






import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand

def      __lowercase					( snake_case ):







				"""simple docstring"""






				return EnvironmentCommand()

class 						lowerCamelCase_				(      lowerCamelCase ):







				@staticmethod
				def 			A	(						__lowerCAmelCase     ):
								"""simple docstring"""
								__magic_name__		:List[str]        =      parser.add_parser('''env'''     )
								download_parser.set_defaults(func=__lowerCAmelCase     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Optional[Any]        =      huggingface_hub.__version__

								__magic_name__		:Tuple        =      '''not installed'''
								__magic_name__		:List[str]        =      '''NA'''
								if is_torch_available():
												import torch

												__magic_name__		:int        =      torch.__version__
												__magic_name__		:Dict        =      torch.cuda.is_available()

								__magic_name__		:int        =      '''not installed'''
								if is_transformers_available():
												import transformers

												__magic_name__		:Any        =      transformers.__version__

								__magic_name__		:List[str]        =      '''not installed'''
								if is_accelerate_available():
												import accelerate

												__magic_name__		:Tuple        =      accelerate.__version__

								__magic_name__		:Any        =      '''not installed'''
								if is_xformers_available():
												import xformers

												__magic_name__		:List[str]        =      xformers.__version__

								__magic_name__		:Any        =      {
								    '''`diffusers` version''': version,
								    '''Platform''': platform.platform(),
								    '''Python version''': platform.python_version(),
								    '''PyTorch version (GPU?)''': F'''{pt_version} ({pt_cuda_available})''',
								    '''Huggingface_hub version''': hub_version,
								    '''Transformers version''': transformers_version,
								    '''Accelerate version''': accelerate_version,
								    '''xFormers version''': xformers_version,
								    '''Using GPU in script?''': '''<fill in>''',
								    '''Using distributed or parallel set-up in script?''': '''<fill in>''',
								}

								print('''\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'''     )
								print(self.format_dict(__lowerCAmelCase     )     )

								return info







				@staticmethod
				def 			A	(						__lowerCAmelCase     ):
								"""simple docstring"""
								return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]     ) + "\n"














import unittest

import numpy as np
import torch

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







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Dict        =      1_0







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Dict        =      [1, 2, 3, 4]
								__magic_name__		:Union[str, Any]        =      [1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
								self.assertEqual(truncate_or_pad(__lowerCAmelCase       ,					self.block_size       ,					0     )       ,					__lowerCAmelCase     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Dict        =      [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
								__magic_name__		:Optional[Any]        =      [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
								self.assertEqual(truncate_or_pad(__lowerCAmelCase       ,					self.block_size       ,					0     )       ,					__lowerCAmelCase     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Any        =      [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0, 1_1, 1_2, 1_3]
								__magic_name__		:str        =      [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
								self.assertEqual(truncate_or_pad(__lowerCAmelCase       ,					self.block_size       ,					0     )       ,					__lowerCAmelCase     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Tuple        =      '''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.'''
								__magic_name__     ,				__magic_name__		:Optional[int]        =      process_story(__lowerCAmelCase     )
								self.assertEqual(__lowerCAmelCase       ,					[]     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Union[str, Any]        =      ''''''
								__magic_name__     ,				__magic_name__		:Optional[int]        =      process_story(__lowerCAmelCase     )
								self.assertEqual(__lowerCAmelCase       ,					[]     )
								self.assertEqual(__lowerCAmelCase       ,					[]     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:List[Any]        =      (
								    '''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'''
								)
								__magic_name__     ,				__magic_name__		:str        =      process_story(__lowerCAmelCase     )

								__magic_name__		:Optional[int]        =      [
								    '''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(__lowerCAmelCase       ,					__lowerCAmelCase     )

								__magic_name__		:Union[str, Any]        =      ['''It was the best of times.''']
								self.assertEqual(__lowerCAmelCase       ,					__lowerCAmelCase     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Any        =      torch.tensor([1, 2, 3, 4]     )
								__magic_name__		:List[str]        =      torch.tensor([1, 1, 1, 1]     )
								np.testing.assert_array_equal(build_mask(__lowerCAmelCase       ,					0     ).numpy()       ,					expected.numpy()     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:List[str]        =      torch.tensor([1, 2, 3, 4, 2_3, 2_3, 2_3]     )
								__magic_name__		:Union[str, Any]        =      torch.tensor([1, 1, 1, 1, 0, 0, 0]     )
								np.testing.assert_array_equal(build_mask(__lowerCAmelCase       ,					2_3     ).numpy()       ,					expected.numpy()     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Any        =      torch.tensor([8, 2, 3, 4, 1, 1, 1]     )
								__magic_name__		:Dict        =      torch.tensor([1, 1, 1, 1, 0, 0, 0]     )
								np.testing.assert_array_equal(build_mask(__lowerCAmelCase       ,					1     ).numpy()       ,					expected.numpy()     )







				def 			A	(						self     ):
								"""simple docstring"""
								__magic_name__		:Dict        =      1_0_1
								__magic_name__		:List[Any]        =      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]]     )
								__magic_name__		:str        =      torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]     )

								__magic_name__		:Tuple        =      compute_token_type_ids(__lowerCAmelCase       ,					__lowerCAmelCase     )
								np.testing.assert_array_equal(__lowerCAmelCase       ,					__lowerCAmelCase     )






