'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


SCREAMING_SNAKE_CASE_:					str					={
    'configuration_clip': [
        'CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'CLIPConfig',
        'CLIPOnnxConfig',
        'CLIPTextConfig',
        'CLIPVisionConfig',
    ],
    'processing_clip': ['CLIPProcessor'],
    'tokenization_clip': ['CLIPTokenizer'],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					Any					=['CLIPTokenizerFast']

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					Optional[Any]					=['CLIPFeatureExtractor']
    SCREAMING_SNAKE_CASE_:					str					=['CLIPImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					Optional[int]					=[
        'CLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'CLIPModel',
        'CLIPPreTrainedModel',
        'CLIPTextModel',
        'CLIPTextModelWithProjection',
        'CLIPVisionModel',
        'CLIPVisionModelWithProjection',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					Tuple					=[
        'TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'TFCLIPModel',
        'TFCLIPPreTrainedModel',
        'TFCLIPTextModel',
        'TFCLIPVisionModel',
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					Optional[int]					=[
        'FlaxCLIPModel',
        'FlaxCLIPPreTrainedModel',
        'FlaxCLIPTextModel',
        'FlaxCLIPTextPreTrainedModel',
        'FlaxCLIPVisionModel',
        'FlaxCLIPVisionPreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_clip import (
        CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
        CLIPConfig,
        CLIPOnnxConfig,
        CLIPTextConfig,
        CLIPVisionConfig,
    )
    from .processing_clip import CLIPProcessor
    from .tokenization_clip import CLIPTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_clip_fast import CLIPTokenizerFast

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_clip import CLIPFeatureExtractor
        from .image_processing_clip import CLIPImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_clip import (
            CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
            CLIPModel,
            CLIPPreTrainedModel,
            CLIPTextModel,
            CLIPTextModelWithProjection,
            CLIPVisionModel,
            CLIPVisionModelWithProjection,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_clip import (
            TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFCLIPModel,
            TFCLIPPreTrainedModel,
            TFCLIPTextModel,
            TFCLIPVisionModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_clip import (
            FlaxCLIPModel,
            FlaxCLIPPreTrainedModel,
            FlaxCLIPTextModel,
            FlaxCLIPTextPreTrainedModel,
            FlaxCLIPVisionModel,
            FlaxCLIPVisionPreTrainedModel,
        )


else:
    import sys

    SCREAMING_SNAKE_CASE_:					List[Any]					=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





'''simple docstring'''





from random import randint
from tempfile import TemporaryFile

import numpy as np





def      lowerCAmelCase_    ( snake_case_	:			int ,   snake_case_	:			Any ,   snake_case_	:			int      )   ->				Optional[Any]:


     '''simple docstring'''




     UpperCAmelCase_	   =       0
     if start < end:
          UpperCAmelCase_	   =       randint(snake_case_ ,   snake_case_      )
          UpperCAmelCase_	   =       a[end]
          UpperCAmelCase_	   =       a[pivot]
          UpperCAmelCase_	   =       temp

          UpperCAmelCase_   ,			UpperCAmelCase_	   =       _in_place_partition(snake_case_ ,   snake_case_ ,   snake_case_      )
          count += _in_place_quick_sort(snake_case_ ,   snake_case_ ,   p - 1      )
          count += _in_place_quick_sort(snake_case_ ,   p + 1 ,   snake_case_      )
     return count





def      lowerCAmelCase_    ( snake_case_	:			List[Any] ,   snake_case_	:			Dict ,   snake_case_	:			List[str]      )   ->				Optional[int]:


     '''simple docstring'''




     UpperCAmelCase_	   =       0
     UpperCAmelCase_	   =       randint(snake_case_ ,   snake_case_      )
     UpperCAmelCase_	   =       a[end]
     UpperCAmelCase_	   =       a[pivot]
     UpperCAmelCase_	   =       temp
     UpperCAmelCase_	   =       start - 1
     for index in range(snake_case_ ,   snake_case_      ):
          count += 1
          if a[index] < a[end]:  # check if current val is less than pivot value
               UpperCAmelCase_	   =       new_pivot_index + 1
               UpperCAmelCase_	   =       a[new_pivot_index]
               UpperCAmelCase_	   =       a[index]
               UpperCAmelCase_	   =       temp

     UpperCAmelCase_	   =       a[new_pivot_index + 1]
     UpperCAmelCase_	   =       a[end]
     UpperCAmelCase_	   =       temp
     return new_pivot_index + 1, count


SCREAMING_SNAKE_CASE_:					List[str]  =TemporaryFile()
SCREAMING_SNAKE_CASE_:					int  =1_00  # 1000 elements are to be sorted


SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_:					str  =0, 1  # mean and standard deviation
SCREAMING_SNAKE_CASE_:					List[str]  =np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('The array is')
print(X)


outfile.seek(0)  # using the same array
SCREAMING_SNAKE_CASE_:					str  =np.load(outfile)
SCREAMING_SNAKE_CASE_:					List[Any]  =len(M) - 1
SCREAMING_SNAKE_CASE_:					Dict  =_in_place_quick_sort(M, 0, r)

print(
    'No of Comparisons for 100 elements selected from a standard normal distribution'
    'is :'
)






print(z)




