import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
					from PIL import Image

					from transformers import CLIPSegProcessor, ViTImageProcessor





@require_vision
class 					lowercase__						(   unittest.TestCase):


						def        __A       (       self	:				List[Any]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Dict							=							tempfile.mkdtemp()

												# fmt: off
												SCREAMING_SNAKE_CASE							:    Any							=							['''l''', '''o''', '''w''', '''e''', '''r''', '''s''', '''t''', '''i''', '''d''', '''n''', '''lo''', '''l</w>''', '''w</w>''', '''r</w>''', '''t</w>''', '''low</w>''', '''er</w>''', '''lowest</w>''', '''newer</w>''', '''wider''', '''<unk>''', '''<|startoftext|>''', '''<|endoftext|>''']
												# fmt: on
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							dict(zip(UpperCamelCase__    ,		range(len(UpperCamelCase__						)						)						)						)
												SCREAMING_SNAKE_CASE							:    List[Any]							=							['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
												SCREAMING_SNAKE_CASE							:    int							=							{'''unk_token''': '''<unk>'''}

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

												SCREAMING_SNAKE_CASE							:    List[str]							=							{
												    '''do_resize''': True,
												    '''size''': 20,
												    '''do_center_crop''': True,
												    '''crop_size''': 18,
												    '''do_normalize''': True,
												    '''image_mean''': [0.4814_5466, 0.457_8275, 0.4082_1073],
												    '''image_std''': [0.2686_2954, 0.2613_0258, 0.2757_7711],
												}
												SCREAMING_SNAKE_CASE							:    Optional[int]							=							os.path.join(self.tmpdirname    ,		UpperCamelCase__						)
												with open(self.image_processor_file    ,		'''w'''    ,		encoding='''utf-8'''						) as fp:
																		json.dump(UpperCamelCase__    ,		UpperCamelCase__						)


						def        __A       (       self	:				str    ,		**UpperCamelCase__	:				Any						):





												'''simple docstring'''





												return CLIPTokenizer.from_pretrained(self.tmpdirname    ,		**UpperCamelCase__						)


						def        __A       (       self	:				int    ,		**UpperCamelCase__	:				List[Any]						):





												'''simple docstring'''





												return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,		**UpperCamelCase__						)


						def        __A       (       self	:				List[str]    ,		**UpperCamelCase__	:				str						):





												'''simple docstring'''





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


						def        __A       (       self	:				List[Any]						):





												'''simple docstring'''





												shutil.rmtree(self.tmpdirname						)


						def        __A       (       self	:				int						):





												'''simple docstring'''





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

												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							[Image.fromarray(np.moveaxis(UpperCamelCase__    ,		0    ,		-1						)						) for x in image_inputs]

												return image_inputs


						def        __A       (       self	:				List[Any]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    int							=							self.get_tokenizer()
												SCREAMING_SNAKE_CASE							:    Tuple							=							self.get_rust_tokenizer()
												SCREAMING_SNAKE_CASE							:    List[str]							=							self.get_image_processor()

												SCREAMING_SNAKE_CASE							:    Dict							=							CLIPSegProcessor(tokenizer=UpperCamelCase__    ,		image_processor=UpperCamelCase__						)
												processor_slow.save_pretrained(self.tmpdirname						)
												SCREAMING_SNAKE_CASE							:    int							=							CLIPSegProcessor.from_pretrained(self.tmpdirname    ,		use_fast=UpperCamelCase__						)

												SCREAMING_SNAKE_CASE							:    str							=							CLIPSegProcessor(tokenizer=UpperCamelCase__    ,		image_processor=UpperCamelCase__						)
												processor_fast.save_pretrained(self.tmpdirname						)
												SCREAMING_SNAKE_CASE							:    Any							=							CLIPSegProcessor.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    ,		UpperCamelCase__						)
												self.assertIsInstance(processor_fast.tokenizer    ,		UpperCamelCase__						)

												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    ,		UpperCamelCase__						)
												self.assertIsInstance(processor_fast.image_processor    ,		UpperCamelCase__						)


						def        __A       (       self	:				Dict						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    int							=							CLIPSegProcessor(tokenizer=self.get_tokenizer()    ,		image_processor=self.get_image_processor()						)
												processor.save_pretrained(self.tmpdirname						)

