"""simple docstring"""


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available


if is_torch_available():
 from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_11
else:
 lowerCAmelCase_:       Dict			     =       False

if is_vision_available():
 from PIL import Image

 from transformers import (
     AutoProcessor,
     PixaStructImageProcessor,
     PixaStructProcessor,
     PreTrainedTokenizerFast,
     TaTokenizer,
 )






@unittest.skipIf(
    not is_torch_greater_or_equal_than_1_11       ,       reason="`Pix2StructImageProcessor` requires `torch>=1.11.0`."       ,       )
@require_vision
@require_torch
class  a__     ( unittest.TestCase						):


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				tempfile.mkdtemp()

        lowercase__								=				PixaStructImageProcessor()
        lowercase__								=				TaTokenizer.from_pretrained("t5-small"	)

        lowercase__								=				PixaStructProcessor(_UpperCAmelCase,					_UpperCAmelCase	)

        processor.save_pretrained(self.tmpdirname	)


   def 						snake_case__						(  self,					**_UpperCAmelCase	):
        '''simple docstring'''



        return AutoProcessor.from_pretrained(self.tmpdirname,					**_UpperCAmelCase	).tokenizer


   def 						snake_case__						(  self,					**_UpperCAmelCase	):
        '''simple docstring'''



        return AutoProcessor.from_pretrained(self.tmpdirname,					**_UpperCAmelCase	).image_processor


   def 						snake_case__						(  self	):
        '''simple docstring'''



        shutil.rmtree(self.tmpdirname	)


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				[np.random.randint(255,					size=(3, 30, 400),					dtype=np.uinta	)]

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

        return image_inputs


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				PixaStructProcessor(tokenizer=self.get_tokenizer(),					image_processor=self.get_image_processor()	)
        processor.save_pretrained(self.tmpdirname	)

        lowercase__								=				self.get_tokenizer(bos_token="(BOS)",					eos_token="(EOS)"	)
        lowercase__								=				self.get_image_processor(do_normalize=_UpperCAmelCase,					padding_value=1.0	)

        lowercase__								=				PixaStructProcessor.from_pretrained(
            self.tmpdirname,					bos_token="(BOS)",					eos_token="(EOS)",					do_normalize=_UpperCAmelCase,					padding_value=1.0	)

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

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


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				self.get_image_processor()
        lowercase__								=				self.get_tokenizer()

        lowercase__								=				PixaStructProcessor(tokenizer=_UpperCAmelCase,					image_processor=_UpperCAmelCase	)

        lowercase__								=				self.prepare_image_inputs()

        lowercase__								=				image_processor(_UpperCAmelCase,					return_tensors="np"	)
        lowercase__								=				processor(images=_UpperCAmelCase,					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 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				self.get_image_processor()
        lowercase__								=				self.get_tokenizer()

        lowercase__								=				PixaStructProcessor(tokenizer=_UpperCAmelCase,					image_processor=_UpperCAmelCase	)

        lowercase__								=				"lower newer"

        lowercase__								=				processor(text=_UpperCAmelCase	)

        lowercase__								=				tokenizer(_UpperCAmelCase,					return_token_type_ids=_UpperCAmelCase,					add_special_tokens=_UpperCAmelCase	)

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


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				self.get_image_processor()
        lowercase__								=				self.get_tokenizer()

        lowercase__								=				PixaStructProcessor(tokenizer=_UpperCAmelCase,					image_processor=_UpperCAmelCase	)

        lowercase__								=				"lower newer"
        lowercase__								=				self.prepare_image_inputs()

        lowercase__								=				processor(text=_UpperCAmelCase,					images=_UpperCAmelCase	)

        self.assertListEqual(
            list(inputs.keys()	),					["flattened_patches", "attention_mask", "decoder_attention_mask", "decoder_input_ids"]	)

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


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				self.get_image_processor()
        lowercase__								=				self.get_tokenizer()

        lowercase__								=				PixaStructProcessor(tokenizer=_UpperCAmelCase,					image_processor=_UpperCAmelCase	)

        lowercase__								=				"lower newer"
        lowercase__								=				self.prepare_image_inputs()

        lowercase__								=				processor(text=_UpperCAmelCase,					images=_UpperCAmelCase	)

        lowercase__								=				[512, 1024, 2048, 4096]
        lowercase__								=				[770, 770, 770, 770]
        # with text
        for i, max_patch in enumerate(_UpperCAmelCase	):
             lowercase__								=				processor(text=_UpperCAmelCase,					images=_UpperCAmelCase,					max_patches=_UpperCAmelCase	)
             self.assertEqual(inputs["flattened_patches"][0].shape[0],					_UpperCAmelCase	)
             self.assertEqual(inputs["flattened_patches"][0].shape[1],					expected_hidden_size[i]	)

        # without text input
        for i, max_patch in enumerate(_UpperCAmelCase	):
             lowercase__								=				processor(images=_UpperCAmelCase,					max_patches=_UpperCAmelCase	)
             self.assertEqual(inputs["flattened_patches"][0].shape[0],					_UpperCAmelCase	)
             self.assertEqual(inputs["flattened_patches"][0].shape[1],					expected_hidden_size[i]	)


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				self.get_image_processor()
        lowercase__								=				self.get_tokenizer()

        lowercase__								=				PixaStructProcessor(tokenizer=_UpperCAmelCase,					image_processor=_UpperCAmelCase	)

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

        lowercase__								=				processor.batch_decode(_UpperCAmelCase	)
        lowercase__								=				tokenizer.batch_decode(_UpperCAmelCase	)

        self.assertListEqual(_UpperCAmelCase,					_UpperCAmelCase	)


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				self.get_image_processor()
        lowercase__								=				self.get_tokenizer()

        lowercase__								=				PixaStructProcessor(tokenizer=_UpperCAmelCase,					image_processor=_UpperCAmelCase	)

        lowercase__								=				"lower newer"
        lowercase__								=				self.prepare_image_inputs()

        lowercase__								=				processor(text=_UpperCAmelCase,					images=_UpperCAmelCase	)

        # For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
        self.assertListEqual(
            list(inputs.keys()	),					["flattened_patches", "attention_mask", "decoder_attention_mask", "decoder_input_ids"]	)

        lowercase__								=				processor(text=_UpperCAmelCase	)

        # For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
        self.assertListEqual(list(inputs.keys()	),					["input_ids", "attention_mask"]	)





"""simple docstring"""


import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand







def        __a (		A   ):






     '''simple docstring'''



     return EnvironmentCommand()






class  a__     ( _a						):


   @staticmethod
   def 						snake_case__						(  _UpperCAmelCase	):
        '''simple docstring'''



        lowercase__								=				parser.add_parser("env",					help="Print relevant system environment info."	)
        download_parser.set_defaults(func=_UpperCAmelCase	)


   def 						snake_case__						(  self	):
        '''simple docstring'''



        lowercase__								=				{
            "`datasets` version": version,
            "Platform": platform.platform(),
            "Python version": platform.python_version(),
            "Huggingface_hub version": huggingface_hub.__version__,
            "PyArrow version": pyarrow.__version__,
            "Pandas version": pandas.__version__,
        }

        print("\nCopy-and-paste the text below in your GitHub issue.\n"	)
        print(self.format_dict(_UpperCAmelCase	)	)

        return info


   @staticmethod
   def 						snake_case__						(  _UpperCAmelCase	):
        '''simple docstring'''



        return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]	) + "\n"




