





'''simple docstring'''




import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil




class      UpperCamelCase__					(					lowercase_			):




					"""simple docstring"""


					def lowerCamelCase_			(						self				:			Any						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Optional[int]		=			pa.array(TypedSequence([1, 2, 3]						)						)
							self.assertEqual(arr.type      ,						pa.intaa()						)


					def lowerCamelCase_			(						self				:			Tuple						):

							'''simple docstring'''



							with self.assertRaises(lowerCamelCase_						):
									SCREAMING_SNAKE_CASE :				str		=			pa.array(TypedSequence([1, 2, 3]						)      ,						type=pa.intaa()						)


					def lowerCamelCase_			(						self				:			str						):

							'''simple docstring'''



							with self.assertRaises(lowerCamelCase_						):
									SCREAMING_SNAKE_CASE :				List[Any]		=			pa.array(TypedSequence([1, 2, 3]      ,						try_type=Value("""bool"""						)      ,						type=Value("""int64"""						)						)						)


					def lowerCamelCase_			(						self				:			int						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Dict		=			pa.array(TypedSequence([1, 2, 3]      ,						type=Value("""int32"""						)						)						)
							self.assertEqual(arr.type      ,						pa.intaa()						)


					def lowerCamelCase_			(						self				:			int						):

							'''simple docstring'''



							with self.assertRaises((TypeError, pa.lib.ArrowInvalid)						):
									SCREAMING_SNAKE_CASE :				Tuple		=			pa.array(TypedSequence(["""foo""", """bar"""]      ,						type=Value("""int64"""						)						)						)


					def lowerCamelCase_			(						self				:			Optional[int]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Any		=			pa.array(TypedSequence([1, 2, 3]      ,						try_type=Value("""int32"""						)						)						)
							self.assertEqual(arr.type      ,						pa.intaa()						)


					def lowerCamelCase_			(						self				:			Tuple						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Any		=			pa.array(TypedSequence(["""foo""", """bar"""]      ,						try_type=Value("""int64"""						)						)						)
							self.assertEqual(arr.type      ,						pa.string()						)


					def lowerCamelCase_			(						self				:			Tuple						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Any		=			pa.array(TypedSequence([[[1, 2, 3]]]      ,						type=ArrayaD((1, 3)      ,						"""int64"""						)						)						)
							self.assertEqual(arr.type      ,						ArrayaDExtensionType((1, 3)      ,						"""int64"""						)						)


					def lowerCamelCase_			(						self				:			List[Any]						):

							'''simple docstring'''



							with self.assertRaises((TypeError, pa.lib.ArrowInvalid)						):
									SCREAMING_SNAKE_CASE :				Tuple		=			pa.array(TypedSequence(["""foo""", """bar"""]      ,						type=ArrayaD((1, 3)      ,						"""int64"""						)						)						)


					def lowerCamelCase_			(						self				:			List[str]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Optional[int]		=			pa.array(TypedSequence([[[1, 2, 3]]]      ,						try_type=ArrayaD((1, 3)      ,						"""int64"""						)						)						)
							self.assertEqual(arr.type      ,						ArrayaDExtensionType((1, 3)      ,						"""int64"""						)						)


					def lowerCamelCase_			(						self				:			str						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Optional[int]		=			pa.array(TypedSequence(["""foo""", """bar"""]      ,						try_type=ArrayaD((1, 3)      ,						"""int64"""						)						)						)
							self.assertEqual(arr.type      ,						pa.string()						)



					@require_pil
					def lowerCamelCase_			(						self				:			Optional[Any]						):

							'''simple docstring'''



							import PIL.Image

							SCREAMING_SNAKE_CASE :				Optional[Any]		=			PIL.Image.fromarray(np.arange(10      ,						dtype=np.uinta						).reshape(2      ,						5						)						)
							with patch(
							    """datasets.arrow_writer.cast_to_python_objects"""      ,						side_effect=lowerCamelCase_						) as mock_cast_to_python_objects:
									SCREAMING_SNAKE_CASE :				List[str]		=			pa.array(TypedSequence([{"""path""": None, """bytes""": b"""image_bytes"""}, pil_image]      ,						type=Image()						)						)
									SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				str		=			mock_cast_to_python_objects.call_args_list[-1]
									self.assertIn("""optimize_list_casting"""      ,						lowerCamelCase_						)
									self.assertFalse(kwargs["""optimize_list_casting"""]						)







def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				List[str]		=			pa.BufferReader(lowerCamelCase_	) if isinstance(lowerCamelCase_			,			pa.Buffer	) else pa.memory_map(lowerCamelCase_	)
		SCREAMING_SNAKE_CASE :				Dict		=			pa.ipc.open_stream(lowerCamelCase_	)
		SCREAMING_SNAKE_CASE :				pa.Table		=			f.read_all()
		assert len(pa_table.to_batches()	) == expected_num_chunks
		assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
		del pa_table



