





from collections import OrderedDict

from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES


_lowerCamelCase   				=			logging.get_logger(__name__)


_lowerCamelCase   				=			OrderedDict(
    [
        # Base model mapping
        ('albert', 'FlaxAlbertModel'),
        ('bart', 'FlaxBartModel'),
        ('beit', 'FlaxBeitModel'),
        ('bert', 'FlaxBertModel'),
        ('big_bird', 'FlaxBigBirdModel'),
        ('blenderbot', 'FlaxBlenderbotModel'),
        ('blenderbot-small', 'FlaxBlenderbotSmallModel'),
        ('clip', 'FlaxCLIPModel'),
        ('distilbert', 'FlaxDistilBertModel'),
        ('electra', 'FlaxElectraModel'),
        ('gpt-sw3', 'FlaxGPT2Model'),
        ('gpt2', 'FlaxGPT2Model'),
        ('gpt_neo', 'FlaxGPTNeoModel'),
        ('gptj', 'FlaxGPTJModel'),
        ('longt5', 'FlaxLongT5Model'),
        ('marian', 'FlaxMarianModel'),
        ('mbart', 'FlaxMBartModel'),
        ('mt5', 'FlaxMT5Model'),
        ('opt', 'FlaxOPTModel'),
        ('pegasus', 'FlaxPegasusModel'),
        ('regnet', 'FlaxRegNetModel'),
        ('resnet', 'FlaxResNetModel'),
        ('roberta', 'FlaxRobertaModel'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormModel'),
        ('roformer', 'FlaxRoFormerModel'),
        ('t5', 'FlaxT5Model'),
        ('vision-text-dual-encoder', 'FlaxVisionTextDualEncoderModel'),
        ('vit', 'FlaxViTModel'),
        ('wav2vec2', 'FlaxWav2Vec2Model'),
        ('whisper', 'FlaxWhisperModel'),
        ('xglm', 'FlaxXGLMModel'),
        ('xlm-roberta', 'FlaxXLMRobertaModel'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for pre-training mapping
        ('albert', 'FlaxAlbertForPreTraining'),
        ('bart', 'FlaxBartForConditionalGeneration'),
        ('bert', 'FlaxBertForPreTraining'),
        ('big_bird', 'FlaxBigBirdForPreTraining'),
        ('electra', 'FlaxElectraForPreTraining'),
        ('longt5', 'FlaxLongT5ForConditionalGeneration'),
        ('mbart', 'FlaxMBartForConditionalGeneration'),
        ('mt5', 'FlaxMT5ForConditionalGeneration'),
        ('roberta', 'FlaxRobertaForMaskedLM'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormForMaskedLM'),
        ('roformer', 'FlaxRoFormerForMaskedLM'),
        ('t5', 'FlaxT5ForConditionalGeneration'),
        ('wav2vec2', 'FlaxWav2Vec2ForPreTraining'),
        ('whisper', 'FlaxWhisperForConditionalGeneration'),
        ('xlm-roberta', 'FlaxXLMRobertaForMaskedLM'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Masked LM mapping
        ('albert', 'FlaxAlbertForMaskedLM'),
        ('bart', 'FlaxBartForConditionalGeneration'),
        ('bert', 'FlaxBertForMaskedLM'),
        ('big_bird', 'FlaxBigBirdForMaskedLM'),
        ('distilbert', 'FlaxDistilBertForMaskedLM'),
        ('electra', 'FlaxElectraForMaskedLM'),
        ('mbart', 'FlaxMBartForConditionalGeneration'),
        ('roberta', 'FlaxRobertaForMaskedLM'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormForMaskedLM'),
        ('roformer', 'FlaxRoFormerForMaskedLM'),
        ('xlm-roberta', 'FlaxXLMRobertaForMaskedLM'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Seq2Seq Causal LM mapping
        ('bart', 'FlaxBartForConditionalGeneration'),
        ('blenderbot', 'FlaxBlenderbotForConditionalGeneration'),
        ('blenderbot-small', 'FlaxBlenderbotSmallForConditionalGeneration'),
        ('encoder-decoder', 'FlaxEncoderDecoderModel'),
        ('longt5', 'FlaxLongT5ForConditionalGeneration'),
        ('marian', 'FlaxMarianMTModel'),
        ('mbart', 'FlaxMBartForConditionalGeneration'),
        ('mt5', 'FlaxMT5ForConditionalGeneration'),
        ('pegasus', 'FlaxPegasusForConditionalGeneration'),
        ('t5', 'FlaxT5ForConditionalGeneration'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Image-classsification
        ('beit', 'FlaxBeitForImageClassification'),
        ('regnet', 'FlaxRegNetForImageClassification'),
