
from argparse import ArgumentParser

from . import BaseTransformersCLICommand




def 				a						(							snake_case__:					Tuple					):


				'''simple docstring'''
				return DownloadCommand(args.model						,   args.cache_dir						,   args.force						,   args.trust_remote_code					)


class  lowercase__(				UpperCAmelCase							):



	"""simple docstring"""




	@staticmethod
	def 						_lowercase  (       SCREAMING_SNAKE_CASE_  :			ArgumentParser       )       ->     int:
					lowercase_       =					parser.add_parser('''download'''       )
					download_parser.add_argument(
					    '''--cache-dir'''       ,							type=SCREAMING_SNAKE_CASE_       ,							default=SCREAMING_SNAKE_CASE_       ,							help='''Path to location to store the models'''       )
					download_parser.add_argument(
					    '''--force'''       ,							action='''store_true'''       ,							help='''Force the model to be download even if already in cache-dir'''       )
					download_parser.add_argument(
					    '''--trust-remote-code'''       ,							action='''store_true'''       ,							help='''Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine'''       ,							)
					download_parser.add_argument('''model'''       ,							type=SCREAMING_SNAKE_CASE_       ,							help='''Name of the model to download'''       )
					download_parser.set_defaults(func=SCREAMING_SNAKE_CASE_       )
	def __init__(       self  :			str       ,							SCREAMING_SNAKE_CASE_  :			str       ,							SCREAMING_SNAKE_CASE_  :			str       ,							SCREAMING_SNAKE_CASE_  :			bool       ,							SCREAMING_SNAKE_CASE_  :			bool       )       ->     Optional[Any]:
					lowercase_       =					model
					lowercase_       =					cache
					lowercase_       =					force
					lowercase_       =					trust_remote_code




	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Union[str, Any]:
					from ..models.auto import AutoModel, AutoTokenizer

					AutoModel.from_pretrained(
					    self._model       ,							cache_dir=self._cache       ,							force_download=self._force       ,							trust_remote_code=self._trust_remote_code       )
					AutoTokenizer.from_pretrained(
					    self._model       ,							cache_dir=self._cache       ,							force_download=self._force       ,							trust_remote_code=self._trust_remote_code       )






import unittest

import numpy as np
import torch

from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	def 						_lowercase  (       self  :			List[str]       )       ->     List[Any]:
					lowercase_       =					1_0
	def 						_lowercase  (       self  :			int       )       ->     List[str]:
					lowercase_       =					[1, 2, 3, 4]
					lowercase_       =					[1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
					self.assertEqual(truncate_or_pad(SCREAMING_SNAKE_CASE_       ,							self.block_size       ,							0       )       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			int       )       ->     Optional[Any]:
					lowercase_       =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
					lowercase_       =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
					self.assertEqual(truncate_or_pad(SCREAMING_SNAKE_CASE_       ,							self.block_size       ,							0       )       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					lowercase_       =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0, 1_1, 1_2, 1_3]
					lowercase_       =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
					self.assertEqual(truncate_or_pad(SCREAMING_SNAKE_CASE_       ,							self.block_size       ,							0       )       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Any       )       ->     List[Any]:
					lowercase_       =					'''It was the year of Our Lord one thousand seven hundred and
        seventy-five.\n\nSpiritual revelations were conceded to England at that
        favoured period, as at this.'''
					lowercase_  ,	lowercase_       =					process_story(SCREAMING_SNAKE_CASE_       )
					self.assertEqual(SCREAMING_SNAKE_CASE_       ,							[]       )
	def 						_lowercase  (       self  :			List[str]       )       ->     List[str]:
					lowercase_       =					''''''
					lowercase_  ,	lowercase_       =					process_story(SCREAMING_SNAKE_CASE_       )
					self.assertEqual(SCREAMING_SNAKE_CASE_       ,							[]       )
					self.assertEqual(SCREAMING_SNAKE_CASE_       ,							[]       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Union[str, Any]:
					lowercase_       =					(
					    '''It was the year of Our Lord one thousand seven hundred and '''
					    '''seventy-five\n\nSpiritual revelations were conceded to England '''
					    '''at that favoured period, as at this.\n@highlight\n\nIt was the best of times'''
					)
					lowercase_  ,	lowercase_       =					process_story(SCREAMING_SNAKE_CASE_       )

					lowercase_       =					[
					    '''It was the year of Our Lord one thousand seven hundred and seventy-five.''',
					    '''Spiritual revelations were conceded to England at that favoured period, as at this.''',
					]
					self.assertEqual(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )

					lowercase_       =					['''It was the best of times.''']
					self.assertEqual(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[Any]:
					lowercase_       =					torch.tensor([1, 2, 3, 4]       )
					lowercase_       =					torch.tensor([1, 1, 1, 1]       )
					np.testing.assert_array_equal(build_mask(SCREAMING_SNAKE_CASE_       ,							0       ).numpy()       ,							expected.numpy()       )
	def 						_lowercase  (       self  :			List[Any]       )       ->     Tuple:
					lowercase_       =					torch.tensor([1, 2, 3, 4, 2_3, 2_3, 2_3]       )
					lowercase_       =					torch.tensor([1, 1, 1, 1, 0, 0, 0]       )
					np.testing.assert_array_equal(build_mask(SCREAMING_SNAKE_CASE_       ,							2_3       ).numpy()       ,							expected.numpy()       )
	def 						_lowercase  (       self  :			int       )       ->     Dict:
					lowercase_       =					torch.tensor([8, 2, 3, 4, 1, 1, 1]       )
					lowercase_       =					torch.tensor([1, 1, 1, 1, 0, 0, 0]       )
					np.testing.assert_array_equal(build_mask(SCREAMING_SNAKE_CASE_       ,							1       ).numpy()       ,							expected.numpy()       )




	def 						_lowercase  (       self  :			List[str]       )       ->     Tuple:
					lowercase_       =					1_0_1
					lowercase_       =					torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 1_0_1, 5, 6], [1, 1_0_1, 3, 4, 1_0_1, 6]]       )
					lowercase_       =					torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]       )

					lowercase_       =					compute_token_type_ids(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )
					np.testing.assert_array_equal(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )




