
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       a		(   __UpperCAmelCase      ,	unittest.TestCase					):
							lowercase_		:						Dict   							=  LEDTokenizer
							lowercase_		:						List[Any]   							=  LEDTokenizerFast
							lowercase_		:						str   							=  True







							def       UpperCAmelCase__					(						self  :  Tuple ):
								"""simple docstring"""







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

								__lowerCAmelCase         =							os.path.join(self.tmpdirname      ,				VOCAB_FILES_NAMES["vocab_file"] )
								__lowerCAmelCase         =							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(snake_case__ ) + "\n" )
								with open(self.merges_file      ,				"w"      ,				encoding="utf-8" ) as fp:
									fp.write("\n".join(snake_case__ ) )







							def       UpperCAmelCase__					(						self  :  Dict      ,				**snake_case__  :  Optional[int] ):
								"""simple docstring"""







								kwargs.update(self.special_tokens_map )
								return self.tokenizer_class.from_pretrained(self.tmpdirname      ,				**snake_case__ )







							def       UpperCAmelCase__					(						self  :  Dict      ,				**snake_case__  :  List[str] ):
								"""simple docstring"""







								kwargs.update(self.special_tokens_map )
								return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      ,				**snake_case__ )







							def       UpperCAmelCase__					(						self  :  Optional[int]      ,				snake_case__  :  Tuple ):
								"""simple docstring"""







								return "lower newer", "lower newer"







							@cached_property
							def       UpperCAmelCase__					(						self  :  List[str] ):
								"""simple docstring"""







								return LEDTokenizer.from_pretrained("allenai/led-base-16384" )







							@cached_property
							def       UpperCAmelCase__					(						self  :  Union[str, Any] ):
								"""simple docstring"""







								return LEDTokenizerFast.from_pretrained("allenai/led-base-16384" )







							@require_torch
							def       UpperCAmelCase__					(						self  :  int ):
								"""simple docstring"""







								__lowerCAmelCase         =							["A long paragraph for summarization.", "Another paragraph for summarization."]
								__lowerCAmelCase         =							[0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

								for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									__lowerCAmelCase         =							tokenizer(snake_case__      ,				max_length=len(snake_case__ )      ,				padding=snake_case__      ,				return_tensors="pt" )
									self.assertIsInstance(snake_case__      ,				snake_case__ )

									self.assertEqual((2, 9)      ,				batch.input_ids.shape )
									self.assertEqual((2, 9)      ,				batch.attention_mask.shape )
									__lowerCAmelCase         =							batch.input_ids.tolist()[0]
									self.assertListEqual(snake_case__      ,				snake_case__ )







							@require_torch
							def       UpperCAmelCase__					(						self  :  str ):
								"""simple docstring"""







								__lowerCAmelCase         =							["A long paragraph for summarization.", "Another paragraph for summarization."]
								for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									__lowerCAmelCase         =							tokenizer(snake_case__      ,				padding=snake_case__      ,				return_tensors="pt" )
									self.assertIn("input_ids"      ,				snake_case__ )
									self.assertIn("attention_mask"      ,				snake_case__ )
									self.assertNotIn("labels"      ,				snake_case__ )
									self.assertNotIn("decoder_attention_mask"      ,				snake_case__ )







							@require_torch
							def       UpperCAmelCase__					(						self  :  List[str] ):
								"""simple docstring"""







								__lowerCAmelCase         =							[
								    "Summary of the text.",
								    "Another summary.",
								]
								for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									__lowerCAmelCase         =							tokenizer(text_target=snake_case__      ,				max_length=32      ,				padding="max_length"      ,				return_tensors="pt" )
									self.assertEqual(32      ,				targets["input_ids"].shape[1] )







							@require_torch
							def       UpperCAmelCase__					(						self  :  Optional[Any] ):
								"""simple docstring"""







								for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									__lowerCAmelCase         =							tokenizer(
									    ["I am a small frog" * 1_024, "I am a small frog"]      ,				padding=snake_case__      ,				truncation=snake_case__      ,				return_tensors="pt" )
									self.assertIsInstance(snake_case__      ,				snake_case__ )
									self.assertEqual(batch.input_ids.shape      ,				(2, 5_122) )







							@require_torch
							def       UpperCAmelCase__					(						self  :  str ):
								"""simple docstring"""







								__lowerCAmelCase         =							["A long paragraph for summarization."]
								__lowerCAmelCase         =							[
								    "Summary of the text.",
								]
								for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									__lowerCAmelCase         =							tokenizer(snake_case__      ,				return_tensors="pt" )
									__lowerCAmelCase         =							tokenizer(text_target=snake_case__      ,				return_tensors="pt" )
									__lowerCAmelCase         =							inputs["input_ids"]
									__lowerCAmelCase         =							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       UpperCAmelCase__					(						self  :  Any ):
								"""simple docstring"""







								for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
									__lowerCAmelCase         =							["Summary of the text.", "Another summary."]
									__lowerCAmelCase         =							[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

