






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 							SCREAMING_SNAKE_CASE__		(       unittest.TestCase		):





					"""simple docstring"""






					a_			=	ViTImageProcessor if is_vision_available() else None



					@property
					def  _lowercase  (      self  :						Optional[int] ):
						return self.image_processor_tester.prepare_image_processor_dict()



					def  _lowercase  (      self  :						List[str] ):
						snake_case__				:   Any     =						(3, 3_2, 1_2_8)
						snake_case__				:   str     =						tempfile.mkdtemp()

						# fmt: off
						snake_case__				:   Union[str, Any]     =						["[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     =						dict(zip(UpperCamelCase__							,	range(len(UpperCamelCase__ ) ) ) )

						snake_case__				:   Dict     =						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(UpperCamelCase__ ) + "\n" )

						snake_case__				:   str     =						{
						    "do_normalize": False,
						    "do_resize": True,
						    "image_processor_type": "ViTImageProcessor",
						    "resample": 3,
						    "size": {"height": 3_2, "width": 1_2_8},
						}
						snake_case__				:   Tuple     =						os.path.join(self.tmpdirname							,	UpperCamelCase__ )
						with open(self.image_processor_file							,	"w"							,	encoding="utf-8" ) as fp:
							json.dump(UpperCamelCase__							,	UpperCamelCase__ )



					def  _lowercase  (      self  :						Union[str, Any]							,	**__A  :						int ):
						return MgpstrTokenizer.from_pretrained(self.tmpdirname							,	**UpperCamelCase__ )



					def  _lowercase  (      self  :						int							,	**__A  :						Optional[int] ):
						return ViTImageProcessor.from_pretrained(self.tmpdirname							,	**UpperCamelCase__ )



					def  _lowercase  (      self  :						Tuple ):
						shutil.rmtree(self.tmpdirname )



					def  _lowercase  (      self  :						Union[str, Any] ):
						snake_case__				:   Any     =						np.random.randint(2_5_5							,	size=(3, 3_0, 4_0_0)							,	dtype=np.uinta )

						snake_case__				:   List[str]     =						Image.fromarray(np.moveaxis(UpperCamelCase__							,	0							,	-1 ) )

						return image_input



					def  _lowercase  (      self  :						Optional[int] ):
						snake_case__				:   int     =						self.get_tokenizer()
						snake_case__				:   Optional[int]     =						self.get_image_processor()

						snake_case__				:   str     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )
						processor.save_pretrained(self.tmpdirname )
						snake_case__				:   List[str]     =						MgpstrProcessor.from_pretrained(self.tmpdirname							,	use_fast=UpperCamelCase__ )

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

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



					def  _lowercase  (      self  :						int ):
						snake_case__				:   Optional[Any]     =						self.get_tokenizer()
						snake_case__				:   Tuple     =						self.get_image_processor()

						snake_case__				:   Union[str, Any]     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )
						processor.save_pretrained(self.tmpdirname )

						snake_case__				:   Optional[Any]     =						self.get_tokenizer(bos_token="(BOS)"							,	eos_token="(EOS)" )
						snake_case__				:   Union[str, Any]     =						self.get_image_processor(do_normalize=UpperCamelCase__							,	padding_value=1.0 )

						snake_case__				:   Any     =						MgpstrProcessor.from_pretrained(
						    self.tmpdirname							,	bos_token="(BOS)"							,	eos_token="(EOS)"							,	do_normalize=UpperCamelCase__							,	padding_value=1.0 )

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

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



					def  _lowercase  (      self  :						Union[str, Any] ):
						snake_case__				:   List[Any]     =						self.get_image_processor()
						snake_case__				:   Optional[int]     =						self.get_tokenizer()

						snake_case__				:   int     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )

						snake_case__				:   Tuple     =						self.prepare_image_inputs()

						snake_case__				:   Union[str, Any]     =						image_processor(UpperCamelCase__							,	return_tensors="np" )
						snake_case__				:   Union[str, Any]     =						processor(images=UpperCamelCase__							,	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  _lowercase  (      self  :						Tuple ):
						snake_case__				:   str     =						self.get_image_processor()
						snake_case__				:   Tuple     =						self.get_tokenizer()

						snake_case__				:   Optional[int]     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )

						snake_case__				:   int     =						"test"

						snake_case__				:   List[str]     =						processor(text=UpperCamelCase__ )

						snake_case__				:   int     =						tokenizer(UpperCamelCase__ )
						for key in encoded_tok.keys():
							self.assertListEqual(encoded_tok[key]							,	encoded_processor[key] )



					def  _lowercase  (      self  :						int ):
						snake_case__				:   str     =						self.get_image_processor()
						snake_case__				:   Dict     =						self.get_tokenizer()

						snake_case__				:   Any     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )

						snake_case__				:   List[Any]     =						"test"
						snake_case__				:   int     =						self.prepare_image_inputs()

						snake_case__				:   Optional[Any]     =						processor(text=UpperCamelCase__							,	images=UpperCamelCase__ )

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

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



					def  _lowercase  (      self  :						Any ):
						snake_case__				:   Optional[Any]     =						self.get_image_processor()
						snake_case__				:   Dict     =						self.get_tokenizer()

						snake_case__				:   str     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )

						snake_case__				:   str     =						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

						snake_case__				:   Optional[int]     =						processor.char_decode(UpperCamelCase__ )
						snake_case__				:   Dict     =						tokenizer.batch_decode(UpperCamelCase__ )
						snake_case__				:   Optional[int]     =						[seq.replace(" "							,	"" ) for seq in decoded_tok]

						self.assertListEqual(UpperCamelCase__							,	UpperCamelCase__ )



					def  _lowercase  (      self  :						int ):
						snake_case__				:   List[str]     =						self.get_image_processor()
						snake_case__				:   Optional[int]     =						self.get_tokenizer()

						snake_case__				:   Optional[Any]     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )

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

						snake_case__				:   int     =						processor(text=UpperCamelCase__							,	images=UpperCamelCase__ )

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






					def  _lowercase  (      self  :						Union[str, Any] ):
						snake_case__				:   Optional[int]     =						self.get_image_processor()
						snake_case__				:   Dict     =						self.get_tokenizer()

						snake_case__				:   Optional[int]     =						MgpstrProcessor(tokenizer=UpperCamelCase__							,	image_processor=UpperCamelCase__ )

						snake_case__				:   Optional[Any]     =						torch.randn(1							,	2_7							,	3_8 )
						snake_case__				:   Union[str, Any]     =						torch.randn(1							,	2_7							,	5_0_2_5_7 )
						snake_case__				:   Any     =						torch.randn(1							,	2_7							,	3_0_5_2_2 )

						snake_case__				:   List[str]     =						processor.batch_decode([char_input, bpe_input, wp_input] )

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











# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

__lowerCamelCase      :    Union[str, Any]   		=   """2.13.1"""

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("""3.7"""):
	raise ImportWarning(
	    """To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."""
	)

if version.parse(pyarrow.__version__).major < 8:
	raise ImportWarning(
	    """To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"""
	    """If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."""
	)

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

__lowerCamelCase      :    List[Any]   		=   concatenate_datasets
__lowerCamelCase      :    List[str]   		=   DownloadConfig
__lowerCamelCase      :    Union[str, Any]   		=   DownloadManager
__lowerCamelCase      :    str   		=   DownloadMode
__lowerCamelCase      :    Union[str, Any]   		=   DownloadConfig
__lowerCamelCase      :    List[str]   		=   DownloadMode
__lowerCamelCase      :    Dict   		=   DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager



