



'''simple docstring'''





from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase			):



    """simple docstring"""





    lowerCAmelCase__      ,   lowerCAmelCase__ :  List[str]							      =					analyze_text(UpperCamelCase			)
    lowerCAmelCase__ :  Optional[int]							      =					list(""" """ + ascii_lowercase			)
    # what is our total sum of probabilities.
    lowerCAmelCase__ :  List[Any]							      =					sum(single_char_strings.values()			)

    # one length string
    lowerCAmelCase__ :  Optional[int]							      =					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:
            lowerCAmelCase__ :  List[Any]							      =					single_char_strings[ch]
            lowerCAmelCase__ :  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
    lowerCAmelCase__ :  Dict							      =					sum(two_char_strings.values()			)
    lowerCAmelCase__ :  int							      =					0
    # for each alpha (two in size) calculate entropy.
    for cha in my_alphas:
        for cha in my_alphas:
            lowerCAmelCase__ :  Union[str, Any]							      =					cha + cha
            if sequence in two_char_strings:
                lowerCAmelCase__ :  Dict							      =					two_char_strings[sequence]
                lowerCAmelCase__ :  Tuple							      =					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    _SCREAMING_SNAKE_CASE  (       UpperCamelCase			):



    """simple docstring"""





    lowerCAmelCase__ :  Optional[Any]							      =					Counter()  # type: ignore
    lowerCAmelCase__ :  Tuple							      =					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    _SCREAMING_SNAKE_CASE  (       ):



    """simple docstring"""





    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()







'''simple docstring'''





# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# this script dumps information about the environment

import os
import sys

import transformers


_lowerCAmelCase      						=	'''3'''

print('''Python version:''', sys.version)
print('''transformers version:''', transformers.__version__)

try:
 import torch

 print('''Torch version:''', torch.__version__)
 print('''Cuda available:''', torch.cuda.is_available())
 print('''Cuda version:''', torch.version.cuda)
 print('''CuDNN version:''', torch.backends.cudnn.version())
 print('''Number of GPUs available:''', torch.cuda.device_count())
 print('''NCCL version:''', torch.cuda.nccl.version())
except ImportError:
 print('''Torch version:''', None)

try:
 import deepspeed

 print('''DeepSpeed version:''', deepspeed.__version__)
except ImportError:
 print('''DeepSpeed version:''', None)

try:
 import tensorflow as tf

 print('''TensorFlow version:''', tf.__version__)
 print('''TF GPUs available:''', bool(tf.config.list_physical_devices('''GPU''')))
 print('''Number of TF GPUs available:''', len(tf.config.list_physical_devices('''GPU''')))
except ImportError:
 print('''TensorFlow version:''', None)


