


import unittest

import numpy as np

from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
       import jax.numpy as jnp

       from transformers.models.distilbert.modeling_flax_distilbert import (
           FlaxDistilBertForMaskedLM,
           FlaxDistilBertForMultipleChoice,
           FlaxDistilBertForQuestionAnswering,
           FlaxDistilBertForSequenceClassification,
           FlaxDistilBertForTokenClassification,
           FlaxDistilBertModel,
       )





class  lowerCAmelCase__(    unittest.TestCase						):






    '''simple docstring'''





    def __init__(	self				:   Dict       ,   __snake_case				:   Optional[int]       ,   __snake_case				:   int=13       ,   __snake_case				:   Optional[Any]=7       ,   __snake_case				:   Optional[int]=True       ,   __snake_case				:   Optional[int]=True       ,   __snake_case				:   Union[str, Any]=True       ,   __snake_case				:   int=True       ,   __snake_case				:   List[str]=99       ,   __snake_case				:   List[str]=32       ,   __snake_case				:   Tuple=5       ,   __snake_case				:   int=4       ,   __snake_case				:   List[Any]=37       ,   __snake_case				:   str="gelu"       ,   __snake_case				:   Optional[int]=0.1       ,   __snake_case				:   List[Any]=0.1       ,   __snake_case				:   Optional[int]=512       ,   __snake_case				:   Tuple=16       ,   __snake_case				:   List[str]=2       ,   __snake_case				:   List[Any]=0.02       ,   __snake_case				:   Tuple=4       ,   ):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[int]						=   parent
       UpperCAmelCase_							:      Tuple						=   batch_size
       UpperCAmelCase_							:      Union[str, Any]						=   seq_length
       UpperCAmelCase_							:      Tuple						=   is_training
       UpperCAmelCase_							:      Union[str, Any]						=   use_attention_mask
       UpperCAmelCase_							:      Dict						=   use_token_type_ids
       UpperCAmelCase_							:      int						=   use_labels
       UpperCAmelCase_							:      Any						=   vocab_size
       UpperCAmelCase_							:      Optional[int]						=   hidden_size
       UpperCAmelCase_							:      str						=   num_hidden_layers
       UpperCAmelCase_							:      Optional[Any]						=   num_attention_heads
       UpperCAmelCase_							:      List[str]						=   intermediate_size
       UpperCAmelCase_							:      Optional[Any]						=   hidden_act
       UpperCAmelCase_							:      List[str]						=   hidden_dropout_prob
       UpperCAmelCase_							:      Dict						=   attention_probs_dropout_prob
       UpperCAmelCase_							:      List[str]						=   max_position_embeddings
       UpperCAmelCase_							:      Union[str, Any]						=   type_vocab_size
       UpperCAmelCase_							:      str						=   type_sequence_label_size
       UpperCAmelCase_							:      str						=   initializer_range
       UpperCAmelCase_							:      List[Any]						=   num_choices





    def 					_lowerCamelCase (	self				:   Optional[Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[Any]						=   ids_tensor([self.batch_size, self.seq_length]       ,   self.vocab_size	)

       UpperCAmelCase_							:      Optional[int]						=   None
       if self.use_attention_mask:
          UpperCAmelCase_							:      Any						=   random_attention_mask([self.batch_size, self.seq_length]	)

       UpperCAmelCase_							:      List[str]						=   DistilBertConfig(
           vocab_size=self.vocab_size       ,   dim=self.hidden_size       ,   n_layers=self.num_hidden_layers       ,   n_heads=self.num_attention_heads       ,   hidden_dim=self.intermediate_size       ,   hidden_act=self.hidden_act       ,   dropout=self.hidden_dropout_prob       ,   attention_dropout=self.attention_probs_dropout_prob       ,   max_position_embeddings=self.max_position_embeddings       ,   initializer_range=self.initializer_range       ,   tie_weights_=__snake_case       ,   )

       return config, input_ids, attention_mask





    def 					_lowerCamelCase (	self				:   Any	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[Any]						=   self.prepare_config_and_inputs()
       UpperCAmelCase_							:      Tuple						=   config_and_inputs
       UpperCAmelCase_							:      int						=   {'''input_ids''': input_ids, '''attention_mask''': attention_mask}
       return config, inputs_dict





@require_flax
class  lowerCAmelCase__(    snake_case__    ,    unittest.TestCase						):






    '''simple docstring'''





    A_  :     Optional[int]			= (
        (
            FlaxDistilBertModel,
            FlaxDistilBertForMaskedLM,
            FlaxDistilBertForMultipleChoice,
            FlaxDistilBertForQuestionAnswering,
            FlaxDistilBertForSequenceClassification,
            FlaxDistilBertForTokenClassification,
            FlaxDistilBertForQuestionAnswering,
        )
        if is_flax_available()
        else ()
    )





    def 					_lowerCamelCase (	self				:   List[str]	):





       '''simple docstring'''
       UpperCAmelCase_							:      int						=   FlaxDistilBertModelTester(self	)





    @slow
    def 					_lowerCamelCase (	self				:   Optional[int]	):





       '''simple docstring'''
       for model_class_name in self.all_model_classes:
          UpperCAmelCase_							:      str						=   model_class_name.from_pretrained('''distilbert-base-uncased'''	)
          UpperCAmelCase_							:      Union[str, Any]						=   model(np.ones((1, 1)	)	)
          self.assertIsNotNone(__snake_case	)





@require_flax
class  lowerCAmelCase__(    unittest.TestCase						):






    '''simple docstring'''