									__lowerCAmelCase         =							tokenizer(snake_case__      ,				padding=snake_case__ )
									__lowerCAmelCase         =							[[0] * len(snake_case__ ) for x in encoded_output["input_ids"]]
									__lowerCAmelCase         =							tokenizer.pad(snake_case__ )
									self.assertSequenceEqual(outputs["global_attention_mask"]      ,				snake_case__ )







							def       UpperCAmelCase__					(						self  :  List[str] ):
								"""simple docstring"""







								pass







							def       UpperCAmelCase__					(						self  :  int ):
								"""simple docstring"""







								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})" ):
										__lowerCAmelCase         =							self.rust_tokenizer_class.from_pretrained(snake_case__      ,				**snake_case__ )
										__lowerCAmelCase         =							self.tokenizer_class.from_pretrained(snake_case__      ,				**snake_case__ )
										__lowerCAmelCase         =							"A, <mask> AllenNLP sentence."
										__lowerCAmelCase         =							tokenizer_r.encode_plus(snake_case__      ,				add_special_tokens=snake_case__      ,				return_token_type_ids=snake_case__ )
										__lowerCAmelCase         =							tokenizer_p.encode_plus(snake_case__      ,				add_special_tokens=snake_case__      ,				return_token_type_ids=snake_case__ )
										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"] )      ,				)

										__lowerCAmelCase         =							tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"] )
										__lowerCAmelCase         =							tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"] )
										self.assertSequenceEqual(tokens_p["input_ids"]      ,				[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2] )
										self.assertSequenceEqual(tokens_r["input_ids"]      ,				[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2] )

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








import math
import sys






def 		_UpperCAmelCase   (	UpperCamelCase:     str  ):






	"""simple docstring"""


	__lowerCAmelCase         =							""
	try:
		with open(UpperCamelCase			,							"rb"  ) as binary_file:
			__lowerCAmelCase         =							binary_file.read()
		for dat in data:
			__lowerCAmelCase         =							F"{dat:08b}"
			result += curr_byte
		return result
	except OSError:
		print("File not accessible"  )
		sys.exit()






def 		_UpperCAmelCase   (	UpperCamelCase:     str  ):






	"""simple docstring"""


	__lowerCAmelCase         =							{"0": "0", "1": "1"}
	__lowerCAmelCase   ,						__lowerCAmelCase         =							"", ""
	__lowerCAmelCase         =							len(UpperCamelCase  )

	for i in range(len(UpperCamelCase  )  ):
		curr_string += data_bits[i]
		if curr_string not in lexicon:
			continue

		__lowerCAmelCase         =							lexicon[curr_string]
		result += last_match_id
		__lowerCAmelCase         =							last_match_id + "0"

		if math.loga(UpperCamelCase  ).is_integer():
			__lowerCAmelCase         =							{}
			for curr_key in list(UpperCamelCase  ):
				__lowerCAmelCase         =							lexicon.pop(UpperCamelCase  )
			__lowerCAmelCase         =							new_lex

		__lowerCAmelCase         =							last_match_id + "1"
		index += 1
		__lowerCAmelCase         =							""
	return result






def 		_UpperCAmelCase   (	UpperCamelCase:     str			,							UpperCamelCase:     str  ):






	"""simple docstring"""


	__lowerCAmelCase         =							8
	try:
		with open(UpperCamelCase			,							"wb"  ) as opened_file:
			__lowerCAmelCase         =							[
			    to_write[i : i + byte_length]
			    for i in range(0			,							len(UpperCamelCase  )			,							UpperCamelCase  )
			]

			if len(result_byte_array[-1]  ) % byte_length == 0:
				result_byte_array.append("10000000"  )
			else:
				result_byte_array[-1] += "1" + "0" * (
				    byte_length - len(result_byte_array[-1]  ) - 1
				)

			for elem in result_byte_array[:-1]:
				opened_file.write(int(UpperCamelCase			,							2  ).to_bytes(1			,							byteorder="big"  )  )
	except OSError:
		print("File not accessible"  )
		sys.exit()






def 		_UpperCAmelCase   (	UpperCamelCase:     str  ):






	"""simple docstring"""


	__lowerCAmelCase         =							0
	for letter in data_bits:
		if letter == "1":
			break
		counter += 1

	__lowerCAmelCase         =							data_bits[counter:]
	__lowerCAmelCase         =							data_bits[counter + 1 :]
	return data_bits






def 		_UpperCAmelCase   (	UpperCamelCase:     str			,							UpperCamelCase:     str  ):






	"""simple docstring"""


	__lowerCAmelCase         =							read_file_binary(UpperCamelCase  )
	__lowerCAmelCase         =							remove_prefix(UpperCamelCase  )
	__lowerCAmelCase         =							decompress_data(UpperCamelCase  )
	write_file_binary(UpperCamelCase			,							UpperCamelCase  )


if __name__ == "__main__":
					compress(sys.argv[1], sys.argv[2])






