




"""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
		a            =							"platform"
		import jax
		import jax.numpy as jnp
		import numpy as np

		from transformers import FlaxPegasusForConditionalGeneration, FlaxPegasusModel






@require_flax
class 					SCREAMING_SNAKE_CASE__    :
						_a			  =  PegasusConfig
						_a			  =  {}
						_a			  =  'gelu'


						def __init__(							self :	Tuple  ,  lowerCAmelCase :	List[str]  ,  lowerCAmelCase :	int=13  ,  lowerCAmelCase :	List[Any]=7  ,  lowerCAmelCase :	Tuple=True  ,  lowerCAmelCase :	Tuple=False  ,  lowerCAmelCase :	List[Any]=99  ,  lowerCAmelCase :	Optional[Any]=32  ,  lowerCAmelCase :	Union[str, Any]=5  ,  lowerCAmelCase :	Union[str, Any]=4  ,  lowerCAmelCase :	List[Any]=37  ,  lowerCAmelCase :	List[str]=0.1  ,  lowerCAmelCase :	List[Any]=0.1  ,  lowerCAmelCase :	Any=20  ,  lowerCAmelCase :	List[Any]=2  ,  lowerCAmelCase :	Optional[int]=1  ,  lowerCAmelCase :	Optional[Any]=0  ,  ):
										lowerCAmelCase              = parent
										lowerCAmelCase              = batch_size
										lowerCAmelCase              = seq_length
										lowerCAmelCase              = is_training
										lowerCAmelCase              = use_labels
										lowerCAmelCase              = vocab_size
										lowerCAmelCase              = hidden_size
										lowerCAmelCase              = num_hidden_layers
										lowerCAmelCase              = num_attention_heads
										lowerCAmelCase              = intermediate_size

										lowerCAmelCase              = hidden_dropout_prob
										lowerCAmelCase              = attention_probs_dropout_prob
										lowerCAmelCase              = max_position_embeddings
										lowerCAmelCase              = eos_token_id
										lowerCAmelCase              = pad_token_id
										lowerCAmelCase              = bos_token_id


						def      __lowercase       (							self :	Any    ):
										lowerCAmelCase              = ids_tensor([self.batch_size, self.seq_length - 1]  ,  self.vocab_size    ).clip(3  ,  self.vocab_size    )
										lowerCAmelCase              = np.expand_dims(np.array([self.eos_token_id] * self.batch_size    )  ,  1    )
										lowerCAmelCase              = np.concatenate([input_ids, eos_tensor]  ,  axis=1    )

										lowerCAmelCase              = ids_tensor([self.batch_size, self.seq_length]  ,  self.vocab_size    )

										lowerCAmelCase              = 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  ,  )
										lowerCAmelCase              = prepare_pegasus_inputs_dict(lowercase_  ,  lowercase_  ,  lowercase_    )
										return config, inputs_dict


						def      __lowercase       (							self :	Union[str, Any]  ,  lowerCAmelCase :	int  ,  lowerCAmelCase :	Union[str, Any]  ,  lowerCAmelCase :	int    ):
										lowerCAmelCase              = 20
										lowerCAmelCase              = model_class_name(lowercase_    )

										lowerCAmelCase              = model.encode(inputs_dict["""input_ids"""]    )

										lowerCAmelCase       ,  lowerCAmelCase              = (
										    inputs_dict["""decoder_input_ids"""],
										    inputs_dict["""decoder_attention_mask"""],
										)

										lowerCAmelCase              = model.init_cache(decoder_input_ids.shape[0]  ,  lowercase_  ,  lowercase_    )
										lowerCAmelCase              = jnp.ones((decoder_input_ids.shape[0], max_decoder_length)  ,  dtype="""i4"""    )

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

										lowerCAmelCase              = jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]  ,  dtype="""i4"""    )
										lowerCAmelCase              = model.decode(
										    decoder_input_ids[:, -1:]  ,  lowercase_  ,  decoder_attention_mask=lowercase_  ,  past_key_values=outputs_cache.past_key_values  ,  decoder_position_ids=lowercase_  ,  )

										lowerCAmelCase              = model.decode(lowercase_  ,  lowercase_    )

										lowerCAmelCase              = 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      __lowercase       (							self :	Dict  ,  lowerCAmelCase :	str  ,  lowerCAmelCase :	List[Any]  ,  lowerCAmelCase :	Dict    ):
										lowerCAmelCase              = 20
										lowerCAmelCase              = model_class_name(lowercase_    )

										lowerCAmelCase              = model.encode(inputs_dict["""input_ids"""]    )

										lowerCAmelCase       ,  lowerCAmelCase              = (
										    inputs_dict["""decoder_input_ids"""],
										    inputs_dict["""decoder_attention_mask"""],
										)

