


'''simple docstring'''
import unittest

from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor


if is_flax_available():
		import os

		# The slow tests are often failing with OOM error on GPU
		# This makes JAX allocate exactly what is needed on demand, and deallocate memory that is no longer needed
		# but will be slower as stated here https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html
		__snake_case				 =	'''platform'''
		import jax
		import jax.numpy as jnp
		import numpy as np

		from transformers import FlaxPegasusForConditionalGeneration, FlaxPegasusModel
@require_flax
class   lowercase      :

		"""simple docstring"""

		_a       					=							PegasusConfig
		_a       					=							{}
		_a       					=							'gelu'




		def __init__(						self       ,  UpperCamelCase_       ,  UpperCamelCase_=13       ,  UpperCamelCase_=7       ,  UpperCamelCase_=True       ,  UpperCamelCase_=False       ,  UpperCamelCase_=99       ,  UpperCamelCase_=32       ,  UpperCamelCase_=5       ,  UpperCamelCase_=4       ,  UpperCamelCase_=37       ,  UpperCamelCase_=0.1       ,  UpperCamelCase_=0.1       ,  UpperCamelCase_=20       ,  UpperCamelCase_=2       ,  UpperCamelCase_=1       ,  UpperCamelCase_=0       ,  ):

							'''simple docstring'''


							UpperCamelCase__  :Union[str, Any]				   =					parent
							UpperCamelCase__  :List[Any]				   =					batch_size
							UpperCamelCase__  :Optional[int]				   =					seq_length
							UpperCamelCase__  :Union[str, Any]				   =					is_training
							UpperCamelCase__  :Optional[Any]				   =					use_labels
							UpperCamelCase__  :List[str]				   =					vocab_size
							UpperCamelCase__  :Dict				   =					hidden_size
							UpperCamelCase__  :Union[str, Any]				   =					num_hidden_layers
							UpperCamelCase__  :List[Any]				   =					num_attention_heads
							UpperCamelCase__  :Any				   =					intermediate_size

							UpperCamelCase__  :Optional[Any]				   =					hidden_dropout_prob
							UpperCamelCase__  :Union[str, Any]				   =					attention_probs_dropout_prob
							UpperCamelCase__  :int				   =					max_position_embeddings
							UpperCamelCase__  :Optional[Any]				   =					eos_token_id
							UpperCamelCase__  :int				   =					pad_token_id
							UpperCamelCase__  :Dict				   =					bos_token_id




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :Tuple				   =					ids_tensor([self.batch_size, self.seq_length - 1]       ,  self.vocab_size				).clip(3       ,  self.vocab_size				)
							UpperCamelCase__  :Optional[int]				   =					np.expand_dims(np.array([self.eos_token_id] * self.batch_size				)       ,  1				)
							UpperCamelCase__  :Tuple				   =					np.concatenate([input_ids, eos_tensor]       ,  axis=1				)

							UpperCamelCase__  :Optional[int]				   =					ids_tensor([self.batch_size, self.seq_length]       ,  self.vocab_size				)

							UpperCamelCase__  :Optional[int]				   =					self.config_cls(
							    vocab_size=self.vocab_size       ,  d_model=self.hidden_size       ,  encoder_layers=self.num_hidden_layers       ,  decoder_layers=self.num_hidden_layers       ,  encoder_attention_heads=self.num_attention_heads       ,  decoder_attention_heads=self.num_attention_heads       ,  encoder_ffn_dim=self.intermediate_size       ,  decoder_ffn_dim=self.intermediate_size       ,  dropout=self.hidden_dropout_prob       ,  attention_dropout=self.attention_probs_dropout_prob       ,  max_position_embeddings=self.max_position_embeddings       ,  eos_token_ids=[2]       ,  bos_token_id=self.bos_token_id       ,  pad_token_id=self.pad_token_id       ,  decoder_start_token_id=self.pad_token_id       ,  **self.config_updates       ,  )
							UpperCamelCase__  :Tuple				   =					prepare_pegasus_inputs_dict(UpperCamelCase_       ,  UpperCamelCase_       ,  UpperCamelCase_				)
							return config, inputs_dict




		def        lowerCAmelCase__							(						self       ,  UpperCamelCase_       ,  UpperCamelCase_       ,  UpperCamelCase_				):

							'''simple docstring'''


							UpperCamelCase__  :List[Any]				   =					20
							UpperCamelCase__  :Optional[int]				   =					model_class_name(UpperCamelCase_				)

