





"""simple docstring"""





import random
import unittest

import numpy as np

import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax


if is_flax_available():
  import os

  import jax.numpy as jnp
  from jax import jit

  from transformers import AutoTokenizer, FlaxAutoModelForCausalLM
  from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model

  __A											=		"""0.12"""  # assumed parallelism: 8


if is_torch_available():
  import torch
def  __A   (_SCREAMING_SNAKE_CASE     ,   _SCREAMING_SNAKE_CASE     ,   _SCREAMING_SNAKE_CASE=None			)					->Any:





  """simple docstring"""


  if rng is None:
    lowerCAmelCase__			:Tuple											=							random.Random()

  lowerCAmelCase__			:Optional[int]											=							1
  for dim in shape:
    total_dims *= dim

  lowerCAmelCase__			:Union[str, Any]											=							[]
  for _ in range(SCREAMING_SNAKE_CASE_			):
    values.append(rng.randint(0     ,   vocab_size - 1			)			)

  lowerCAmelCase__			:str											=							np.array(SCREAMING_SNAKE_CASE_     ,   dtype=jnp.intaa			).reshape(SCREAMING_SNAKE_CASE_			)

  return output
def  __A   (_SCREAMING_SNAKE_CASE     ,   _SCREAMING_SNAKE_CASE=None			)					->Union[str, Any]:





  """simple docstring"""


  lowerCAmelCase__			:Dict											=							ids_tensor(SCREAMING_SNAKE_CASE_     ,   vocab_size=2     ,   rng=SCREAMING_SNAKE_CASE_			)
  # make sure that at least one token is attended to for each batch
  lowerCAmelCase__			:Dict											=							1
  return attn_mask






@require_flax
class 					_lowerCAmelCase   :
       """simple docstring"""




       __magic_name__     :Dict		  =					None
       __magic_name__     :Optional[int]		  =					()






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:int											=							self.model_tester.prepare_config_and_inputs_for_common()

         # cut to half length & take max batch_size 3
         lowerCAmelCase__			:Tuple											=							2
         lowerCAmelCase__			:List[str]											=							inputs['input_ids'].shape[-1] // 2
         lowerCAmelCase__			:Tuple											=							inputs['input_ids'][:max_batch_size, :sequence_length]

         lowerCAmelCase__			:Optional[Any]											=							jnp.ones_like(__UpperCAmelCase      )
         lowerCAmelCase__			:List[str]											=							attention_mask[:max_batch_size, :sequence_length]

         # generate max 5 tokens
         lowerCAmelCase__			:Any											=							input_ids.shape[-1] + 5
         if config.eos_token_id is not None and config.pad_token_id is None:
           # hack to allow generate for models such as GPT2 as is done in `generate()`
           lowerCAmelCase__			:List[str]											=							config.eos_token_id
         return config, input_ids, attention_mask, max_length






       @is_pt_flax_cross_test
       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:int											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:Optional[int]											=							False
         lowerCAmelCase__			:Union[str, Any]											=							max_length
         lowerCAmelCase__			:Tuple											=							0

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:Tuple											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:Union[str, Any]											=							model_class.__name__[4:]  # Skip the "Flax" at the beginning
           lowerCAmelCase__			:List[Any]											=							getattr(__UpperCAmelCase    , __UpperCAmelCase      )
           lowerCAmelCase__			:List[Any]											=							pt_model_class(__UpperCAmelCase      ).eval()
           lowerCAmelCase__			:Tuple											=							load_flax_weights_in_pytorch_model(__UpperCAmelCase    , flax_model.params      )

           lowerCAmelCase__			:Dict											=							flax_model.generate(__UpperCAmelCase      ).sequences
           lowerCAmelCase__			:Dict											=							pt_model.generate(torch.tensor(__UpperCAmelCase    , dtype=torch.long      )      )

           if flax_generation_outputs.shape[-1] > pt_generation_outputs.shape[-1]:
             lowerCAmelCase__			:Optional[int]											=							flax_generation_outputs[:, : pt_generation_outputs.shape[-1]]

           self.assertListEqual(pt_generation_outputs.numpy().tolist()    , flax_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Tuple											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:Any											=							False
         lowerCAmelCase__			:int											=							max_length

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:Union[str, Any]											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:Any											=							model.generate(__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:List[Any]											=							jit(model.generate      )
           lowerCAmelCase__			:Any											=							jit_generate(__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[Any]											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:List[str]											=							True
         lowerCAmelCase__			:str											=							max_length

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:str											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:Union[str, Any]											=							model.generate(__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:int											=							jit(model.generate      )
           lowerCAmelCase__			:Dict											=							jit_generate(__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[Any]											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:List[Any]											=							False
         lowerCAmelCase__			:List[str]											=							max_length
         lowerCAmelCase__			:str											=							2

