(processor.image_processor.to_json_string()   ,     image_processor_add_kwargs.to_json_string() )
											self.assertIsInstance(processor.image_processor   ,     snake_case )




				def 					a							(      self ):
											snake_case_           =					self.get_image_processor()
											snake_case_           =					self.get_tokenizer()

											snake_case_           =					ChineseCLIPProcessor(tokenizer=snake_case   ,     image_processor=snake_case )

											snake_case_           =					self.prepare_image_inputs()

											snake_case_           =					image_processor(snake_case   ,     return_tensors='np' )
											snake_case_           =					processor(images=snake_case   ,     return_tensors='np' )

											for key in input_feat_extract.keys():
																		self.assertAlmostEqual(input_feat_extract[key].sum()   ,     input_processor[key].sum()   ,     delta=1e-2 )




				def 					a							(      self ):
											snake_case_           =					self.get_image_processor()
											snake_case_           =					self.get_tokenizer()

											snake_case_           =					ChineseCLIPProcessor(tokenizer=snake_case   ,     image_processor=snake_case )

											snake_case_           =					'Alexandra，T-shirt的价格是15便士。'

											snake_case_           =					processor(text=snake_case )

											snake_case_           =					tokenizer(snake_case )

											for key in encoded_tok.keys():
																		self.assertListEqual(encoded_tok[key]   ,     encoded_processor[key] )




				def 					a							(      self ):
											snake_case_           =					self.get_image_processor()
											snake_case_           =					self.get_tokenizer()

											snake_case_           =					ChineseCLIPProcessor(tokenizer=snake_case   ,     image_processor=snake_case )

											snake_case_           =					'Alexandra，T-shirt的价格是15便士。'
											snake_case_           =					self.prepare_image_inputs()

											snake_case_           =					processor(text=snake_case   ,     images=snake_case )

											self.assertListEqual(list(inputs.keys() )   ,     ['input_ids', 'token_type_ids', 'attention_mask', 'pixel_values'] )

											# test if it raises when no input is passed
											with pytest.raises(snake_case ):
																		processor()




				def 					a							(      self ):
											snake_case_           =					self.get_image_processor()
											snake_case_           =					self.get_tokenizer()

											snake_case_           =					ChineseCLIPProcessor(tokenizer=snake_case   ,     image_processor=snake_case )

											snake_case_           =					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

											snake_case_           =					processor.batch_decode(snake_case )
											snake_case_           =					tokenizer.batch_decode(snake_case )

											self.assertListEqual(snake_case   ,     snake_case )




				def 					a							(      self ):
											snake_case_           =					self.get_image_processor()
											snake_case_           =					self.get_tokenizer()

											snake_case_           =					ChineseCLIPProcessor(tokenizer=snake_case   ,     image_processor=snake_case )

											snake_case_           =					'Alexandra，T-shirt的价格是15便士。'
											snake_case_           =					self.prepare_image_inputs()

											snake_case_           =					processor(text=snake_case   ,     images=snake_case )

											self.assertListEqual(list(inputs.keys() )   ,     processor.model_input_names )







from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any







@dataclass
class 				lowercase       :
				__SCREAMING_SNAKE_CASE      :				int
				__SCREAMING_SNAKE_CASE      :				Node | None     =    None
				__SCREAMING_SNAKE_CASE      :				Node | None     =    None





def       __lowerCamelCase			(				):







							'''simple docstring'''






							snake_case_           =					Node(1   )
							snake_case_           =					Node(2   )
							snake_case_           =					Node(3   )
							snake_case_           =					Node(4   )
							snake_case_           =					Node(5   )
							return tree





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							return [root.data, *preorder(root.left   ), *preorder(root.right   )] if root else []





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							return postorder(root.left   ) + postorder(root.right   ) + [root.data] if root else []





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							return [*inorder(root.left   ), root.data, *inorder(root.right   )] if root else []





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							return (max(height(root.left   )     ,							height(root.right   )   ) + 1) if root else 0





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					[]

							if root is None:
														return output

							snake_case_           =					deque([root]   )

							while process_queue:
														snake_case_           =					process_queue.popleft()
														output.append(node.data   )

														if node.left:
																					process_queue.append(node.left   )
														if node.right:
																					process_queue.append(node.right   )
							return output





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					[]

							def populate_output(UpperCamelCase__     ,							UpperCamelCase__   ) -> None:
														if not root:
																					return
														if level == 1:
																					output.append(root.data   )
														elif level > 1:
																					populate_output(root.left     ,							level - 1   )
																					populate_output(root.right     ,							level - 1   )

							populate_output(UpperCamelCase__     ,							UpperCamelCase__   )
							return output





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					[]

							def populate_output(UpperCamelCase__     ,							UpperCamelCase__   ) -> None:
														if root is None:
																					return
														if level == 1:
																					output.append(root.data   )
														elif level > 1:
																					populate_output(root.right     ,							level - 1   )
																					populate_output(root.left     ,							level - 1   )

							populate_output(UpperCamelCase__     ,							UpperCamelCase__   )
							return output





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							if root is None:
														return []

							snake_case_           =					[]

							snake_case_           =					0
							snake_case_           =					height(UpperCamelCase__   )

							for h in range(1     ,							height_tree + 1   ):
														if not flag:
																					output.append(get_nodes_from_left_to_right(UpperCamelCase__     ,							UpperCamelCase__   )   )
																					snake_case_           =					1
														else:
																					output.append(get_nodes_from_right_to_left(UpperCamelCase__     ,							UpperCamelCase__   )   )
																					snake_case_           =					0

							return output





def       __lowerCamelCase			(				):  # Main function for testing.







							'''simple docstring'''






							snake_case_           =					make_tree()
							print(F'''In-order Traversal: {inorder(UpperCamelCase__   )}'''   )
							print(F'''Pre-order Traversal: {preorder(UpperCamelCase__   )}'''   )
							print(F'''Post-order Traversal: {postorder(UpperCamelCase__   )}'''     ,							'\n'   )

							print(F'''Height of Tree: {height(UpperCamelCase__   )}'''     ,							'\n'   )

							print('Complete Level Order Traversal: '   )
							print(level_order(UpperCamelCase__   )     ,							'\n'   )

							print('Level-wise order Traversal: '   )

							for level in range(1     ,							height(UpperCamelCase__   ) + 1   ):
														print(F'''Level {level}:'''     ,							get_nodes_from_left_to_right(UpperCamelCase__     ,							level=UpperCamelCase__   )   )

							print('\nZigZag order Traversal: '   )
							print(zigzag(UpperCamelCase__   )   )


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()