							UpperCamelCase__  :str				   =					model.encode(inputs_dict['''input_ids''']				)

							UpperCamelCase__   ,							UpperCamelCase__  :Union[str, Any]				   =					(
							    inputs_dict['''decoder_input_ids'''],
							    inputs_dict['''decoder_attention_mask'''],
							)

							UpperCamelCase__  :int				   =					model.init_cache(decoder_input_ids.shape[0]       ,  UpperCamelCase_       ,  UpperCamelCase_				)
							UpperCamelCase__  :int				   =					jnp.ones((decoder_input_ids.shape[0], max_decoder_length)       ,  dtype='''i4'''				)

							UpperCamelCase__  :Tuple				   =					jnp.broadcast_to(
							    jnp.arange(decoder_input_ids.shape[-1] - 1				)[None, :]       ,  (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)       ,  )
							UpperCamelCase__  :Tuple				   =					model.decode(
							    decoder_input_ids[:, :-1]       ,  UpperCamelCase_       ,  decoder_attention_mask=UpperCamelCase_       ,  past_key_values=UpperCamelCase_       ,  decoder_position_ids=UpperCamelCase_       ,  )

							UpperCamelCase__  :List[str]				   =					jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]       ,  dtype='''i4'''				)
							UpperCamelCase__  :List[str]				   =					model.decode(
							    decoder_input_ids[:, -1:]       ,  UpperCamelCase_       ,  decoder_attention_mask=UpperCamelCase_       ,  past_key_values=outputs_cache.past_key_values       ,  decoder_position_ids=UpperCamelCase_       ,  )

							UpperCamelCase__  :int				   =					model.decode(UpperCamelCase_       ,  UpperCamelCase_				)

							UpperCamelCase__  :int				   =					np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])				)				)
							self.parent.assertTrue(diff < 1e-3       ,  msg=F'''Max diff is {diff}'''				)




		def        lowerCAmelCase__							(						self       ,  UpperCamelCase_       ,  UpperCamelCase_       ,  UpperCamelCase_				):

							'''simple docstring'''


							UpperCamelCase__  :Optional[Any]				   =					20
							UpperCamelCase__  :Dict				   =					model_class_name(UpperCamelCase_				)

							UpperCamelCase__  :int				   =					model.encode(inputs_dict['''input_ids''']				)

							UpperCamelCase__   ,							UpperCamelCase__  :str				   =					(
							    inputs_dict['''decoder_input_ids'''],
							    inputs_dict['''decoder_attention_mask'''],
							)

							UpperCamelCase__  :Dict				   =					jnp.concatenate(
							    [
							        decoder_attention_mask,
							        jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1])				),
							    ]       ,  axis=-1       ,  )

							UpperCamelCase__  :List[Any]				   =					model.init_cache(decoder_input_ids.shape[0]       ,  UpperCamelCase_       ,  UpperCamelCase_				)
							UpperCamelCase__  :Tuple				   =					jnp.broadcast_to(
							    jnp.arange(decoder_input_ids.shape[-1] - 1				)[None, :]       ,  (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)       ,  )

							UpperCamelCase__  :Union[str, Any]				   =					model.decode(
							    decoder_input_ids[:, :-1]       ,  UpperCamelCase_       ,  decoder_attention_mask=UpperCamelCase_       ,  past_key_values=UpperCamelCase_       ,  decoder_position_ids=UpperCamelCase_       ,  )
							UpperCamelCase__  :List[Any]				   =					jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]       ,  dtype='''i4'''				)
							UpperCamelCase__  :Any				   =					model.decode(
							    decoder_input_ids[:, -1:]       ,  UpperCamelCase_       ,  past_key_values=outputs_cache.past_key_values       ,  decoder_attention_mask=UpperCamelCase_       ,  decoder_position_ids=UpperCamelCase_       ,  )

							UpperCamelCase__  :Optional[Any]				   =					model.decode(UpperCamelCase_       ,  UpperCamelCase_       ,  decoder_attention_mask=UpperCamelCase_				)

							UpperCamelCase__  :Tuple				   =					np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])				)				)
							self.parent.assertTrue(diff < 1e-3       ,  msg=F'''Max diff is {diff}'''				)



def      a (     __a					,   __a					,   __a					,   __a=None					,   __a=None					,   )    ->      Optional[int]:



