"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
					import torch


if is_vision_available():
					from PIL import Image

					from transformers import MgpstrProcessor, ViTImageProcessor



@require_torch
@require_vision
class 					lowerCAmelCase_      (     unittest.TestCase   ):



				"""simple docstring"""
				_lowerCAmelCase       :      Union[str, Any]     					=  ViTImageProcessor if is_vision_available() else None

				@property
				def 						snake_case	(			self      ):






										"""simple docstring"""

										return self.image_processor_tester.prepare_image_processor_dict()

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     (3, 32, 1_28)
										snake_case        =     tempfile.mkdtemp()

										# fmt: off
										snake_case        =     ['[GO]', '[s]', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
										# fmt: on
										snake_case        =     dict(zip(lowerCAmelCase						,      range(len(lowerCAmelCase      )      )      )      )

										snake_case        =     os.path.join(self.tmpdirname						,      VOCAB_FILES_NAMES['vocab_file']      )
										with open(self.vocab_file						,      'w'						,      encoding='utf-8'      ) as fp:
																fp.write(json.dumps(lowerCAmelCase      ) + '\n'      )

										snake_case        =     {
										    'do_normalize': False,
										    'do_resize': True,
										    'image_processor_type': 'ViTImageProcessor',
										    'resample': 3,
										    'size': {'height': 32, 'width': 1_28},
										}
										snake_case        =     os.path.join(self.tmpdirname						,      lowerCAmelCase      )
										with open(self.image_processor_file						,      'w'						,      encoding='utf-8'      ) as fp:
																json.dump(lowerCAmelCase						,      lowerCAmelCase      )

				def 						snake_case	(			self						,      **lowerCAmelCase      ):






										"""simple docstring"""

										return MgpstrTokenizer.from_pretrained(self.tmpdirname						,      **lowerCAmelCase      )

				def 						snake_case	(			self						,      **lowerCAmelCase      ):






										"""simple docstring"""

										return ViTImageProcessor.from_pretrained(self.tmpdirname						,      **lowerCAmelCase      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										shutil.rmtree(self.tmpdirname      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     np.random.randint(2_55						,      size=(3, 30, 4_00)						,      dtype=np.uinta      )

										snake_case        =     Image.fromarray(np.moveaxis(lowerCAmelCase						,      0						,      -1      )      )

										return image_input

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_tokenizer()
										snake_case        =     self.get_image_processor()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )
										processor.save_pretrained(self.tmpdirname      )
										snake_case        =     MgpstrProcessor.from_pretrained(self.tmpdirname						,      use_fast=lowerCAmelCase      )

										self.assertEqual(processor.char_tokenizer.get_vocab()						,      tokenizer.get_vocab()      )
										self.assertIsInstance(processor.char_tokenizer						,      lowerCAmelCase      )

										self.assertEqual(processor.image_processor.to_json_string()						,      image_processor.to_json_string()      )
										self.assertIsInstance(processor.image_processor						,      lowerCAmelCase      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_tokenizer()
										snake_case        =     self.get_image_processor()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )
										processor.save_pretrained(self.tmpdirname      )

										snake_case        =     self.get_tokenizer(bos_token='(BOS)'						,      eos_token='(EOS)'      )
										snake_case        =     self.get_image_processor(do_normalize=lowerCAmelCase						,      padding_value=1.0      )

										snake_case        =     MgpstrProcessor.from_pretrained(
										    self.tmpdirname						,      bos_token='(BOS)'						,      eos_token='(EOS)'						,      do_normalize=lowerCAmelCase						,      padding_value=1.0      )

										self.assertEqual(processor.char_tokenizer.get_vocab()						,      tokenizer_add_kwargs.get_vocab()      )
										self.assertIsInstance(processor.char_tokenizer						,      lowerCAmelCase      )

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

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_image_processor()
										snake_case        =     self.get_tokenizer()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

										snake_case        =     self.prepare_image_inputs()

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

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

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_image_processor()
										snake_case        =     self.get_tokenizer()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

										snake_case        =     'test'

										snake_case        =     processor(text=lowerCAmelCase      )

										snake_case        =     tokenizer(lowerCAmelCase      )
										for key in encoded_tok.keys():
																self.assertListEqual(encoded_tok[key]						,      encoded_processor[key]      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_image_processor()
										snake_case        =     self.get_tokenizer()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

										snake_case        =     'test'
										snake_case        =     self.prepare_image_inputs()

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

										self.assertListEqual(list(inputs.keys()      )						,      ['pixel_values', 'labels']      )

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

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_image_processor()
										snake_case        =     self.get_tokenizer()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

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

										snake_case        =     processor.char_decode(lowerCAmelCase      )
										snake_case        =     tokenizer.batch_decode(lowerCAmelCase      )
										snake_case        =     [seq.replace(' '						,      ''      ) for seq in decoded_tok]

										self.assertListEqual(lowerCAmelCase						,      lowerCAmelCase      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_image_processor()
										snake_case        =     self.get_tokenizer()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

										snake_case        =     None
										snake_case        =     self.prepare_image_inputs()

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

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

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_image_processor()
										snake_case        =     self.get_tokenizer()

										snake_case        =     MgpstrProcessor(tokenizer=lowerCAmelCase						,      image_processor=lowerCAmelCase      )

										snake_case        =     torch.randn(1						,      27						,      38      )
										snake_case        =     torch.randn(1						,      27						,      5_02_57      )
										snake_case        =     torch.randn(1						,      27						,      3_05_22      )

										snake_case        =     processor.batch_decode([char_input, bpe_input, wp_input]      )

										self.assertListEqual(list(results.keys()      )						,      ['generated_text', 'scores', 'char_preds', 'bpe_preds', 'wp_preds']      )



"""simple docstring"""
from __future__ import annotations

from typing import Any



class 					lowerCAmelCase_      (     lowerCAmelCase   ):



				"""simple docstring"""
				pass





class 					lowerCAmelCase_      :



				"""simple docstring"""

				def __init__(			self						,      lowerCAmelCase      ):






										"""simple docstring"""

										snake_case        =     data
										snake_case        =     None

				def __iter__(			self      ):






										"""simple docstring"""

										snake_case        =     self
										snake_case        =     []
										while node:
																if node in visited:
																						raise ContainsLoopError
																visited.append(lowerCAmelCase      )
																yield node.data
																snake_case        =     node.next_node

				@property
				def 						snake_case	(			self      ):






										"""simple docstring"""

										try:
																list(self      )
																return False
										except ContainsLoopError:
																return True


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__   =					Node(1)
					SCREAMING_SNAKE_CASE__   =					Node(2)
					SCREAMING_SNAKE_CASE__   =					Node(3)
					SCREAMING_SNAKE_CASE__   =					Node(4)
					print(root_node.has_loop)  # False
					SCREAMING_SNAKE_CASE__   =					root_node.next_node
					print(root_node.has_loop)  # True

					SCREAMING_SNAKE_CASE__   =					Node(5)
					SCREAMING_SNAKE_CASE__   =					Node(6)
					SCREAMING_SNAKE_CASE__   =					Node(5)
					SCREAMING_SNAKE_CASE__   =					Node(6)
					print(root_node.has_loop)  # False

					SCREAMING_SNAKE_CASE__   =					Node(1)
					print(root_node.has_loop)  # False


