





"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
		from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


_snake_case     :		List[Any]       						= get_tests_dir('fixtures/test_sentencepiece.model')

_snake_case     :		Dict       						= {'target_lang': 'fi', 'source_lang': 'en'}
_snake_case     :		List[str]       						= '>>zh<<'
_snake_case     :		List[Any]       						= 'Helsinki-NLP/'

if is_torch_available():
		_snake_case     :		int       						= 'pt'
elif is_tf_available():
		_snake_case     :		Tuple       						= 'tf'
else:
		_snake_case     :		str       						= 'jax'






@require_sentencepiece
class 					_UpperCAmelCase   (	lowercase_     ,							unittest.TestCase ):
					UpperCamelCase      =							MarianTokenizer
					UpperCamelCase      =							False
					UpperCamelCase      =							True


					def 	lowerCamelCase       (					self			:Any		):
												super().setUp()
												A		=  ["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
												A		=  dict(zip(__UpperCamelCase     ,       range(len(__UpperCamelCase		)		)		)		)
												A		=  Path(self.tmpdirname		)
												save_json(__UpperCamelCase     ,       save_dir / VOCAB_FILES_NAMES["vocab"]		)
												save_json(__UpperCamelCase     ,       save_dir / VOCAB_FILES_NAMES["tokenizer_config_file"]		)
												if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
																			copyfile(__UpperCamelCase     ,       save_dir / VOCAB_FILES_NAMES["source_spm"]		)
																			copyfile(__UpperCamelCase     ,       save_dir / VOCAB_FILES_NAMES["target_spm"]		)

												A		=  MarianTokenizer.from_pretrained(self.tmpdirname		)
												tokenizer.save_pretrained(self.tmpdirname		)


					def 	lowerCamelCase       (					self			:Tuple     ,       **__UpperCamelCase			:Any		):
												return MarianTokenizer.from_pretrained(self.tmpdirname     ,       **__UpperCamelCase		)


					def 	lowerCamelCase       (					self			:List[Any]     ,       __UpperCamelCase			:Optional[int]		):
												return (
												    "This is a test",
												    "This is a test",
												)


					def 	lowerCamelCase       (					self			:Optional[Any]		):
												A		=  "</s>"
												A		=  0

												self.assertEqual(self.get_tokenizer()._convert_token_to_id(__UpperCamelCase		)     ,       __UpperCamelCase		)
												self.assertEqual(self.get_tokenizer()._convert_id_to_token(__UpperCamelCase		)     ,       __UpperCamelCase		)


					def 	lowerCamelCase       (					self			:Any		):
												A		=  list(self.get_tokenizer().get_vocab().keys()		)

												self.assertEqual(vocab_keys[0]     ,       "</s>"		)
												self.assertEqual(vocab_keys[1]     ,       "<unk>"		)
												self.assertEqual(vocab_keys[-1]     ,       "<pad>"		)
												self.assertEqual(len(__UpperCamelCase		)     ,       9		)


					def 	lowerCamelCase       (					self			:Optional[int]		):
												self.assertEqual(self.get_tokenizer().vocab_size     ,       9		)


					def 	lowerCamelCase       (					self			:List[str]		):
												A		=  MarianTokenizer.from_pretrained(f"{ORG_NAME}opus-mt-en-de"		)
												A		=  en_de_tokenizer(["I am a small frog"]     ,       return_tensors=__UpperCamelCase		)
												self.assertIsInstance(__UpperCamelCase     ,       __UpperCamelCase		)
												A		=  [38, 1_21, 14, 6_97, 3_88_48, 0]
												self.assertListEqual(__UpperCamelCase     ,       batch.input_ids[0]		)

												A		=  tempfile.mkdtemp()
												en_de_tokenizer.save_pretrained(__UpperCamelCase		)
												A		=  [x.name for x in Path(__UpperCamelCase		).glob("*"		)]
												self.assertIn("source.spm"     ,       __UpperCamelCase		)
												MarianTokenizer.from_pretrained(__UpperCamelCase		)


					def 	lowerCamelCase       (					self			:Optional[Any]		):
												A		=  self.get_tokenizer()

												A		=  tok(
												    ["I am a small frog" * 10_00, "I am a small frog"]     ,       padding=__UpperCamelCase     ,       truncation=__UpperCamelCase     ,       return_tensors=__UpperCamelCase		)
												self.assertIsInstance(__UpperCamelCase     ,       __UpperCamelCase		)
												self.assertEqual(batch.input_ids.shape     ,       (2, 5_12)		)


					def 	lowerCamelCase       (					self			:Any		):
												A		=  self.get_tokenizer()
												A		=  tok(["I am a tiny frog", "I am a small frog"]     ,       padding=__UpperCamelCase     ,       return_tensors=__UpperCamelCase		)
												self.assertIsInstance(__UpperCamelCase     ,       __UpperCamelCase		)
												self.assertEqual(batch_smaller.input_ids.shape     ,       (2, 10)		)