					'''simple docstring'''






					if attention_mask is None:
										UpperCamelCase__  :Optional[int]				   =					np.not_equal(__a					,   config.pad_token_id  ).astype(np.inta  )
					if decoder_attention_mask is None:
										UpperCamelCase__  :Any				   =					np.concatenate(
										    [
										        np.ones(decoder_input_ids[:, :1].shape					,   dtype=np.inta  ),
										        np.not_equal(decoder_input_ids[:, 1:]					,   config.pad_token_id  ).astype(np.inta  ),
										    ]					,   axis=-1					,   )
					return {
					    "input_ids": input_ids,
					    "decoder_input_ids": decoder_input_ids,
					    "attention_mask": attention_mask,
					    "decoder_attention_mask": decoder_attention_mask,
					}







@require_flax
class   lowercase      (				A__      ,						unittest.TestCase   ):

		"""simple docstring"""

		_a       					=							(
		    (
		        FlaxPegasusForConditionalGeneration,
		        FlaxPegasusModel,
		    )
		    if is_flax_available()
		    else ()
		)
		_a       					=							(FlaxPegasusForConditionalGeneration,) if is_flax_available() else ()
		_a       					=							True
		_a       					=							False
		_a       					=							False
		_a       					=							False




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :Union[str, Any]				   =					FlaxPegasusModelTester(self				)
							UpperCamelCase__  :str				   =					ConfigTester(self       ,  config_class=UpperCamelCase_				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							self.config_tester.run_common_tests()




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__   ,							UpperCamelCase__  :Dict				   =					self.model_tester.prepare_config_and_inputs_for_common()
							for model_class in self.all_model_classes:
												self.model_tester.check_use_cache_forward(UpperCamelCase_       ,  UpperCamelCase_       ,  UpperCamelCase_				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__   ,							UpperCamelCase__  :List[str]				   =					self.model_tester.prepare_config_and_inputs_for_common()
							for model_class in self.all_model_classes:
												self.model_tester.check_use_cache_forward_with_attn_mask(UpperCamelCase_       ,  UpperCamelCase_       ,  UpperCamelCase_				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__   ,							UpperCamelCase__  :Optional[Any]				   =					self.model_tester.prepare_config_and_inputs_for_common()

							for model_class in self.all_model_classes:
												with self.subTest(model_class.__name__				):
																	UpperCamelCase__  :Union[str, Any]				   =					self._prepare_for_class(UpperCamelCase_       ,  UpperCamelCase_				)
																	UpperCamelCase__  :str				   =					model_class(UpperCamelCase_				)

																	@jax.jit
																	def encode_jitted(UpperCamelCase_       ,  UpperCamelCase_=None       ,  **UpperCamelCase_				):
																						return model.encode(input_ids=UpperCamelCase_       ,  attention_mask=UpperCamelCase_				)

																	with self.subTest('''JIT Enabled'''				):
																						UpperCamelCase__  :Any				   =					encode_jitted(**UpperCamelCase_				).to_tuple()

																	with self.subTest('''JIT Disabled'''				):
																						with jax.disable_jit():
																											UpperCamelCase__  :str				   =					encode_jitted(**UpperCamelCase_				).to_tuple()

																	self.assertEqual(len(UpperCamelCase_				)       ,  len(UpperCamelCase_				)				)
																	for jitted_output, output in zip(UpperCamelCase_       ,  UpperCamelCase_				):
																						self.assertEqual(jitted_output.shape       ,  output.shape				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__   ,							UpperCamelCase__  :Optional[Any]				   =					self.model_tester.prepare_config_and_inputs_for_common()

							for model_class in self.all_model_classes:
												with self.subTest(model_class.__name__				):
																	UpperCamelCase__  :str				   =					model_class(UpperCamelCase_				)
																	UpperCamelCase__  :int				   =					model.encode(inputs_dict['''input_ids''']       ,  inputs_dict['''attention_mask''']				)

																	UpperCamelCase__  :Optional[Any]				   =					{
																	    '''decoder_input_ids''': inputs_dict['''decoder_input_ids'''],
																	    '''decoder_attention_mask''': inputs_dict['''decoder_attention_mask'''],
																	    '''encoder_outputs''': encoder_outputs,
																	}