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:Tuple											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:int											=							model.generate(__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:str											=							jit(model.generate      )
           lowerCAmelCase__			:Tuple											=							jit_generate(__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Any											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:Union[str, Any]											=							False
         lowerCAmelCase__			:Optional[Any]											=							max_length
         lowerCAmelCase__			:List[str]											=							2
         lowerCAmelCase__			:List[Any]											=							2

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:Union[str, Any]											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:Any											=							model.generate(__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[0]    , input_ids.shape[0] * config.num_return_sequences      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[Any]											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:List[Any]											=							True
         lowerCAmelCase__			:Optional[Any]											=							max_length
         lowerCAmelCase__			:int											=							0.8
         lowerCAmelCase__			:Optional[Any]											=							1_0
         lowerCAmelCase__			:Optional[Any]											=							0.3
         lowerCAmelCase__			:Optional[Any]											=							1
         lowerCAmelCase__			:Union[str, Any]											=							8
         lowerCAmelCase__			:Any											=							9

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:List[str]											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:int											=							model.generate(__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:List[Any]											=							jit(model.generate      )
           lowerCAmelCase__			:str											=							jit_generate(__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:str											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:Dict											=							max_length
         lowerCAmelCase__			:int											=							1
         lowerCAmelCase__			:int											=							8
         lowerCAmelCase__			:List[str]											=							9

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:Optional[Any]											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:Tuple											=							model.generate(__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:Optional[Any]											=							jit(model.generate      )
           lowerCAmelCase__			:Tuple											=							jit_generate(__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[Any]											=							self._get_input_ids_and_config()
         lowerCAmelCase__			:Union[str, Any]											=							max_length
         lowerCAmelCase__			:int											=							2
         lowerCAmelCase__			:Tuple											=							1
         lowerCAmelCase__			:Optional[int]											=							8
         lowerCAmelCase__			:Optional[int]											=							9

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:str											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:int											=							model.generate(__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:List[Any]											=							jit(model.generate      )
           lowerCAmelCase__			:Optional[Any]											=							jit_generate(__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:str											=							self._get_input_ids_and_config()

         # pad attention mask on the left
         lowerCAmelCase__			:str											=							attention_mask.at[(0, 0)].set(0      )

         lowerCAmelCase__			:str											=							False
         lowerCAmelCase__			:Union[str, Any]											=							max_length

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:int											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:Dict											=							model.generate(__UpperCAmelCase    , attention_mask=__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:Optional[int]											=							jit(model.generate      )
           lowerCAmelCase__			:List[Any]											=							jit_generate(__UpperCAmelCase    , attention_mask=__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:List[Any]											=							self._get_input_ids_and_config()

         # pad attention mask on the left
         lowerCAmelCase__			:List[Any]											=							attention_mask.at[(0, 0)].set(0      )

         lowerCAmelCase__			:str											=							True
         lowerCAmelCase__			:Tuple											=							max_length

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:Tuple											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:List[Any]											=							model.generate(__UpperCAmelCase    , attention_mask=__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:int											=							jit(model.generate      )
           lowerCAmelCase__			:str											=							jit_generate(__UpperCAmelCase    , attention_mask=__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Union[str, Any]											=							self._get_input_ids_and_config()

         # pad attention mask on the left
         lowerCAmelCase__			:Union[str, Any]											=							attention_mask.at[(0, 0)].set(0      )

         lowerCAmelCase__			:str											=							2
         lowerCAmelCase__			:List[str]											=							max_length

         for model_class in self.all_generative_model_classes:
           lowerCAmelCase__			:Tuple											=							model_class(__UpperCAmelCase      )

           lowerCAmelCase__			:Optional[Any]											=							model.generate(__UpperCAmelCase    , attention_mask=__UpperCAmelCase      ).sequences
           self.assertEqual(generation_outputs.shape[-1]    , __UpperCAmelCase      )

           lowerCAmelCase__			:int											=							jit(model.generate      )
           lowerCAmelCase__			:List[Any]											=							jit_generate(__UpperCAmelCase    , attention_mask=__UpperCAmelCase      ).sequences

           self.assertListEqual(generation_outputs.tolist()    , jit_generation_outputs.tolist()      )






@require_flax
class 					_lowerCAmelCase   (     unittest.TestCase       ):
       """simple docstring"""




       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:List[Any]											=							AutoTokenizer.from_pretrained('hf-internal-testing/tiny-bert'      )
         lowerCAmelCase__			:Optional[int]											=							FlaxAutoModelForCausalLM.from_pretrained('hf-internal-testing/tiny-bert-flax-only'      )

         lowerCAmelCase__			:List[Any]											=							'Hello world'
         lowerCAmelCase__			:Any											=							tokenizer(__UpperCAmelCase    , return_tensors='np'      ).input_ids