@pytest.mark.parametrize("""writer_batch_size"""			,			[None, 1, 10]	)
@pytest.mark.parametrize(
    """fields"""			,			[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Union[str, Any]		=			pa.BufferOutputStream()
		SCREAMING_SNAKE_CASE :				Any		=			pa.schema(lowerCamelCase_	) if fields else None
		with ArrowWriter(stream=lowerCamelCase_			,			schema=lowerCamelCase_			,			writer_batch_size=lowerCamelCase_	) as writer:
				writer.write({"""col_1""": """foo""", """col_2""": 1}	)
				writer.write({"""col_1""": """bar""", """col_2""": 2}	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Tuple		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				SCREAMING_SNAKE_CASE :				Optional[int]		=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
		assert writer._schema == pa.schema(lowerCamelCase_			,			metadata=writer._schema.metadata	)
		_check_output(output.getvalue()			,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)



def 		__A		(  ):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Union[str, Any]		=			pa.BufferOutputStream()
		SCREAMING_SNAKE_CASE :				Union[str, Any]		=			Features({"""labels""": ClassLabel(names=["""neg""", """pos"""]	)}	)
		with ArrowWriter(stream=lowerCamelCase_			,			features=lowerCamelCase_	) as writer:
				writer.write({"""labels""": 0}	)
				writer.write({"""labels""": 1}	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Optional[Any]		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		assert writer._schema == features.arrow_schema
		assert writer._schema.metadata == features.arrow_schema.metadata
		SCREAMING_SNAKE_CASE :				Tuple		=			pa.BufferReader(output.getvalue()	)
		SCREAMING_SNAKE_CASE :				List[str]		=			pa.ipc.open_stream(lowerCamelCase_	)
		SCREAMING_SNAKE_CASE :				pa.Table		=			f.read_all()
		SCREAMING_SNAKE_CASE :				Optional[Any]		=			pa_table.schema
		assert pa_table.num_rows == 2
		assert schema == features.arrow_schema
		assert schema.metadata == features.arrow_schema.metadata
		assert features == Features.from_arrow_schema(lowerCamelCase_	)



@pytest.mark.parametrize("""writer_batch_size"""			,			[None, 1, 10]	)
def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				List[Any]		=			pa.BufferOutputStream()
		with ArrowWriter(
		    stream=lowerCamelCase_			,			writer_batch_size=lowerCamelCase_			,			hash_salt="""split_name"""			,			check_duplicates=lowerCamelCase_			,			) as writer:
				with pytest.raises(lowerCamelCase_	):
						writer.write({"""col_1""": """foo""", """col_2""": 1}			,			key=[1, 2]	)
						SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Tuple		=			writer.finalize()



@pytest.mark.parametrize("""writer_batch_size"""			,			[None, 2, 10]	)
def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Optional[int]		=			pa.BufferOutputStream()
		with ArrowWriter(
		    stream=lowerCamelCase_			,			writer_batch_size=lowerCamelCase_			,			hash_salt="""split_name"""			,			check_duplicates=lowerCamelCase_			,			) as writer:
				with pytest.raises(lowerCamelCase_	):
						writer.write({"""col_1""": """foo""", """col_2""": 1}			,			key=10	)
						writer.write({"""col_1""": """bar""", """col_2""": 2}			,			key=10	)
						SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			writer.finalize()



@pytest.mark.parametrize("""writer_batch_size"""			,			[None, 2, 10]	)
def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				List[str]		=			pa.BufferOutputStream()
		with ArrowWriter(
		    stream=lowerCamelCase_			,			writer_batch_size=lowerCamelCase_			,			hash_salt="""split_name"""			,			check_duplicates=lowerCamelCase_			,			) as writer:
				writer.write({"""col_1""": """foo""", """col_2""": 1}			,			key=1	)
				writer.write({"""col_1""": """bar""", """col_2""": 2}			,			key=2	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Dict		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		_check_output(output.getvalue()			,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)



@pytest.mark.parametrize("""writer_batch_size"""			,			[None, 1, 10]	)
@pytest.mark.parametrize(
    """fields"""			,			[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Any		=			pa.BufferOutputStream()
		SCREAMING_SNAKE_CASE :				Dict		=			pa.schema(lowerCamelCase_	) if fields else None
		with ArrowWriter(stream=lowerCamelCase_			,			schema=lowerCamelCase_			,			writer_batch_size=lowerCamelCase_	) as writer:
				writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}	)
				writer.write_batch({"""col_1""": [], """col_2""": []}	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Any		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				SCREAMING_SNAKE_CASE :				Optional[int]		=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
		assert writer._schema == pa.schema(lowerCamelCase_			,			metadata=writer._schema.metadata	)
		_check_output(output.getvalue()			,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)