																	@jax.jit
																	def decode_jitted(UpperCamelCase_       ,  UpperCamelCase_       ,  UpperCamelCase_				):
																						return model.decode(
																						    decoder_input_ids=UpperCamelCase_       ,  decoder_attention_mask=UpperCamelCase_       ,  encoder_outputs=UpperCamelCase_       ,  )

																	with self.subTest('''JIT Enabled'''				):
																						UpperCamelCase__  :Any				   =					decode_jitted(**UpperCamelCase_				).to_tuple()

																	with self.subTest('''JIT Disabled'''				):
																						with jax.disable_jit():
																											UpperCamelCase__  :List[str]				   =					decode_jitted(**UpperCamelCase_				).to_tuple()

																	self.assertEqual(len(UpperCamelCase_				)       ,  len(UpperCamelCase_				)				)
																	for jitted_output, output in zip(UpperCamelCase_       ,  UpperCamelCase_				):
																						self.assertEqual(jitted_output.shape       ,  output.shape				)




		@slow
		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							for model_class_name in self.all_model_classes:
												UpperCamelCase__  :List[Any]				   =					model_class_name.from_pretrained('''google/pegasus-large'''       ,  from_pt=UpperCamelCase_				)
												UpperCamelCase__  :Optional[Any]				   =					np.ones((1, 1)				)
												UpperCamelCase__  :List[Any]				   =					model(UpperCamelCase_				)
												self.assertIsNotNone(UpperCamelCase_				)




		@slow
		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :str				   =					FlaxPegasusForConditionalGeneration.from_pretrained('''google/pegasus-xsum'''				)
							UpperCamelCase__  :Dict				   =					PegasusTokenizer.from_pretrained('''google/pegasus-xsum'''				)

							UpperCamelCase__  :Optional[Any]				   =					[
							    ''' PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.''',
							    ''' The London trio are up for best UK act and best album, as well as getting two nominations in the best song category."We got told like this morning \'Oh I think you\'re nominated\'", said Dappy."And I was like \'Oh yeah, which one?\' And now we\'ve got nominated for four awards. I mean, wow!"Bandmate Fazer added: "We thought it\'s best of us to come down and mingle with everyone and say hello to the cameras. And now we find we\'ve got four nominations."The band have two shots at the best song prize, getting the nod for their Tynchy Stryder collaboration Number One, and single Strong Again.Their album Uncle B will also go up against records by the likes of Beyonce and Kanye West.N-Dubz picked up the best newcomer Mobo in 2007, but female member Tulisa said they wouldn\'t be too disappointed if they didn\'t win this time around."At the end of the day we\'re grateful to be where we are in our careers."If it don\'t happen then it don\'t happen - live to fight another day and keep on making albums and hits for the fans."Dappy also revealed they could be performing live several times on the night.The group will be doing Number One and also a possible rendition of the War Child single, I Got Soul.The charity song is a  re-working of The Killers\' All These Things That I\'ve Done and is set to feature artists like Chipmunk, Ironik and Pixie Lott.This year\'s Mobos will be held outside of London for the first time, in Glasgow on 30 September.N-Dubz said they were looking forward to performing for their Scottish fans and boasted about their recent shows north of the border."We just done Edinburgh the other day," said Dappy."We smashed up an N-Dubz show over there. We done Aberdeen about three or four months ago - we smashed up that show over there! Everywhere we go we smash it up!" ''',
							]

							UpperCamelCase__  :List[str]				   =					[
							    '''California\'s largest electricity provider has turned off power to hundreds of thousands of customers.''',
							    '''Pop group N-Dubz have revealed they were surprised to get four nominations for this year\'s Mobo Awards.''',
							]

							UpperCamelCase__  :Dict				   =					tokenizer(UpperCamelCase_       ,  return_tensors='''np'''       ,  truncation=UpperCamelCase_       ,  max_length=512       ,  padding=UpperCamelCase_				)
							UpperCamelCase__  :Any				   =					model.generate(**UpperCamelCase_       ,  num_beams=2				).sequences
							UpperCamelCase__  :List[Any]				   =					tokenizer.batch_decode(UpperCamelCase_       ,  skip_special_tokens=UpperCamelCase_				)
							assert tgt_text == decoded



'''simple docstring'''
import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')


def      a (     __a  )    ->      List[str]:



					'''simple docstring'''






					UpperCamelCase__  :int				   =					test_file.split(os.path.sep  )
					if components[0:2] != ["tests", "models"]:
										raise ValueError(
										    '''`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '''
										    f'''{test_file} instead.'''  )
					UpperCamelCase__  :List[Any]				   =					components[-1]
					if not test_fn.endswith('''py'''  ):
										raise ValueError(f'''`test_file` should be a python file. Got {test_fn} instead.'''  )
					if not test_fn.startswith('''test_modeling_'''  ):
										raise ValueError(
										    f'''`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead.'''  )

