
'''simple docstring'''



import argparse
import struct
import unittest




class     UpperCAmelCase_	:






						'''simple docstring'''






						def __init__(   self       ,  _lowercase ):

												"""simple docstring"""



												_lowerCAmelCase    		=					data

												# Initialize hash values
												_lowerCAmelCase    		=					[
												    0x6_A_0_9_E_6_6_7,
												    0xB_B_6_7_A_E_8_5,
												    0x3_C_6_E_F_3_7_2,
												    0xA_5_4_F_F_5_3_A,
												    0x5_1_0_E_5_2_7_F,
												    0x9_B_0_5_6_8_8_C,
												    0x1_F_8_3_D_9_A_B,
												    0x5_B_E_0_C_D_1_9,
												]

												# Initialize round constants
												_lowerCAmelCase    		=					[
												    0x4_2_8_A_2_F_9_8,
												    0x7_1_3_7_4_4_9_1,
												    0xB_5_C_0_F_B_C_F,
												    0xE_9_B_5_D_B_A_5,
												    0x3_9_5_6_C_2_5_B,
												    0x5_9_F_1_1_1_F_1,
												    0x9_2_3_F_8_2_A_4,
												    0xA_B_1_C_5_E_D_5,
												    0xD_8_0_7_A_A_9_8,
												    0x1_2_8_3_5_B_0_1,
												    0x2_4_3_1_8_5_B_E,
												    0x5_5_0_C_7_D_C_3,
												    0x7_2_B_E_5_D_7_4,
												    0x8_0_D_E_B_1_F_E,
												    0x9_B_D_C_0_6_A_7,
												    0xC_1_9_B_F_1_7_4,
												    0xE_4_9_B_6_9_C_1,
												    0xE_F_B_E_4_7_8_6,
												    0x0_F_C_1_9_D_C_6,
												    0x2_4_0_C_A_1_C_C,
												    0x2_D_E_9_2_C_6_F,
												    0x4_A_7_4_8_4_A_A,
												    0x5_C_B_0_A_9_D_C,
												    0x7_6_F_9_8_8_D_A,
												    0x9_8_3_E_5_1_5_2,
												    0xA_8_3_1_C_6_6_D,
												    0xB_0_0_3_2_7_C_8,
												    0xB_F_5_9_7_F_C_7,
												    0xC_6_E_0_0_B_F_3,
												    0xD_5_A_7_9_1_4_7,
												    0x0_6_C_A_6_3_5_1,
												    0x1_4_2_9_2_9_6_7,
												    0x2_7_B_7_0_A_8_5,
												    0x2_E_1_B_2_1_3_8,
												    0x4_D_2_C_6_D_F_C,
												    0x5_3_3_8_0_D_1_3,
												    0x6_5_0_A_7_3_5_4,
												    0x7_6_6_A_0_A_B_B,
												    0x8_1_C_2_C_9_2_E,
												    0x9_2_7_2_2_C_8_5,
												    0xA_2_B_F_E_8_A_1,
												    0xA_8_1_A_6_6_4_B,
												    0xC_2_4_B_8_B_7_0,
												    0xC_7_6_C_5_1_A_3,
												    0xD_1_9_2_E_8_1_9,
												    0xD_6_9_9_0_6_2_4,
												    0xF_4_0_E_3_5_8_5,
												    0x1_0_6_A_A_0_7_0,
												    0x1_9_A_4_C_1_1_6,
												    0x1_E_3_7_6_C_0_8,
												    0x2_7_4_8_7_7_4_C,
												    0x3_4_B_0_B_C_B_5,
												    0x3_9_1_C_0_C_B_3,
												    0x4_E_D_8_A_A_4_A,
												    0x5_B_9_C_C_A_4_F,
												    0x6_8_2_E_6_F_F_3,
												    0x7_4_8_F_8_2_E_E,
												    0x7_8_A_5_6_3_6_F,
												    0x8_4_C_8_7_8_1_4,
												    0x8_C_C_7_0_2_0_8,
												    0x9_0_B_E_F_F_F_A,
												    0xA_4_5_0_6_C_E_B,
												    0xB_E_F_9_A_3_F_7,
												    0xC_6_7_1_7_8_F_2,
												]

												_lowerCAmelCase    		=					self.preprocessing(self.data )
												self.final_hash()




