





from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase




def 		lowerCAmelCase_    (  __UpperCAmelCase:			str      )      ->	None:
    UpperCamelCase__   ,UpperCamelCase__							:				Dict          =      analyze_text(__UpperCAmelCase      )
    UpperCamelCase__							:				Tuple          =      list(''' ''' + ascii_lowercase      )
    # what is our total sum of probabilities.
    UpperCamelCase__							:				str          =      sum(single_char_strings.values()      )

    # one length string
    UpperCamelCase__							:				List[Any]          =      0
    # for each alpha we go in our dict and if it is in it we calculate entropy
    for ch in my_alphas:
        if ch in single_char_strings:
            UpperCamelCase__							:				Tuple          =      single_char_strings[ch]
            UpperCamelCase__							:				List[Any]          =      my_str / all_sum
            my_fir_sum += prob * math.loga(__UpperCAmelCase      )  # entropy formula.

    # print entropy
    print(f"{round(-1 * my_fir_sum      ):.1f}"      )

    # two len string
    UpperCamelCase__							:				str          =      sum(two_char_strings.values()      )
    UpperCamelCase__							:				str          =      0
    # for each alpha (two in size) calculate entropy.
    for cha in my_alphas:
        for cha in my_alphas:
            UpperCamelCase__							:				Union[str, Any]          =      cha + cha
            if sequence in two_char_strings:
                UpperCamelCase__							:				Any          =      two_char_strings[sequence]
                UpperCamelCase__							:				List[Any]          =      int(__UpperCAmelCase      ) / all_sum
                my_sec_sum += prob * math.loga(__UpperCAmelCase      )

    # print second entropy
    print(f"{round(-1 * my_sec_sum      ):.1f}"      )

    # print the difference between them
    print(f"{round((-1 * my_sec_sum) - (-1 * my_fir_sum)      ):.1f}"      )




def 		lowerCAmelCase_    (  __UpperCAmelCase:			str      )      ->	tuple[dict, dict]:
    UpperCamelCase__							:				Dict          =      Counter()  # type: ignore
    UpperCamelCase__							:				Union[str, Any]          =      Counter()  # type: ignore
    single_char_strings[text[-1]] += 1

    # first case when we have space at start.
    two_char_strings[" " + text[0]] += 1
    for i in range(0		,   len(__UpperCAmelCase      ) - 1      ):
        single_char_strings[text[i]] += 1
        two_char_strings[text[i : i + 2]] += 1
    return single_char_strings, two_char_strings




def 		lowerCAmelCase_    (  )      ->	List[Any]:
    import doctest

    doctest.testmod()
    # text = (
    #     "Had repulsive dashwoods suspicion sincerity but advantage now him. Remark "
    #     "easily garret nor nay. Civil those mrs enjoy shy fat merry. You greatest "
    #     "jointure saw horrible. He private he on be imagine suppose. Fertile "
    #     "beloved evident through no service elderly is. Blind there if every no so "
    #     "at. Own neglected you preferred way sincerity delivered his attempted. To "
    #     "of message cottage windows do besides against uncivil.  Delightful "
    #     "unreserved impossible few estimating men favourable see entreaties. She "
    #     "propriety immediate was improving. He or entrance humoured likewise "
    #     "moderate. Much nor game son say feel. Fat make met can must form into "
    #     "gate. Me we offending prevailed discovery. "
    # )

    # calculate_prob(text)


if __name__ == "__main__":
  main()








from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_     							= logging.get_logger(__name__)

UpperCAmelCase_     							= {
    'google/mobilenet_v2_1.4_224': 'https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json',
    'google/mobilenet_v2_1.0_224': 'https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json',
    'google/mobilenet_v2_0.75_160': 'https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json',
    'google/mobilenet_v2_0.35_96': 'https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}






class     lowercase__       (	__lowerCamelCase				):

   '''simple docstring'''


   a						:							List[str]   		=		"mobilenet_v2"




   def __init__(    self,		__magic_name__=3,		__magic_name__=224,		__magic_name__=1.0,		__magic_name__=8,		__magic_name__=8,		__magic_name__=6,		__magic_name__=32,		__magic_name__=True,		__magic_name__=True,		__magic_name__="relu6",		__magic_name__=True,		__magic_name__=0.8,		__magic_name__=0.02,		__magic_name__=0.001,		__magic_name__=255,		**__magic_name__,		) ->      List[Any]:






       """simple docstring"""
       super().__init__(**__magic_name__							)

       if depth_multiplier <= 0:
           raise ValueError('''depth_multiplier must be greater than zero.'''							)

       UpperCamelCase__							:				Union[str, Any]          =      num_channels
       UpperCamelCase__							:				int          =      image_size
       UpperCamelCase__							:				int          =      depth_multiplier
       UpperCamelCase__							:				Tuple          =      depth_divisible_by
       UpperCamelCase__							:				List[str]          =      min_depth
       UpperCamelCase__							:				Optional[int]          =      expand_ratio
       UpperCamelCase__							:				Optional[int]          =      output_stride
       UpperCamelCase__							:				Tuple          =      first_layer_is_expansion
       UpperCamelCase__							:				Union[str, Any]          =      finegrained_output
       UpperCamelCase__							:				str          =      hidden_act
       UpperCamelCase__							:				Optional[Any]          =      tf_padding
       UpperCamelCase__							:				Optional[int]          =      classifier_dropout_prob
       UpperCamelCase__							:				int          =      initializer_range
       UpperCamelCase__							:				Union[str, Any]          =      layer_norm_eps
       UpperCamelCase__							:				Tuple          =      semantic_loss_ignore_index






class     lowercase__       (	__lowerCamelCase				):

   '''simple docstring'''


   a						:							Union[str, Any]   		=		version.parse("1.11"				)




   @property
   def       UpperCamelCase__  (    self							) ->      Mapping[str, Mapping[int, str]]:






       """simple docstring"""
       return OrderedDict([('''pixel_values''', {0: '''batch'''})]							)




   @property
   def       UpperCamelCase__  (    self							) ->      Mapping[str, Mapping[int, str]]:






       """simple docstring"""
       if self.task == "image-classification":
           return OrderedDict([('''logits''', {0: '''batch'''})]							)
       else:
           return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]							)




   @property
   def       UpperCamelCase__  (    self							) ->      float:






       """simple docstring"""
       return 1E-4