					@slow
					def 	lowerCamelCase       (					self			:str		):
												# fmt: off
												A		=  {"input_ids": [[4_34_95, 4_62, 20, 4_21_64, 13_69, 52, 4_64, 1_32, 17_03, 4_92, 13, 74_91, 3_89_99, 6, 8, 4_64, 1_32, 17_03, 4_92, 13, 46_69, 3_78_67, 13, 75_25, 27, 15_93, 9_88, 13, 3_39_72, 70_29, 6, 20, 82_51, 3_83, 2, 2_70, 58_66, 37_88, 2, 23_53, 82_51, 1_23_38, 2, 1_39_58, 3_87, 2, 36_29, 69_53, 1_88, 29_00, 2, 1_39_58, 80_11, 1_15_01, 23, 84_60, 40_73, 3_40_09, 20, 4_35, 1_14_39, 27, 8, 84_60, 40_73, 60_04, 20, 99_88, 3_75, 27, 33, 2_66, 19_45, 10_76, 13_50, 3_78_67, 32_88, 5, 5_77, 10_76, 43_74, 8, 50_82, 5, 2_64_53, 2_57, 5_56, 4_03, 2, 2_42, 1_32, 3_83, 3_16, 4_92, 8, 1_07_67, 6, 3_16, 3_04, 42_39, 3, 0], [1_48, 1_57_22, 19, 18_39, 12, 13_50, 13, 2_23_27, 50_82, 54_18, 4_75_67, 3_59_38, 59, 3_18, 1_95_52, 1_08, 21_83, 54, 1_49_76, 48_35, 32, 5_47, 11_14, 8, 3_15, 24_17, 5, 92, 1_90_88, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00], [36, 63_95, 1_25_70, 3_91_47, 1_15_97, 6, 2_66, 4, 4_54_05, 72_96, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
												# fmt: on

												self.tokenizer_integration_test_util(
												    expected_encoding=__UpperCamelCase     ,       model_name="Helsinki-NLP/opus-mt-en-de"     ,       revision="1a8c2263da11e68e50938f97e10cd57820bd504c"     ,       decode_kwargs={"use_source_tokenizer": True}     ,       )


					def 	lowerCamelCase       (					self			:str		):
												A		=  MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs"		)

												A		=  "Tämä on testi"
												A		=  "This is a test"

												A		=  [76, 7, 20_47, 2]
												A		=  [69, 12, 11, 9_40, 2]

												A		=  tokenizer(__UpperCamelCase		).input_ids
												self.assertListEqual(__UpperCamelCase     ,       __UpperCamelCase		)

												A		=  tokenizer(text_target=__UpperCamelCase		).input_ids
												self.assertListEqual(__UpperCamelCase     ,       __UpperCamelCase		)

												A		=  tokenizer.decode(__UpperCamelCase     ,       skip_special_tokens=__UpperCamelCase		)
												self.assertEqual(__UpperCamelCase     ,       __UpperCamelCase		)









"""simple docstring"""
def 					A__				(			UpperCamelCase       ):
							A		=  generate_pascal_triangle(UpperCamelCase       )
							for row_idx in range(UpperCamelCase       ):
														# Print left spaces
														for _ in range(num_rows - row_idx - 1       ):
																					print(end=" "       )
														# Print row values
														for col_idx in range(row_idx + 1       ):
																					if col_idx != row_idx:
																												print(triangle[row_idx][col_idx]					,  end=" "       )
																					else:
																												print(triangle[row_idx][col_idx]					,  end=""       )
														print()






def 					A__				(			UpperCamelCase       ):

							if not isinstance(UpperCamelCase					,  UpperCamelCase       ):
														raise TypeError("The input value of 'num_rows' should be 'int'"       )

							if num_rows == 0:
														return []
							elif num_rows < 0:
														raise ValueError(
														    "The input value of 'num_rows' should be greater than or equal to 0"       )

							A		=  []
							for current_row_idx in range(UpperCamelCase       ):
														A		=  populate_current_row(UpperCamelCase					,  UpperCamelCase       )
														triangle.append(UpperCamelCase       )
							return triangle






def 					A__				(			UpperCamelCase					,  UpperCamelCase       ):
							A		=  [-1] * (current_row_idx + 1)
							# first and last elements of current row are equal to 1
							A,	A		=  1, 1
							for current_col_idx in range(1					,  UpperCamelCase       ):
														calculate_current_element(
														    UpperCamelCase					,  UpperCamelCase					,  UpperCamelCase					,  UpperCamelCase       )
							return current_row






def 					A__				(			UpperCamelCase					,  UpperCamelCase					,  UpperCamelCase					,  UpperCamelCase					,  ):
							A		=  triangle[current_row_idx - 1][current_col_idx - 1]
							A		=  triangle[current_row_idx - 1][current_col_idx]
							A		=  above_to_left_elt + above_to_right_elt






def 					A__				(			UpperCamelCase       ):

							if not isinstance(UpperCamelCase					,  UpperCamelCase       ):
														raise TypeError("The input value of 'num_rows' should be 'int'"       )

							if num_rows == 0:
														return []
							elif num_rows < 0:
														raise ValueError(
														    "The input value of 'num_rows' should be greater than or equal to 0"       )

							A		=  [[1]]

							for row_index in range(1					,  UpperCamelCase       ):
														A		=  [0] + result[-1] + [0]
														A		=  row_index + 1
														# Calculate the number of distinct elements in a row
														A		=  sum(divmod(UpperCamelCase					,  2       )       )
														A		=  [
														    temp_row[i - 1] + temp_row[i] for i in range(1					,  distinct_elements + 1       )
														]
														A		=  row_first_half[: (row_index + 1) // 2]
														row_second_half.reverse()
														A		=  row_first_half + row_second_half
														result.append(UpperCamelCase       )

							return result






def 					A__				(			):
							from collections.abc import Callable
							from timeit import timeit

							def benchmark_a_function(UpperCamelCase					,  UpperCamelCase       ) -> None:
														A		=  F"{func.__name__}({value})"
														A		=  timeit(F"__main__.{call}"					,  setup="import __main__"       )
														# print(f"{call:38} = {func(value)} -- {timing:.4f} seconds")
														print(F"{call:38} -- {timing:.4f} seconds"       )

							for value in range(15       ):  # (1, 7, 14):
														for func in (generate_pascal_triangle, generate_pascal_triangle_optimized):
																					benchmark_a_function(UpperCamelCase					,  UpperCamelCase       )
														print()


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()