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

										lowerCAmelCase              = model.init_cache(decoder_input_ids.shape[0]  ,  lowercase_  ,  lowercase_    )
										lowerCAmelCase              = jnp.broadcast_to(
										    jnp.arange(decoder_input_ids.shape[-1] - 1    )[None, :]  ,  (decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)  ,  )

										lowerCAmelCase              = model.decode(
										    decoder_input_ids[:, :-1]  ,  lowercase_  ,  decoder_attention_mask=lowercase_  ,  past_key_values=lowercase_  ,  decoder_position_ids=lowercase_  ,  )
										lowerCAmelCase              = jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]  ,  dtype="""i4"""    )
										lowerCAmelCase              = model.decode(
										    decoder_input_ids[:, -1:]  ,  lowercase_  ,  past_key_values=outputs_cache.past_key_values  ,  decoder_attention_mask=lowercase_  ,  decoder_position_ids=lowercase_  ,  )

										lowerCAmelCase              = model.decode(lowercase_  ,  lowercase_  ,  decoder_attention_mask=lowercase_    )

										lowerCAmelCase              = 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 							lowercase    (snake_case__      :       List[str]					,				snake_case__      :       int					,				snake_case__      :       Optional[int]					,				snake_case__      :       str=None					,				snake_case__      :       Tuple=None					,				)   ->     Optional[int]:


				'''simple docstring'''






				if attention_mask is None:
								lowerCAmelCase              = np.not_equal(_lowerCamelCase					,				config.pad_token_id       ).astype(np.inta       )
				if decoder_attention_mask is None:
								lowerCAmelCase              = 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 					SCREAMING_SNAKE_CASE__    (    UpperCamelCase__  , unittest.TestCase    ):
						_a			  =  (
						    (
						        FlaxPegasusForConditionalGeneration,
						        FlaxPegasusModel,
						    )
						    if is_flax_available()
						    else ()
						)
						_a			  =  (FlaxPegasusForConditionalGeneration,) if is_flax_available() else ()
						_a			  =  True
						_a			  =  False
						_a			  =  False
						_a			  =  False


						def      __lowercase       (							self :	Union[str, Any]    ):
										lowerCAmelCase              = FlaxPegasusModelTester(self    )
										lowerCAmelCase              = ConfigTester(self  ,  config_class=lowercase_    )


						def      __lowercase       (							self :	Any    ):
										self.config_tester.run_common_tests()


						def      __lowercase       (							self :	Tuple    ):
										lowerCAmelCase       ,  lowerCAmelCase              = self.model_tester.prepare_config_and_inputs_for_common()
										for model_class in self.all_model_classes:
														self.model_tester.check_use_cache_forward(lowercase_  ,  lowercase_  ,  lowercase_    )


						def      __lowercase       (							self :	Optional[int]    ):
										lowerCAmelCase       ,  lowerCAmelCase              = 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(lowercase_  ,  lowercase_  ,  lowercase_    )


						def      __lowercase       (							self :	Union[str, Any]    ):
										lowerCAmelCase       ,  lowerCAmelCase              = self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
														with self.subTest(model_class.__name__    ):
																		lowerCAmelCase              = self._prepare_for_class(lowercase_  ,  lowercase_    )
																		lowerCAmelCase              = model_class(lowercase_    )

																		@jax.jit
																		def encode_jitted(lowerCAmelCase :	Dict  ,  lowerCAmelCase :	Any=None  ,  **lowerCAmelCase :	Any    ):
																						return model.encode(input_ids=lowercase_  ,  attention_mask=lowercase_    )

																		with self.subTest("""JIT Enabled"""    ):
																						lowerCAmelCase              = encode_jitted(**lowercase_    ).to_tuple()

																		with self.subTest("""JIT Disabled"""    ):
																						with jax.disable_jit():
																										lowerCAmelCase              = encode_jitted(**lowercase_    ).to_tuple()

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


						def      __lowercase       (							self :	Optional[Any]    ):
										lowerCAmelCase       ,  lowerCAmelCase              = self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
														with self.subTest(model_class.__name__    ):
																		lowerCAmelCase              = model_class(lowercase_    )
																		lowerCAmelCase              = model.encode(inputs_dict["""input_ids"""]  ,  inputs_dict["""attention_mask"""]    )

																		lowerCAmelCase              = {
																		    """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(lowerCAmelCase :	str  ,  lowerCAmelCase :	str  ,  lowerCAmelCase :	Optional[Any]    ):
																						return model.decode(
																						    decoder_input_ids=lowercase_  ,  decoder_attention_mask=lowercase_  ,  encoder_outputs=lowercase_  ,  )

																		with self.subTest("""JIT Enabled"""    ):
																						lowerCAmelCase              = decode_jitted(**lowercase_    ).to_tuple()

																		with self.subTest("""JIT Disabled"""    ):
																						with jax.disable_jit():
																										lowerCAmelCase              = decode_jitted(**lowercase_    ).to_tuple()

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


						@slow
						def      __lowercase       (							self :	str    ):
										for model_class_name in self.all_model_classes:
														lowerCAmelCase              = model_class_name.from_pretrained("""google/pegasus-large"""  ,  from_pt=lowercase_    )
														lowerCAmelCase              = np.ones((1, 1)    )
														lowerCAmelCase              = model(lowercase_    )
														self.assertIsNotNone(lowercase_    )