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

												SCREAMING_SNAKE_CASE							:    List[str]							=							CLIPSegProcessor.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        __A       (       self	:				Optional[Any]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Dict							=							self.get_image_processor()
												SCREAMING_SNAKE_CASE							:    Dict							=							self.get_tokenizer()

												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							CLIPSegProcessor(tokenizer=UpperCamelCase__    ,		image_processor=UpperCamelCase__						)

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

												SCREAMING_SNAKE_CASE							:    Tuple							=							image_processor(UpperCamelCase__    ,		return_tensors='''np'''						)
												SCREAMING_SNAKE_CASE							:    int							=							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        __A       (       self	:				List[Any]						):





												'''simple docstring'''





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

												SCREAMING_SNAKE_CASE							:    List[Any]							=							CLIPSegProcessor(tokenizer=UpperCamelCase__    ,		image_processor=UpperCamelCase__						)

												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							'''lower newer'''

												SCREAMING_SNAKE_CASE							:    Dict							=							processor(text=UpperCamelCase__						)

												SCREAMING_SNAKE_CASE							:    Dict							=							tokenizer(UpperCamelCase__						)

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


						def        __A       (       self	:				Optional[int]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    List[Any]							=							self.get_image_processor()
												SCREAMING_SNAKE_CASE							:    List[str]							=							self.get_tokenizer()

												SCREAMING_SNAKE_CASE							:    List[Any]							=							CLIPSegProcessor(tokenizer=UpperCamelCase__    ,		image_processor=UpperCamelCase__						)

												SCREAMING_SNAKE_CASE							:    Dict							=							'''lower newer'''
												SCREAMING_SNAKE_CASE							:    Tuple							=							self.prepare_image_inputs()

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

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

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


						def        __A       (       self	:				List[Any]						):





												'''simple docstring'''





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

												SCREAMING_SNAKE_CASE							:    Optional[int]							=							CLIPSegProcessor(tokenizer=UpperCamelCase__    ,		image_processor=UpperCamelCase__						)

												SCREAMING_SNAKE_CASE							:    Any							=							self.prepare_image_inputs()
												SCREAMING_SNAKE_CASE							:    int							=							self.prepare_image_inputs()

												SCREAMING_SNAKE_CASE							:    Dict							=							processor(images=UpperCamelCase__    ,		visual_prompt=UpperCamelCase__						)

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

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



						def        __A       (       self	:				str						):





												'''simple docstring'''





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

												SCREAMING_SNAKE_CASE							:    Tuple							=							CLIPSegProcessor(tokenizer=UpperCamelCase__    ,		image_processor=UpperCamelCase__						)

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

												SCREAMING_SNAKE_CASE							:    Any							=							processor.batch_decode(UpperCamelCase__						)
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							tokenizer.batch_decode(UpperCamelCase__						)

												self.assertListEqual(UpperCamelCase__    ,		UpperCamelCase__						)






import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
    '''split_dict'''		,  [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train'''		,  num_bytes=1_337		,  num_examples=42		,  dataset_name='''my_dataset'''						)}						),
        SplitDict({'''train''': SplitInfo(name='''train'''		,  num_bytes=1_337		,  num_examples=42						)}						),
        SplitDict({'''train''': SplitInfo()}						),
    ]		,  )
def       A	(    _lowercase						):
						SCREAMING_SNAKE_CASE							:    Tuple							=							split_dict._to_yaml_list()
						assert len(_lowercase						) == len(_lowercase						)
						SCREAMING_SNAKE_CASE							:    Tuple							=							SplitDict._from_yaml_list(_lowercase						)
						for split_name, split_info in split_dict.items():
												# dataset_name field is deprecated, and is therefore not part of the YAML dump
												SCREAMING_SNAKE_CASE							:    Any							=							None
												# the split name of split_dict takes over the name of the split info object
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							split_name
						assert split_dict == reloaded



@pytest.mark.parametrize(
    '''split_info'''		,  [SplitInfo(), SplitInfo(dataset_name=_lowercase						), SplitInfo(dataset_name='''my_dataset'''						)]						)
def       A	(    _lowercase						):
						# For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
						# field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
						SCREAMING_SNAKE_CASE							:    List[Any]							=							asdict(SplitDict({'''train''': split_info}						)						)
						assert "dataset_name" in split_dict_asdict["train"]
						assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name