@pytest.mark.parametrize("""writer_batch_size"""			,			[None, 1, 10]	)
@pytest.mark.parametrize(
    """fields"""			,			[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				List[str]		=			pa.BufferOutputStream()
		SCREAMING_SNAKE_CASE :				Optional[int]		=			pa.schema(lowerCamelCase_	) if fields else None
		with ArrowWriter(stream=lowerCamelCase_			,			schema=lowerCamelCase_			,			writer_batch_size=lowerCamelCase_	) as writer:
				writer.write_table(pa.Table.from_pydict({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}	)	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Any		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				SCREAMING_SNAKE_CASE :				Optional[int]		=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
		assert writer._schema == pa.schema(lowerCamelCase_			,			metadata=writer._schema.metadata	)
		_check_output(output.getvalue()			,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)



@pytest.mark.parametrize("""writer_batch_size"""			,			[None, 1, 10]	)
@pytest.mark.parametrize(
    """fields"""			,			[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				int		=			pa.BufferOutputStream()
		SCREAMING_SNAKE_CASE :				Optional[Any]		=			pa.schema(lowerCamelCase_	) if fields else None
		with ArrowWriter(stream=lowerCamelCase_			,			schema=lowerCamelCase_			,			writer_batch_size=lowerCamelCase_	) as writer:
				writer.write_row(pa.Table.from_pydict({"""col_1""": ["""foo"""], """col_2""": [1]}	)	)
				writer.write_row(pa.Table.from_pydict({"""col_1""": ["""bar"""], """col_2""": [2]}	)	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Optional[int]		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				SCREAMING_SNAKE_CASE :				str		=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
		assert writer._schema == pa.schema(lowerCamelCase_			,			metadata=writer._schema.metadata	)
		_check_output(output.getvalue()			,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)



def 		__A		(  ):


		"""simple docstring"""



		with tempfile.TemporaryDirectory() as tmp_dir:
				SCREAMING_SNAKE_CASE :				Optional[int]		=			{"""col_1""": pa.string(), """col_2""": pa.intaa()}
				SCREAMING_SNAKE_CASE :				Optional[int]		=			os.path.join(lowerCamelCase_			,			"""test.arrow"""	)
				with ArrowWriter(path=lowerCamelCase_			,			schema=pa.schema(lowerCamelCase_	)	) as writer:
						writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}	)
						SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Tuple		=			writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				assert writer._schema == pa.schema(lowerCamelCase_			,			metadata=writer._schema.metadata	)
				_check_output(lowerCamelCase_			,			1	)



def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		if pa.types.is_list(lowerCamelCase_	):
				return get_base_dtype(arr_type.value_type	)
		else:
				return arr_type



def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		if isinstance(lst[0]			,			lowerCamelCase_	):
				change_first_primitive_element_in_list(lst[0]			,			lowerCamelCase_	)
		else:
				SCREAMING_SNAKE_CASE :				List[str]		=			value



@pytest.mark.parametrize("""optimized_int_type, expected_dtype"""			,			[(None, pa.intaa()), (Value("""int32"""	), pa.intaa())]	)
@pytest.mark.parametrize("""sequence"""			,			[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				int		=			pa.array(TypedSequence(lowerCamelCase_			,			optimized_int_type=lowerCamelCase_	)	)
		assert get_base_dtype(arr.type	) == expected_dtype



@pytest.mark.parametrize(
    """col, expected_dtype"""			,			[
        ("""attention_mask""", pa.inta()),
        ("""special_tokens_mask""", pa.inta()),
        ("""token_type_ids""", pa.inta()),
        ("""input_ids""", pa.intaa()),
        ("""other""", pa.intaa()),
    ]			,			)
@pytest.mark.parametrize("""sequence"""			,			[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Any		=			pa.array(OptimizedTypedSequence(lowerCamelCase_			,			col=lowerCamelCase_	)	)
		assert get_base_dtype(arr.type	) == expected_dtype

		# not in range
		if col != "other":
				# avoids errors due to in-place modifications
				SCREAMING_SNAKE_CASE :				Union[str, Any]		=			copy.deepcopy(lowerCamelCase_	)
				SCREAMING_SNAKE_CASE :				int		=			np.iinfo(expected_dtype.to_pandas_dtype()	).max + 1
				change_first_primitive_element_in_list(lowerCamelCase_			,			lowerCamelCase_	)
				SCREAMING_SNAKE_CASE :				Union[str, Any]		=			pa.array(OptimizedTypedSequence(lowerCamelCase_			,			col=lowerCamelCase_	)	)
				assert get_base_dtype(arr.type	) == pa.intaa()