						@staticmethod
						def    _lowercase      (   _lowercase ):

												"""simple docstring"""



												_lowerCAmelCase    		=					B"""\x80""" + (B"""\x00""" * (63 - (len(_lowercase ) + 8) % 64))
												_lowerCAmelCase    		=					struct.pack(""">Q"""       ,  (len(_lowercase ) * 8) )
												return data + padding + big_endian_integer




						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					[
												    self.preprocessed_data[x : x + 64]
												    for x in range(0       ,  len(self.preprocessed_data )       ,  64 )
												]

												for block in self.blocks:
																		# Convert the given block into a list of 4 byte integers
																		_lowerCAmelCase    		=					list(struct.unpack(""">16L"""       ,  _lowercase ) )
																		# add 48 0-ed integers
																		words += [0] * 48

																		_lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase    		=					self.hashes

																		for index in range(0       ,  64 ):
																								if index > 15:
																														# modify the zero-ed indexes at the end of the array
																														_lowerCAmelCase    		=					(
																														    self.ror(words[index - 15]       ,  7 )
																														    ^ self.ror(words[index - 15]       ,  18 )
																														    ^ (words[index - 15] >> 3)
																														)
																														_lowerCAmelCase    		=					(
																														    self.ror(words[index - 2]       ,  17 )
																														    ^ self.ror(words[index - 2]       ,  19 )
																														    ^ (words[index - 2] >> 10)
																														)

																														_lowerCAmelCase    		=					(
																														    words[index - 16] + sa + words[index - 7] + sa
																														) % 0x1_0_0_0_0_0_0_0_0

																								# Compression
																								_lowerCAmelCase    		=					self.ror(_lowercase       ,  6 ) ^ self.ror(_lowercase       ,  11 ) ^ self.ror(_lowercase       ,  25 )
																								_lowerCAmelCase    		=					(e & f) ^ ((~e & 0xF_F_F_F_F_F_F_F) & g)
																								_lowerCAmelCase    		=					(
																								    h + sa + ch + self.round_constants[index] + words[index]
																								) % 0x1_0_0_0_0_0_0_0_0
																								_lowerCAmelCase    		=					self.ror(_lowercase       ,  2 ) ^ self.ror(_lowercase       ,  13 ) ^ self.ror(_lowercase       ,  22 )
																								_lowerCAmelCase    		=					(a & b) ^ (a & c) ^ (b & c)
																								_lowerCAmelCase    		=					(sa + maj) % 0x1_0_0_0_0_0_0_0_0

																								_lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase		,       _lowerCAmelCase    		=					(
																								    g,
																								    f,
																								    e,
																								    ((d + tempa) % 0x1_0_0_0_0_0_0_0_0),
																								    c,
																								    b,
																								    a,
																								    ((tempa + tempa) % 0x1_0_0_0_0_0_0_0_0),
																								)

																		_lowerCAmelCase    		=					[a, b, c, d, e, f, g, h]

																		# Modify final values
																		_lowerCAmelCase    		=					[
																		    ((element + mutated_hash_values[index]) % 0x1_0_0_0_0_0_0_0_0)
																		    for index, element in enumerate(self.hashes )
																		]

												_lowerCAmelCase    		=					"""""".join([hex(_lowercase )[2:].zfill(8 ) for value in self.hashes] )




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase ):

												"""simple docstring"""



												return 0xF_F_F_F_F_F_F_F & (value << (32 - rotations)) | (value >> rotations)






class     UpperCAmelCase_	(						unittest.TestCase					):






						'''simple docstring'''






						def    _lowercase      (   self ):

												"""simple docstring"""



												import hashlib

												_lowerCAmelCase    		=					bytes("""Test String"""       ,  """utf-8""" )
												self.assertEqual(SHAaaa(_lowercase ).hash       ,  hashlib.shaaaa(_lowercase ).hexdigest() )






def A ():
						import doctest

						doctest.testmod()

						_lowerCAmelCase    		=					argparse.ArgumentParser()
						parser.add_argument(
						    """-s"""					,      """--string"""					,      dest="""input_string"""					,      default="""Hello World!! Welcome to Cryptography"""					,      help="""Hash the string"""					,      )
						parser.add_argument(
						    """-f"""					,      """--file"""					,      dest="""input_file"""					,      help="""Hash contents of a file"""						)