    @slow
    def 					_lowerCamelCase (	self				:   List[Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[Any]						=   FlaxDistilBertModel.from_pretrained('''distilbert-base-uncased'''	)
       UpperCAmelCase_							:      Optional[Any]						=   np.array([[0, 345, 232, 328, 740, 140, 1_695, 69, 6_078, 1_588, 2]]	)
       UpperCAmelCase_							:      Tuple						=   np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]	)
       UpperCAmelCase_							:      str						=   model(__snake_case       ,   attention_mask=__snake_case	)[0]
       UpperCAmelCase_							:      List[Any]						=   (1, 11, 768)
       self.assertEqual(output.shape       ,   __snake_case	)
       UpperCAmelCase_							:      List[Any]						=   np.array([[[-0.1_639, 0.3_299, 0.1_648], [-0.1_746, 0.3_289, 0.1_710], [-0.1_884, 0.3_357, 0.1_810]]]	)

       self.assertTrue(jnp.allclose(output[:, 1:4, 1:4]       ,   __snake_case       ,   atol=1E-4	)	)



import argparse
import hashlib  # hashlib is only used inside the Test class
import struct





class  lowerCAmelCase__:






    '''simple docstring'''





    def __init__(	self				:   List[str]       ,   __snake_case				:   Union[str, Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      str						=   data
       UpperCAmelCase_							:      List[Any]						=   [0X67_45_23_01, 0Xef_cd_ab_89, 0X98_ba_dc_fe, 0X10_32_54_76, 0Xc3_d2_e1_f0]





    @staticmethod
    def 					_lowerCamelCase (	__snake_case				:   Dict       ,   __snake_case				:   Dict	):





       '''simple docstring'''
       return ((n << b) | (n >> (32 - b))) & 0Xff_ff_ff_ff





    def 					_lowerCamelCase (	self				:   Dict	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[int]						=   B'''\x80''' + B'''\x00''' * (63 - (len(self.data	) + 8) % 64)
       UpperCAmelCase_							:      Union[str, Any]						=   self.data + padding + struct.pack('''>Q'''       ,   8 * len(self.data	)	)
       return padded_data





    def 					_lowerCamelCase (	self				:   Tuple	):





       '''simple docstring'''
       return [
           self.padded_data[i : i + 64] for i in range(0       ,   len(self.padded_data	)       ,   64	)
       ]





    def 					_lowerCamelCase (	self				:   Dict       ,   __snake_case				:   Optional[int]	):





       '''simple docstring'''
       UpperCAmelCase_							:      Any						=   list(struct.unpack('''>16L'''       ,   __snake_case	)	) + [0] * 64
       for i in range(16       ,   80	):
          UpperCAmelCase_							:      str						=   self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16])       ,   1	)
       return w





    def 					_lowerCamelCase (	self				:   Union[str, Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[int]						=   self.padding()
       UpperCAmelCase_							:      str						=   self.split_blocks()
       for block in self.blocks:
          UpperCAmelCase_							:      Any						=   self.expand_block(__snake_case	)
          UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_							:      List[str]						=   self.h
          for i in range(0       ,   80	):
             if 0 <= i < 20:
                UpperCAmelCase_							:      Optional[Any]						=   (b & c) | ((~b) & d)
                UpperCAmelCase_							:      Optional[Any]						=   0X5a_82_79_99
             elif 20 <= i < 40:
                UpperCAmelCase_							:      List[Any]						=   b ^ c ^ d
                UpperCAmelCase_							:      str						=   0X6e_d9_eb_a1
             elif 40 <= i < 60:
                UpperCAmelCase_							:      str						=   (b & c) | (b & d) | (c & d)
                UpperCAmelCase_							:      Optional[int]						=   0X8f_1b_bc_dc
             elif 60 <= i < 80:
                UpperCAmelCase_							:      Union[str, Any]						=   b ^ c ^ d
                UpperCAmelCase_							:      Dict						=   0Xca_62_c1_d6
             UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_							:      int						=   (
                 self.rotate(__snake_case       ,   5	) + f + e + k + expanded_block[i] & 0Xff_ff_ff_ff,
                 a,
                 self.rotate(__snake_case       ,   30	),
                 c,
                 d,
             )
          UpperCAmelCase_							:      Optional[Any]						=   (
              self.h[0] + a & 0Xff_ff_ff_ff,
              self.h[1] + b & 0Xff_ff_ff_ff,
              self.h[2] + c & 0Xff_ff_ff_ff,
              self.h[3] + d & 0Xff_ff_ff_ff,
              self.h[4] + e & 0Xff_ff_ff_ff,
          )
       return ("{:08x}" * 5).format(*self.h	)





def      snake_case_						( ):
   UpperCAmelCase_							:      Tuple						=   B'''Test String'''
   assert SHAaHash(__lowercase       ).final_hash() == hashlib.shaa(__lowercase       ).hexdigest()  # noqa: S324
def      snake_case_						( ):
   UpperCAmelCase_							:      int						=   argparse.ArgumentParser(description='''Process some strings or files'''       )
   parser.add_argument(
       '''--string'''			,       dest='''input_string'''			,       default='''Hello World!! Welcome to Cryptography'''			,       help='''Hash the string'''			,       )
   parser.add_argument('''--file'''			,       dest='''input_file'''			,       help='''Hash contents of a file'''       )
   UpperCAmelCase_							:      List[Any]						=   parser.parse_args()
   UpperCAmelCase_							:      Optional[Any]						=   args.input_string
   # In any case hash input should be a bytestring
   if args.input_file:
      with open(args.input_file			,       '''rb'''       ) as f:
         UpperCAmelCase_							:      List[str]						=   f.read()
   else:
      UpperCAmelCase_							:      Tuple						=   bytes(__lowercase			,       '''utf-8'''       )
   print(SHAaHash(__lowercase       ).final_hash()       )


if __name__ == "__main__":
       main()
       import doctest

       doctest.testmod()