@pytest.mark.parametrize("""raise_exception"""			,			[False, True]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				int		=			str(tmp_path / """dataset-train.arrow"""	)
		try:
				with ArrowWriter(path=lowerCamelCase_	) as writer:
						if raise_exception:
								raise pa.lib.ArrowInvalid()
						else:
								writer.stream.close()
		except pa.lib.ArrowInvalid:
				pass
		finally:
				assert writer.stream.closed



def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Union[str, Any]		=			"""mock://dataset-train.arrow"""
		with ArrowWriter(path=lowerCamelCase_			,			storage_options=mockfs.storage_options	) as writer:
				assert isinstance(writer._fs			,			type(lowerCamelCase_	)	)
				assert writer._fs.storage_options == mockfs.storage_options
				writer.write({"""col_1""": """foo""", """col_2""": 1}	)
				writer.write({"""col_1""": """bar""", """col_2""": 2}	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				Optional[int]		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		assert mockfs.exists(lowerCamelCase_	)



def 		__A		(  ):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				Union[str, Any]		=			pa.BufferOutputStream()
		with ParquetWriter(stream=lowerCamelCase_	) as writer:
				writer.write({"""col_1""": """foo""", """col_2""": 1}	)
				writer.write({"""col_1""": """bar""", """col_2""": 2}	)
				SCREAMING_SNAKE_CASE,							SCREAMING_SNAKE_CASE :				str		=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		SCREAMING_SNAKE_CASE :				Union[str, Any]		=			pa.BufferReader(output.getvalue()	)
		SCREAMING_SNAKE_CASE :				pa.Table		=			pq.read_table(lowerCamelCase_	)
		assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}



@require_pil
@pytest.mark.parametrize("""embed_local_files"""			,			[False, True]	)
def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		import PIL.Image

		SCREAMING_SNAKE_CASE :				Dict		=			str(tmp_path / """test_image_rgb.jpg"""	)
		PIL.Image.fromarray(np.zeros((5, 5)			,			dtype=np.uinta	)	).save(lowerCamelCase_			,			format="""png"""	)
		SCREAMING_SNAKE_CASE :				List[str]		=			pa.BufferOutputStream()
		with ParquetWriter(
		    stream=lowerCamelCase_			,			features=Features({"""image""": Image()}	)			,			embed_local_files=lowerCamelCase_	) as writer:
				writer.write({"""image""": image_path}	)
				writer.finalize()
		SCREAMING_SNAKE_CASE :				Dict		=			pa.BufferReader(output.getvalue()	)
		SCREAMING_SNAKE_CASE :				pa.Table		=			pq.read_table(lowerCamelCase_	)
		SCREAMING_SNAKE_CASE :				str		=			pa_table.to_pydict()
		if embed_local_files:
				assert isinstance(out["""image"""][0]["""path"""]			,			lowerCamelCase_	)
				with open(lowerCamelCase_			,			"""rb"""	) as f:
						assert out["image"][0]["bytes"] == f.read()
		else:
				assert out["image"][0]["path"] == image_path
				assert out["image"][0]["bytes"] is None



def 		__A		(  ):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				int		=			pa.schema([pa.field("""col_1"""			,			pa.string()			,			nullable=lowerCamelCase_	)]	)
		SCREAMING_SNAKE_CASE :				Any		=			pa.BufferOutputStream()
		with ArrowWriter(stream=lowerCamelCase_	) as writer:
				writer._build_writer(inferred_schema=lowerCamelCase_	)
				assert writer._schema == pa.schema([pa.field("""col_1"""			,			pa.string()	)]	)










'''simple docstring'''




from math import sqrt



def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				str		=			0
		for i in range(1			,			int(sqrt(lowerCamelCase_	) + 1	)	):
				if n % i == 0 and i != sqrt(lowerCamelCase_	):
						total += i + n // i
				elif i == sqrt(lowerCamelCase_	):
						total += i
		return total - n



def 		__A		(  lowerCamelCase_ = 1_00_00	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				str		=			sum(
		    i
		    for i in range(1			,			lowerCamelCase_	)
		    if sum_of_divisors(sum_of_divisors(lowerCamelCase_	)	) == i and sum_of_divisors(lowerCamelCase_	) != i	)
		return total


if __name__ == "__main__":
							print(solution(int(str(input()).strip())))