						_lowerCAmelCase    		=					parser.parse_args()

						_lowerCAmelCase    		=					args.input_string

						# hash input should be a bytestring
						if args.input_file:
												with open(args.input_file					,      """rb"""						) as f:
																		_lowerCAmelCase    		=					f.read()
						else:
												_lowerCAmelCase    		=					bytes(__lowerCamelCase					,      """utf-8"""						)

						print(SHAaaa(__lowerCamelCase						).hash						)


if __name__ == "__main__":
						main()








"""simple docstring"""
import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class   SCREAMING_SNAKE_CASE	(					_SCREAMING_SNAKE_CASE							,							unittest.TestCase    ):





	"""simple docstring"""




	_A							:					str 			=					LEDTokenizer
	_A							:					List[Any] 			=					LEDTokenizerFast
	_A							:					Dict 			=					True





	def  lowerCamelCase(self				):
		super().setUp()
		A_		:    Dict						     = [
		    """l""",
		    """o""",
		    """w""",
		    """e""",
		    """r""",
		    """s""",
		    """t""",
		    """i""",
		    """d""",
		    """n""",
		    """\u0120""",
		    """\u0120l""",
		    """\u0120n""",
		    """\u0120lo""",
		    """\u0120low""",
		    """er""",
		    """\u0120lowest""",
		    """\u0120newer""",
		    """\u0120wider""",
		    """<unk>""",
		]
		A_		:    Any						     = dict(zip(lowerCAmelCase_  ,  range(len(lowerCAmelCase_				)				)				)				)
		A_		:    List[Any]						     = ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
		A_		:    List[str]						     = {"""unk_token""": """<unk>"""}

		A_		:    List[Any]						     = os.path.join(self.tmpdirname  ,  VOCAB_FILES_NAMES["""vocab_file"""]				)
		A_		:    Tuple						     = os.path.join(self.tmpdirname  ,  VOCAB_FILES_NAMES["""merges_file"""]				)
		with open(self.vocab_file  ,  """w"""  ,  encoding="""utf-8"""				) as fp:
			fp.write(json.dumps(lowerCAmelCase_				) + """\n"""				)
		with open(self.merges_file  ,  """w"""  ,  encoding="""utf-8"""				) as fp:
			fp.write("""\n""".join(lowerCAmelCase_				)				)





	def  lowerCamelCase(self  ,  **lowerCAmelCase_				):
		kwargs.update(self.special_tokens_map				)
		return self.tokenizer_class.from_pretrained(self.tmpdirname  ,  **lowerCAmelCase_				)





	def  lowerCamelCase(self  ,  **lowerCAmelCase_				):
		kwargs.update(self.special_tokens_map				)
		return self.rust_tokenizer_class.from_pretrained(self.tmpdirname  ,  **lowerCAmelCase_				)





	def  lowerCamelCase(self  ,  lowerCAmelCase_				):
		return "lower newer", "lower newer"





	@cached_property
	def  lowerCamelCase(self				):
		return LEDTokenizer.from_pretrained("""allenai/led-base-16384"""				)





	@cached_property
	def  lowerCamelCase(self				):
		return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384"""				)





	@require_torch
	def  lowerCamelCase(self				):
		A_		:    Optional[int]						     = ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
		A_		:    Any						     = [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

		for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
			A_		:    Optional[int]						     = tokenizer(lowerCAmelCase_  ,  max_length=len(lowerCAmelCase_				)  ,  padding=lowerCAmelCase_  ,  return_tensors="""pt"""				)
			self.assertIsInstance(lowerCAmelCase_  ,  lowerCAmelCase_				)

			self.assertEqual((2, 9)  ,  batch.input_ids.shape				)
			self.assertEqual((2, 9)  ,  batch.attention_mask.shape				)
			A_		:    int						     = batch.input_ids.tolist()[0]
			self.assertListEqual(lowerCAmelCase_  ,  lowerCAmelCase_				)