        ('resnet', 'FlaxResNetForImageClassification'),
        ('vit', 'FlaxViTForImageClassification'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        ('vision-encoder-decoder', 'FlaxVisionEncoderDecoderModel'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Causal LM mapping
        ('bart', 'FlaxBartForCausalLM'),
        ('bert', 'FlaxBertForCausalLM'),
        ('big_bird', 'FlaxBigBirdForCausalLM'),
        ('electra', 'FlaxElectraForCausalLM'),
        ('gpt-sw3', 'FlaxGPT2LMHeadModel'),
        ('gpt2', 'FlaxGPT2LMHeadModel'),
        ('gpt_neo', 'FlaxGPTNeoForCausalLM'),
        ('gptj', 'FlaxGPTJForCausalLM'),
        ('opt', 'FlaxOPTForCausalLM'),
        ('roberta', 'FlaxRobertaForCausalLM'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormForCausalLM'),
        ('xglm', 'FlaxXGLMForCausalLM'),
        ('xlm-roberta', 'FlaxXLMRobertaForCausalLM'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Sequence Classification mapping
        ('albert', 'FlaxAlbertForSequenceClassification'),
        ('bart', 'FlaxBartForSequenceClassification'),
        ('bert', 'FlaxBertForSequenceClassification'),
        ('big_bird', 'FlaxBigBirdForSequenceClassification'),
        ('distilbert', 'FlaxDistilBertForSequenceClassification'),
        ('electra', 'FlaxElectraForSequenceClassification'),
        ('mbart', 'FlaxMBartForSequenceClassification'),
        ('roberta', 'FlaxRobertaForSequenceClassification'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormForSequenceClassification'),
        ('roformer', 'FlaxRoFormerForSequenceClassification'),
        ('xlm-roberta', 'FlaxXLMRobertaForSequenceClassification'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Question Answering mapping
        ('albert', 'FlaxAlbertForQuestionAnswering'),
        ('bart', 'FlaxBartForQuestionAnswering'),
        ('bert', 'FlaxBertForQuestionAnswering'),
        ('big_bird', 'FlaxBigBirdForQuestionAnswering'),
        ('distilbert', 'FlaxDistilBertForQuestionAnswering'),
        ('electra', 'FlaxElectraForQuestionAnswering'),
        ('mbart', 'FlaxMBartForQuestionAnswering'),
        ('roberta', 'FlaxRobertaForQuestionAnswering'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormForQuestionAnswering'),
        ('roformer', 'FlaxRoFormerForQuestionAnswering'),
        ('xlm-roberta', 'FlaxXLMRobertaForQuestionAnswering'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Token Classification mapping
        ('albert', 'FlaxAlbertForTokenClassification'),
        ('bert', 'FlaxBertForTokenClassification'),
        ('big_bird', 'FlaxBigBirdForTokenClassification'),
        ('distilbert', 'FlaxDistilBertForTokenClassification'),
        ('electra', 'FlaxElectraForTokenClassification'),
        ('roberta', 'FlaxRobertaForTokenClassification'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormForTokenClassification'),
        ('roformer', 'FlaxRoFormerForTokenClassification'),
        ('xlm-roberta', 'FlaxXLMRobertaForTokenClassification'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        # Model for Multiple Choice mapping
        ('albert', 'FlaxAlbertForMultipleChoice'),
        ('bert', 'FlaxBertForMultipleChoice'),
        ('big_bird', 'FlaxBigBirdForMultipleChoice'),
        ('distilbert', 'FlaxDistilBertForMultipleChoice'),
        ('electra', 'FlaxElectraForMultipleChoice'),
        ('roberta', 'FlaxRobertaForMultipleChoice'),
        ('roberta-prelayernorm', 'FlaxRobertaPreLayerNormForMultipleChoice'),
        ('roformer', 'FlaxRoFormerForMultipleChoice'),
        ('xlm-roberta', 'FlaxXLMRobertaForMultipleChoice'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        ('bert', 'FlaxBertForNextSentencePrediction'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        ('speech-encoder-decoder', 'FlaxSpeechEncoderDecoderModel'),
        ('whisper', 'FlaxWhisperForConditionalGeneration'),
    ]
)