					UpperCamelCase__  :Optional[Any]				   =					components[:-1] + [test_fn.replace('''.py'''					,   ''''''  )]
					UpperCamelCase__  :str				   =					'''.'''.join(__a  )

					return test_module_path


def      a (     __a  )    ->      Tuple:



					'''simple docstring'''






					UpperCamelCase__  :Dict				   =					get_module_path(__a  )
					UpperCamelCase__  :List[str]				   =					importlib.import_module(__a  )

					return test_module


def      a (     __a  )    ->      int:



					'''simple docstring'''






					UpperCamelCase__  :Dict				   =					[]
					UpperCamelCase__  :Optional[Any]				   =					get_test_module(__a  )
					for attr in dir(__a  ):
										if attr.endswith('''ModelTester'''  ):
															tester_classes.append(getattr(__a					,   __a  )  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      List[Any]:



					'''simple docstring'''






					UpperCamelCase__  :List[Any]				   =					[]
					UpperCamelCase__  :Dict				   =					get_test_module(__a  )
					for attr in dir(__a  ):
										UpperCamelCase__  :Dict				   =					getattr(__a					,   __a  )
										# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
										# `all_model_classes` is not empty (which also excludes other special classes).
										UpperCamelCase__  :Optional[int]				   =					getattr(__a					,   '''all_model_classes'''					,   []  )
										if len(__a  ) > 0:
															test_classes.append(__a  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      Union[str, Any]:



					'''simple docstring'''






					UpperCamelCase__  :int				   =					get_test_classes(__a  )
					UpperCamelCase__  :Any				   =					set()
					for test_class in test_classes:
										model_classes.update(test_class.all_model_classes  )

					# sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      Dict:



					'''simple docstring'''






					UpperCamelCase__  :Optional[Any]				   =					test_class()
					if hasattr(__a					,   '''setUp'''  ):
										test.setUp()

					UpperCamelCase__  :Union[str, Any]				   =					None
					if hasattr(__a					,   '''model_tester'''  ):
										# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
										if test.model_tester is not None:
															UpperCamelCase__  :List[str]				   =					test.model_tester.__class__

					return model_tester


def      a (     __a					,   __a  )    ->      Any:



					'''simple docstring'''






					UpperCamelCase__  :str				   =					get_test_classes(__a  )

					UpperCamelCase__  :List[str]				   =					[]
					for test_class in test_classes:
										if model_class in test_class.all_model_classes:
															target_test_classes.append(__a  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a					,   __a  )    ->      Union[str, Any]:



					'''simple docstring'''






					UpperCamelCase__  :Optional[int]				   =					get_test_classes_for_model(__a					,   __a  )

					UpperCamelCase__  :List[str]				   =					[]
					for test_class in test_classes:
										UpperCamelCase__  :int				   =					get_model_tester_from_test_class(__a  )
										if tester_class is not None:
															tester_classes.append(__a  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      int:



					'''simple docstring'''






					UpperCamelCase__  :Any				   =					get_test_classes(__a  )
					UpperCamelCase__  :Dict				   =					{test_class: get_model_tester_from_test_class(__a  ) for test_class in test_classes}
					return test_tester_mapping


def      a (     __a  )    ->      List[str]:



					'''simple docstring'''






					UpperCamelCase__  :Any				   =					get_model_classes(__a  )
					UpperCamelCase__  :Tuple				   =					{
					    model_class: get_test_classes_for_model(__a					,   __a  ) for model_class in model_classes
					}
					return model_test_mapping


def      a (     __a  )    ->      Tuple:



					'''simple docstring'''






					UpperCamelCase__  :List[str]				   =					get_model_classes(__a  )
					UpperCamelCase__  :Union[str, Any]				   =					{
					    model_class: get_tester_classes_for_model(__a					,   __a  ) for model_class in model_classes
					}
					return model_to_tester_mapping







def      a (     __a  )    ->      List[Any]:



					'''simple docstring'''






					if isinstance(__a					,   __a  ):
										return o
					elif isinstance(__a					,   __a  ):
										return o.__name__
					elif isinstance(__a					,   (list, tuple)  ):
										return [to_json(__a  ) for x in o]
					elif isinstance(__a					,   __a  ):
										return {to_json(__a  ): to_json(__a  ) for k, v in o.items()}
					else:
										return o