	@require_torch
	def  lowerCamelCase(self				):
		A_		:    Union[str, Any]						     = ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
		for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
			A_		:    Tuple						     = tokenizer(lowerCAmelCase_  ,  padding=lowerCAmelCase_  ,  return_tensors="""pt"""				)
			self.assertIn("""input_ids"""  ,  lowerCAmelCase_				)
			self.assertIn("""attention_mask"""  ,  lowerCAmelCase_				)
			self.assertNotIn("""labels"""  ,  lowerCAmelCase_				)
			self.assertNotIn("""decoder_attention_mask"""  ,  lowerCAmelCase_				)





	@require_torch
	def  lowerCamelCase(self				):
		A_		:    Tuple						     = [
		    """Summary of the text.""",
		    """Another summary.""",
		]
		for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
			A_		:    Optional[int]						     = tokenizer(text_target=lowerCAmelCase_  ,  max_length=32  ,  padding="""max_length"""  ,  return_tensors="""pt"""				)
			self.assertEqual(32  ,  targets["""input_ids"""].shape[1]				)





	@require_torch
	def  lowerCamelCase(self				):
		for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
			A_		:    Optional[Any]						     = tokenizer(
			    ["""I am a small frog""" * 1024, """I am a small frog"""]  ,  padding=lowerCAmelCase_  ,  truncation=lowerCAmelCase_  ,  return_tensors="""pt"""				)
			self.assertIsInstance(lowerCAmelCase_  ,  lowerCAmelCase_				)
			self.assertEqual(batch.input_ids.shape  ,  (2, 5122)				)





	@require_torch
	def  lowerCamelCase(self				):
		A_		:    Dict						     = ["""A long paragraph for summarization."""]
		A_		:    Any						     = [
		    """Summary of the text.""",
		]
		for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
			A_		:    int						     = tokenizer(lowerCAmelCase_  ,  return_tensors="""pt"""				)
			A_		:    Optional[int]						     = tokenizer(text_target=lowerCAmelCase_  ,  return_tensors="""pt"""				)
			A_		:    str						     = inputs["""input_ids"""]
			A_		:    Tuple						     = targets["""input_ids"""]
			self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()				)
			self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()				)
			self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()				)
			self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()				)





	@require_torch
	def  lowerCamelCase(self				):
		for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
			A_		:    str						     = ["""Summary of the text.""", """Another summary."""]
			A_		:    Dict						     = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

			A_		:    Optional[Any]						     = tokenizer(lowerCAmelCase_  ,  padding=lowerCAmelCase_				)
			A_		:    Any						     = [[0] * len(lowerCAmelCase_				) for x in encoded_output["""input_ids"""]]
			A_		:    Tuple						     = tokenizer.pad(lowerCAmelCase_				)
			self.assertSequenceEqual(outputs["""global_attention_mask"""]  ,  lowerCAmelCase_				)





	def  lowerCamelCase(self				):
		pass





	def  lowerCamelCase(self				):
		for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
			with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
				A_		:    Any						     = self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_  ,  **lowerCAmelCase_				)
				A_		:    Optional[Any]						     = self.tokenizer_class.from_pretrained(lowerCAmelCase_  ,  **lowerCAmelCase_				)
				A_		:    Optional[Any]						     = """A, <mask> AllenNLP sentence."""
				A_		:    List[Any]						     = tokenizer_r.encode_plus(lowerCAmelCase_  ,  add_special_tokens=lowerCAmelCase_  ,  return_token_type_ids=lowerCAmelCase_				)
				A_		:    Any						     = tokenizer_p.encode_plus(lowerCAmelCase_  ,  add_special_tokens=lowerCAmelCase_  ,  return_token_type_ids=lowerCAmelCase_				)
				self.assertEqual(sum(tokens_r["""token_type_ids"""]				)  ,  sum(tokens_p["""token_type_ids"""]				)				)
				self.assertEqual(
				    sum(tokens_r["""attention_mask"""]				) / len(tokens_r["""attention_mask"""]				)  ,  sum(tokens_p["""attention_mask"""]				) / len(tokens_p["""attention_mask"""]				)  ,  )

				A_		:    List[Any]						     = tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]				)
				A_		:    Union[str, Any]						     = tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]				)
				self.assertSequenceEqual(tokens_p["""input_ids"""]  ,  [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]				)
				self.assertSequenceEqual(tokens_r["""input_ids"""]  ,  [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]				)

				self.assertSequenceEqual(
				    lowerCAmelCase_  ,  ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)
				self.assertSequenceEqual(
				    lowerCAmelCase_  ,  ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)

