
'''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     __snake_case		(   unittest.TestCase):
					_lowerCAmelCase			     =	ViTImageProcessor if is_vision_available() else None
					@property
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.image_processor_tester.prepare_image_processor_dict()
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			List[Any]									= (3, 32, 128)
									lowerCamelCase					:			List[str]									= tempfile.mkdtemp()

									# fmt: off
									lowerCamelCase					:			str									= ['[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
									lowerCamelCase					:			str									= dict(zip(A,    range(len(A      )      )      )      )

									lowerCamelCase					:			Tuple									= 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(A      ) + '\n'      )

									lowerCamelCase					:			int									= {
									    'do_normalize': False,
									    'do_resize': True,
									    'image_processor_type': 'ViTImageProcessor',
									    'resample': 3,
									    'size': {'height': 32, 'width': 128},
									}
									lowerCamelCase					:			Optional[Any]									= os.path.join(self.tmpdirname,    A      )
									with open(self.image_processor_file,    'w',    encoding='utf-8'      ) as fp:
													json.dump(A,    A      )
					def     UpperCAmelCase_							(     self,    **A      ):

									"""simple docstring"""


									return MgpstrTokenizer.from_pretrained(self.tmpdirname,    **A      )
					def     UpperCAmelCase_							(     self,    **A      ):

									"""simple docstring"""


									return ViTImageProcessor.from_pretrained(self.tmpdirname,    **A      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


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

									"""simple docstring"""


									lowerCamelCase					:			List[Any]									= np.random.randint(255,    size=(3, 30, 400),    dtype=np.uinta      )

									lowerCamelCase					:			int									= Image.fromarray(np.moveaxis(A,    0,    -1      )      )

									return image_input
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			List[Any]									= self.get_tokenizer()
									lowerCamelCase					:			Union[str, Any]									= self.get_image_processor()

									lowerCamelCase					:			List[Any]									= MgpstrProcessor(tokenizer=A,    image_processor=A      )
									processor.save_pretrained(self.tmpdirname      )
									lowerCamelCase					:			Optional[Any]									= MgpstrProcessor.from_pretrained(self.tmpdirname,    use_fast=A      )

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

									self.assertEqual(processor.image_processor.to_json_string(),    image_processor.to_json_string()      )
									self.assertIsInstance(processor.image_processor,    A      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			List[Any]									= self.get_tokenizer()
									lowerCamelCase					:			int									= self.get_image_processor()

									lowerCamelCase					:			List[str]									= MgpstrProcessor(tokenizer=A,    image_processor=A      )
									processor.save_pretrained(self.tmpdirname      )

									lowerCamelCase					:			Optional[int]									= self.get_tokenizer(bos_token='(BOS)',    eos_token='(EOS)'      )
									lowerCamelCase					:			Dict									= self.get_image_processor(do_normalize=A,    padding_value=1.0      )

									lowerCamelCase					:			Union[str, Any]									= MgpstrProcessor.from_pretrained(
									    self.tmpdirname,    bos_token='(BOS)',    eos_token='(EOS)',    do_normalize=A,    padding_value=1.0      )

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

									self.assertEqual(processor.image_processor.to_json_string(),    image_processor_add_kwargs.to_json_string()      )
									self.assertIsInstance(processor.image_processor,    A      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Optional[int]									= self.get_image_processor()
									lowerCamelCase					:			int									= self.get_tokenizer()

									lowerCamelCase					:			List[Any]									= MgpstrProcessor(tokenizer=A,    image_processor=A      )

									lowerCamelCase					:			Optional[int]									= self.prepare_image_inputs()

									lowerCamelCase					:			Tuple									= image_processor(A,    return_tensors='np'      )
									lowerCamelCase					:			Union[str, Any]									= processor(images=A,    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     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			List[str]									= self.get_image_processor()
									lowerCamelCase					:			Dict									= self.get_tokenizer()

									lowerCamelCase					:			Any									= MgpstrProcessor(tokenizer=A,    image_processor=A      )

									lowerCamelCase					:			Tuple									= 'test'

									lowerCamelCase					:			Optional[int]									= processor(text=A      )

									lowerCamelCase					:			Optional[Any]									= tokenizer(A      )
									for key in encoded_tok.keys():
													self.assertListEqual(encoded_tok[key],    encoded_processor[key]      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Optional[Any]									= self.get_image_processor()
									lowerCamelCase					:			int									= self.get_tokenizer()

									lowerCamelCase					:			List[str]									= MgpstrProcessor(tokenizer=A,    image_processor=A      )

									lowerCamelCase					:			str									= 'test'
									lowerCamelCase					:			Dict									= self.prepare_image_inputs()

									lowerCamelCase					:			Dict									= processor(text=A,    images=A      )