         # typos are quickly detected (the correct argument is `do_sample`)
         with self.assertRaisesRegex(__UpperCAmelCase    , 'do_samples'      ):
           model.generate(__UpperCAmelCase    , do_samples=__UpperCAmelCase      )

         # arbitrary arguments that will not be used anywhere are also not accepted
         with self.assertRaisesRegex(__UpperCAmelCase    , 'foo'      ):
           lowerCAmelCase__			:Optional[int]											=							{'foo': 'bar'}
           model.generate(__UpperCAmelCase    , **__UpperCAmelCase      )


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







class      A__							:






				def __init__(						self					:      Dict    ,     a					:      str   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Optional[int]         =		data
							lowerCAmelCase__      :      List[Any]         =		[0X67_452_301, 0Xef_cda_b89, 0X98_bad_cfe, 0X10_325_476, 0Xc3_d2e_1f0]






				@staticmethod
				def 							_lowerCamelCase		(						a					:      int    ,     a					:      List[str]   ):






							'''simple docstring'''







							return ((n << b) | (n >> (32 - b))) & 0Xff_fff_fff






				def 							_lowerCamelCase		(						self					:      Optional[int]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Any         =		b'\x80' + b'\x00' * (63 - (len(self.data   ) + 8) % 64)
							lowerCAmelCase__      :      List[str]         =		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					:      Tuple    ,     a					:      List[Any]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[Any]         =		list(struct.unpack('>16L'    ,     a   )   ) + [0] * 64
							for i in range(16    ,     80   ):
										lowerCAmelCase__      :      int         =		self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16])    ,     1   )
							return w






				def 							_lowerCamelCase		(						self					:      Dict   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Optional[Any]         =		self.padding()
							lowerCAmelCase__      :      List[Any]         =		self.split_blocks()
							for block in self.blocks:
										lowerCAmelCase__      :      str         =		self.expand_block(a   )
										lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      :      str         =		self.h
										for i in range(0    ,     80   ):
													if 0 <= i < 20:
																lowerCAmelCase__      :      Tuple         =		(b & c) | ((~b) & d)
																lowerCAmelCase__      :      int         =		0X5a_827_999
													elif 20 <= i < 40:
																lowerCAmelCase__      :      List[str]         =		b ^ c ^ d
																lowerCAmelCase__      :      Any         =		0X6e_d9e_ba1
													elif 40 <= i < 60:
																lowerCAmelCase__      :      Tuple         =		(b & c) | (b & d) | (c & d)
																lowerCAmelCase__      :      Tuple         =		0X8f_1bb_cdc
													elif 60 <= i < 80:
																lowerCAmelCase__      :      List[Any]         =		b ^ c ^ d
																lowerCAmelCase__      :      int         =		0Xca_62c_1d6
													lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      :      Dict         =		(
													    self.rotate(a    ,     5   ) + f + e + k + expanded_block[i] & 0Xff_fff_fff,
													    a,
													    self.rotate(a    ,     30   ),
													    c,
													    d,
													)
										lowerCAmelCase__      :      Optional[Any]         =		(
										    self.h[0] + a & 0Xff_fff_fff,
										    self.h[1] + b & 0Xff_fff_fff,
										    self.h[2] + c & 0Xff_fff_fff,
										    self.h[3] + d & 0Xff_fff_fff,
										    self.h[4] + e & 0Xff_fff_fff,
										)
							return ("{:08x}" * 5).format(*self.h   )






def  lowerCAmelCase__			(  )				->		Tuple:
			lowerCAmelCase__      :      Optional[int]         =		b'Test String'
			assert SHAaHash(SCREAMING_SNAKE_CASE_     ).final_hash() == hashlib.shaa(SCREAMING_SNAKE_CASE_     ).hexdigest()  # noqa: S324
def  lowerCAmelCase__			(  )				->		Any:
			lowerCAmelCase__      :      str         =		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'     )
			lowerCAmelCase__      :      Dict         =		parser.parse_args()
			lowerCAmelCase__      :      Tuple         =		args.input_string
			# In any case hash input should be a bytestring
			if args.input_file:
						with open(args.input_file       ,							'rb'     ) as f:
									lowerCAmelCase__      :      List[Any]         =		f.read()
			else:
						lowerCAmelCase__      :      Tuple         =		bytes(SCREAMING_SNAKE_CASE_       ,							'utf-8'     )
			print(SHAaHash(SCREAMING_SNAKE_CASE_     ).final_hash()     )


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

					doctest.testmod()