_lowerCamelCase   				=			OrderedDict(
    [
        ('whisper', 'FlaxWhisperForAudioClassification'),
    ]
)

_lowerCamelCase   				=			_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_MAPPING_NAMES)
_lowerCamelCase   				=			_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_PRETRAINING_MAPPING_NAMES)
_lowerCamelCase   				=			_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MASKED_LM_MAPPING_NAMES)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES)
_lowerCamelCase   				=			_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES
)
_lowerCamelCase   				=			_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES
)




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_MAPPING



_lowerCamelCase   				=			auto_class_update(FlaxAutoModel)




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_PRETRAINING_MAPPING



_lowerCamelCase   				=			auto_class_update(FlaxAutoModelForPreTraining, head_doc='pretraining')




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_CAUSAL_LM_MAPPING



_lowerCamelCase   				=			auto_class_update(FlaxAutoModelForCausalLM, head_doc='causal language modeling')




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_MASKED_LM_MAPPING



_lowerCamelCase   				=			auto_class_update(FlaxAutoModelForMaskedLM, head_doc='masked language modeling')




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING



_lowerCamelCase   				=			auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc='sequence-to-sequence language modeling', checkpoint_for_example='t5-base'
)




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING



_lowerCamelCase   				=			auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc='sequence classification'
)




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING



_lowerCamelCase   				=			auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc='question answering')




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING



_lowerCamelCase   				=			auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc='token classification'
)




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING



_lowerCamelCase   				=			auto_class_update(FlaxAutoModelForMultipleChoice, head_doc='multiple choice')




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING



_lowerCamelCase   				=			auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc='next sentence prediction'
)




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING



_lowerCamelCase   				=			auto_class_update(
    FlaxAutoModelForImageClassification, head_doc='image classification'
)




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING



_lowerCamelCase   				=			auto_class_update(FlaxAutoModelForVisionaSeq, head_doc='vision-to-text modeling')




class   UpperCamelCase_       (     _BaseAutoModelClass    ):
							lowerCamelCase_           =					FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING



_lowerCamelCase   				=			auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc='sequence-to-sequence speech-to-text modeling'
)






import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


_lowerCamelCase   				=			'\\n    Text data.\n    Second line of data.'

_lowerCamelCase   				=			'file'






@pytest.fixture(scope="""session"""    )
def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							Any    ):
		SCREAMING_SNAKE_CASE__			=      tmp_path_factory.mktemp("""data"""    ) / (FILE_PATH + """.zstd""")
		SCREAMING_SNAKE_CASE__			=      bytes(UpperCamelCase__					,   """utf-8"""    )
		with zstd.open(UpperCamelCase__					,   """wb"""    ) as f:
				f.write(UpperCamelCase__    )
		return path






@pytest.fixture
def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							List[str]    ):
		with open(os.path.join(tmpfs.local_root_dir					,   UpperCamelCase__    )					,   """w"""    ) as f:
				f.write(UpperCamelCase__    )
		return FILE_PATH






@pytest.mark.parametrize("""compression_format"""					,   ["""gzip""", """xz""", """zstd"""]    )
def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							int					,   UpperCamelCase__:							Dict					,   UpperCamelCase__:							int					,   UpperCamelCase__:							str					,   UpperCamelCase__:							Optional[int]					,   UpperCamelCase__:							Optional[Any]    ):
		SCREAMING_SNAKE_CASE__			=      {"""gzip""": gz_file, """xz""": xz_file, """zstd""": zstd_path}
		SCREAMING_SNAKE_CASE__			=      input_paths[compression_format]
		SCREAMING_SNAKE_CASE__			=      tmp_path / """cache"""
		SCREAMING_SNAKE_CASE__			=      DownloadConfig(cache_dir=UpperCamelCase__					,   extract_compressed_file=UpperCamelCase__    )
		SCREAMING_SNAKE_CASE__			=      cached_path(UpperCamelCase__					,   download_config=UpperCamelCase__    )
		with open(UpperCamelCase__    ) as f:
				SCREAMING_SNAKE_CASE__			=      f.read()
		with open(UpperCamelCase__    ) as f:
				SCREAMING_SNAKE_CASE__			=      f.read()
		assert extracted_file_content == expected_file_content