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

									# test if it raises when no input is passed
									with pytest.raises(A      ):
													processor()
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Union[str, Any]									= self.get_image_processor()
									lowerCamelCase					:			List[Any]									= self.get_tokenizer()

									lowerCamelCase					:			int									= MgpstrProcessor(tokenizer=A,    image_processor=A      )

									lowerCamelCase					:			Optional[Any]									= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

									lowerCamelCase					:			Tuple									= processor.char_decode(A      )
									lowerCamelCase					:			Tuple									= tokenizer.batch_decode(A      )
									lowerCamelCase					:			Optional[int]									= [seq.replace(' ',    ''      ) for seq in decoded_tok]

									self.assertListEqual(A,    A      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			int									= self.get_image_processor()
									lowerCamelCase					:			Optional[int]									= self.get_tokenizer()

									lowerCamelCase					:			Union[str, Any]									= MgpstrProcessor(tokenizer=A,    image_processor=A      )

									lowerCamelCase					:			Any									= None
									lowerCamelCase					:			str									= self.prepare_image_inputs()

									lowerCamelCase					:			int									= processor(text=A,    images=A      )

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




					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			int									= self.get_image_processor()
									lowerCamelCase					:			Any									= self.get_tokenizer()

									lowerCamelCase					:			Union[str, Any]									= MgpstrProcessor(tokenizer=A,    image_processor=A      )

									lowerCamelCase					:			List[Any]									= torch.randn(1,    27,    38      )
									lowerCamelCase					:			Optional[int]									= torch.randn(1,    27,    5_0257      )
									lowerCamelCase					:			List[Any]									= torch.randn(1,    27,    3_0522      )

									lowerCamelCase					:			List[Any]									= 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'''






import importlib.metadata
import operator
import re
import sys
from typing import Optional

from packaging import version


A			      =      {
    '<': operator.lt,
    '<=': operator.le,
    '==': operator.eq,
    '!=': operator.ne,
    '>=': operator.ge,
    '>': operator.gt,
}





def    UpperCAmelCase							(  UpperCAmelCase__							:							Optional[Any]       ,							UpperCAmelCase__							:							Optional[Any]       ,							UpperCAmelCase__							:							Union[str, Any]       ,							UpperCAmelCase__							:							List[Any]       ,							UpperCAmelCase__							:							Dict       ,							UpperCAmelCase__							:							Optional[int]):
				if got_ver is None or want_ver is None:
								raise ValueError(
								    F'''Unable to compare versions for {requirement}: need={want_ver} found={got_ver}. This is unusual. Consider'''
								    F''' reinstalling {pkg}.''')
				if not ops[op](version.parse(UpperCAmelCase__)       ,							version.parse(UpperCAmelCase__)):
								raise ImportError(
								    F'''{requirement} is required for a normal functioning of this module, but found {pkg}=={got_ver}.{hint}''')





def    UpperCAmelCase							(  UpperCAmelCase__							:							str       ,							UpperCAmelCase__							:							Optional[str] = None):
				lowerCamelCase					:			List[Any]									= F'''\n{hint}''' if hint is not None else ''

				# non-versioned check
				if re.match(R'^[\w_\-\d]+$'       ,							UpperCAmelCase__):
								lowerCamelCase			, lowerCamelCase			, lowerCamelCase					:			Optional[Any]									= requirement, None, None
				else:
								lowerCamelCase					:			Optional[Any]									= re.findall(R'^([^!=<>\s]+)([\s!=<>]{1,2}.+)'       ,							UpperCAmelCase__)
								if not match:
												raise ValueError(
												    'requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23, but'
												    F''' got {requirement}''')
								lowerCamelCase			, lowerCamelCase					:			Dict									= match[0]
								lowerCamelCase					:			Dict									= want_full.split(',')  # there could be multiple requirements
								lowerCamelCase					:			Union[str, Any]									= {}
								for w in want_range:
												lowerCamelCase					:			int									= re.findall(R'^([\s!=<>]{1,2})(.+)'       ,							UpperCAmelCase__)
												if not match:
																raise ValueError(
																    'requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23,'
																    F''' but got {requirement}''')
												lowerCamelCase			, lowerCamelCase					:			List[Any]									= match[0]
												lowerCamelCase					:			Optional[int]									= want_ver
												if op not in ops:
																raise ValueError(F'''{requirement}: need one of {list(ops.keys())}, but got {op}''')

    # special case
				if pkg == "python":
								lowerCamelCase					:			Optional[int]									= '.'.join([str(UpperCAmelCase__) for x in sys.version_info[:3]])
								for op, want_ver in wanted.items():
												_compare_versions(UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__)
								return

				# check if any version is installed
				try:
								lowerCamelCase					:			Any									= importlib.metadata.version(UpperCAmelCase__)
				except importlib.metadata.PackageNotFoundError:
								raise importlib.metadata.PackageNotFoundError(
								    F'''The \'{requirement}\' distribution was not found and is required by this application. {hint}''')

				# check that the right version is installed if version number or a range was provided
				if want_ver is not None:
								for op, want_ver in wanted.items():
												_compare_versions(UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__)





def    UpperCAmelCase							(  UpperCAmelCase__							:							str):
				lowerCamelCase					:			List[str]									= 'Try: pip install transformers -U or pip install -e \'.[dev]\' if you\'re working with git main'
				return require_version(UpperCAmelCase__       ,							UpperCAmelCase__)