						@slow
						def      __lowercase       (							self :	Union[str, Any]    ):
										lowerCAmelCase              = FlaxPegasusForConditionalGeneration.from_pretrained("""google/pegasus-xsum"""    )
										lowerCAmelCase              = PegasusTokenizer.from_pretrained("""google/pegasus-xsum"""    )

										lowerCAmelCase              = [
										    """ 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!\" """,
										]

										lowerCAmelCase              = [
										    """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.""",
										]

										lowerCAmelCase              = tokenizer(lowercase_  ,  return_tensors="""np"""  ,  truncation=lowercase_  ,  max_length=512  ,  padding=lowercase_    )
										lowerCAmelCase              = model.generate(**lowercase_  ,  num_beams=2    ).sequences
										lowerCAmelCase              = tokenizer.batch_decode(lowercase_  ,  skip_special_tokens=lowercase_    )
										assert tgt_text == decoded












'''simple docstring'''

import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
  from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
  from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
  from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


__lowerCAmelCase							:	Dict			=DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

__lowerCAmelCase							:	List[Any]			="main"
# Default branch name
__lowerCAmelCase							:	int			="f2c752cfc5c0ab6f4bdec59acea69eefbee381c2"
# One particular commit (not the top of `main`)
__lowerCAmelCase							:	List[Any]			="aaaaaaa"
# This commit does not exist, so we should 404.

__lowerCAmelCase							:	Optional[int]			="d9e9f15bc825e4b2c9249e9578f884bbcb5e3684"
# Sha-1 of config.json on the top of `main`, for checking purposes
__lowerCAmelCase							:	Dict			="4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3"





@contextlib.contextmanager
def 						UpperCamelCase				(							):
    print("Welcome!"       )
    yield
    print("Bye!"       )





@contextlib.contextmanager
def 						UpperCamelCase				(							):
    print("Bonjour!"       )
    yield
    print("Au revoir!"       )






class    UpperCAmelCase	(       unittest.TestCase				):
 def      UpperCAmelCase_							(				self      :str							)->							List[str]:
     # If the spec is missing, importlib would not be able to import the module dynamically.
     assert transformers.__spec__ is not None
     assert importlib.util.find_spec("transformers"							) is not None






class    UpperCAmelCase	(       unittest.TestCase				):
 @unittest.mock.patch("sys.stdout"						,       new_callable=io.StringIO							)
 def      UpperCAmelCase_							(				self      :Union[str, Any]						,       lowercase_      :Union[str, Any]							)->							Any:
     with ContextManagers([]							):
         print("Transformers are awesome!"							)
     # The print statement adds a new line at the end of the output
     self.assertEqual(mock_stdout.getvalue()						,       "Transformers are awesome!\n"							)
 @unittest.mock.patch("sys.stdout"						,       new_callable=io.StringIO							)
 def      UpperCAmelCase_							(				self      :Dict						,       lowercase_      :Optional[Any]							)->							Tuple:
     with ContextManagers([context_en()]							):
         print("Transformers are awesome!"							)
     # The output should be wrapped with an English welcome and goodbye
     self.assertEqual(mock_stdout.getvalue()						,       "Welcome!\nTransformers are awesome!\nBye!\n"							)
 @unittest.mock.patch("sys.stdout"						,       new_callable=io.StringIO							)
 def      UpperCAmelCase_							(				self      :Union[str, Any]						,       lowercase_      :int							)->							Union[str, Any]:
     with ContextManagers([context_fr(), context_en()]							):
         print("Transformers are awesome!"							)
     # The output should be wrapped with an English and French welcome and goodbye
     self.assertEqual(mock_stdout.getvalue()						,       "Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n"							)
 @require_torch
 def      UpperCAmelCase_							(				self      :int							)->							Dict:
     self.assertEqual(find_labels(lowercase_							)						,       ["labels"]							)
     self.assertEqual(find_labels(lowercase_							)						,       ["labels", "next_sentence_label"]							)
     self.assertEqual(find_labels(lowercase_							)						,       ["start_positions", "end_positions"]							)






     class    UpperCAmelCase	(       UpperCamelCase__				):
      pass

     self.assertEqual(find_labels(lowercase_							)						,       ["labels"]							)
 @require_tf
 def      UpperCAmelCase_							(				self      :Union[str, Any]							)->							Union[str, Any]:
     self.assertEqual(find_labels(lowercase_							)						,       ["labels"]							)
     self.assertEqual(find_labels(lowercase_							)						,       ["labels", "next_sentence_label"]							)
     self.assertEqual(find_labels(lowercase_							)						,       ["start_positions", "end_positions"]							)






     class    UpperCAmelCase	(       UpperCamelCase__				):
      pass

     self.assertEqual(find_labels(lowercase_							)						,       ["labels"]							)



 @require_flax
 def      UpperCAmelCase_							(				self      :Dict							)->							str:
     # Flax models don't have labels
     self.assertEqual(find_labels(lowercase_							)						,       []							)
     self.assertEqual(find_labels(lowercase_							)						,       []							)
     self.assertEqual(find_labels(lowercase_							)						,       []							)






     class    UpperCAmelCase	(       UpperCamelCase__				):
      pass

     self.assertEqual(find_labels(lowercase_							)						,       []							)