@pytest.mark.parametrize("""default_extracted"""					,   [True, False]    )
@pytest.mark.parametrize("""default_cache_dir"""					,   [True, False]    )
def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							Tuple					,   UpperCamelCase__:							List[str]					,   UpperCamelCase__:							Optional[int]					,   UpperCamelCase__:							Any					,   UpperCamelCase__:							Union[str, Any]    ):
		SCREAMING_SNAKE_CASE__			=      """custom_cache"""
		SCREAMING_SNAKE_CASE__			=      """custom_extracted_dir"""
		SCREAMING_SNAKE_CASE__			=      tmp_path / """custom_extracted_path"""
		if default_extracted:
				SCREAMING_SNAKE_CASE__			=      ("""downloads""" if default_cache_dir else custom_cache_dir, """extracted""")
		else:
				monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_DIR"""					,   UpperCamelCase__    )
				monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_PATH"""					,   str(UpperCamelCase__    )    )
				SCREAMING_SNAKE_CASE__			=      custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

		SCREAMING_SNAKE_CASE__			=      xz_file
		SCREAMING_SNAKE_CASE__			=      (
		    DownloadConfig(extract_compressed_file=UpperCamelCase__    )
		    if default_cache_dir
		    else DownloadConfig(cache_dir=tmp_path / custom_cache_dir					,   extract_compressed_file=UpperCamelCase__    )
		)
		SCREAMING_SNAKE_CASE__			=      cached_path(UpperCamelCase__					,   download_config=UpperCamelCase__    )
		assert Path(UpperCamelCase__    ).parent.parts[-2:] == expected






def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							Optional[int]    ):
		# absolute path
		SCREAMING_SNAKE_CASE__			=      str(Path(UpperCamelCase__    ).resolve()    )
		assert cached_path(UpperCamelCase__    ) == text_file
		# relative path
		SCREAMING_SNAKE_CASE__			=      str(Path(UpperCamelCase__    ).resolve().relative_to(Path(os.getcwd()    )    )    )
		assert cached_path(UpperCamelCase__    ) == text_file






def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							List[str]    ):
		# absolute path
		SCREAMING_SNAKE_CASE__			=      str(tmp_path.resolve() / """__missing_file__.txt"""    )
		with pytest.raises(UpperCamelCase__    ):
				cached_path(UpperCamelCase__    )
		# relative path
		SCREAMING_SNAKE_CASE__			=      """./__missing_file__.txt"""
		with pytest.raises(UpperCamelCase__    ):
				cached_path(UpperCamelCase__    )






def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							List[str]    ):
		SCREAMING_SNAKE_CASE__			=      get_from_cache(f'''tmp://{tmpfs_file}'''    )
		with open(UpperCamelCase__    ) as f:
				SCREAMING_SNAKE_CASE__			=      f.read()
		assert output_file_content == FILE_CONTENT






@patch("""datasets.config.HF_DATASETS_OFFLINE"""					,   UpperCamelCase__    )
def 				SCREAMING_SNAKE_CASE__							(       ):
		with pytest.raises(UpperCamelCase__    ):
				cached_path("""https://huggingface.co"""    )






@patch("""datasets.config.HF_DATASETS_OFFLINE"""					,   UpperCamelCase__    )
def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							Optional[Any]    ):
		SCREAMING_SNAKE_CASE__			=      tmp_path_factory.mktemp("""data"""    ) / """file.html"""
		with pytest.raises(UpperCamelCase__    ):
				http_get("""https://huggingface.co"""					,   temp_file=UpperCamelCase__    )
		with pytest.raises(UpperCamelCase__    ):
				http_head("""https://huggingface.co"""    )






@patch("""datasets.config.HF_DATASETS_OFFLINE"""					,   UpperCamelCase__    )
def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							List[Any]    ):
		SCREAMING_SNAKE_CASE__			=      tmp_path_factory.mktemp("""data"""    ) / """file.html"""
		with pytest.raises(UpperCamelCase__    ):
				ftp_get("""ftp://huggingface.co"""					,   temp_file=UpperCamelCase__    )
		with pytest.raises(UpperCamelCase__    ):
				ftp_head("""ftp://huggingface.co"""    )






@patch("""datasets.config.HF_DATASETS_OFFLINE"""					,   UpperCamelCase__    )
def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							int    ):
		SCREAMING_SNAKE_CASE__			=      tmp_path_factory.mktemp("""data"""    ) / """file.html"""
		with pytest.raises(UpperCamelCase__    ):
				fsspec_get("""s3://huggingface.co"""					,   temp_file=UpperCamelCase__    )
		with pytest.raises(UpperCamelCase__    ):
				fsspec_head("""s3://huggingface.co"""    )