





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
							UpperCAmelCase__  :     Tuple   			= '''platform'''
							import jax
							import jax.numpy as jnp
							import numpy as np

							from transformers import FlaxPegasusForConditionalGeneration, FlaxPegasusModel

@require_flax
class  __A       :
				__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				,	):
								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 _snake_case    (						self							):
								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(UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							)
								return config, inputs_dict


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							):
								lowerCamelCase			=20
								lowerCamelCase			=model_class_name(UpperCAmelCase_							)

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

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

								lowerCamelCase			=model.init_cache(decoder_input_ids.shape[0]				,	UpperCAmelCase_				,	UpperCAmelCase_							)
								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]				,	UpperCAmelCase_				,	decoder_attention_mask=UpperCAmelCase_				,	past_key_values=UpperCAmelCase_				,	decoder_position_ids=UpperCAmelCase_				,	)

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

								lowerCamelCase			=model.decode(UpperCAmelCase_				,	UpperCAmelCase_							)

								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 _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							):
								lowerCamelCase			=20
								lowerCamelCase			=model_class_name(UpperCAmelCase_							)

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

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

								lowerCamelCase			=model.decode(UpperCAmelCase_				,	UpperCAmelCase_				,	decoder_attention_mask=UpperCAmelCase_							)

								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   (  _UpperCAmelCase     , _UpperCAmelCase     , _UpperCAmelCase     , _UpperCAmelCase=None     , _UpperCAmelCase=None     , )  ->					List[str]:





				if attention_mask is None:
								lowerCamelCase			=np.not_equal(lowercase__     , 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  __A       (  __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 _snake_case    (						self							):
								lowerCamelCase			=FlaxPegasusModelTester(self							)
								lowerCamelCase			=ConfigTester(self				,	config_class=UpperCAmelCase_							)


				def _snake_case    (						self							):
								self.config_tester.run_common_tests()


				def _snake_case    (						self							):
								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(UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							)


				def _snake_case    (						self							):
								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(UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							)


				def _snake_case    (						self							):
								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(UpperCAmelCase_				,	UpperCAmelCase_							)
																lowerCamelCase			=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"""							):
																				lowerCamelCase			=encode_jitted(**UpperCAmelCase_							).to_tuple()

																with self.subTest("""JIT Disabled"""							):
																				with jax.disable_jit():
																								lowerCamelCase			=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 _snake_case    (						self							):
								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(UpperCAmelCase_							)
																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(UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							):
																				return model.decode(
																				    decoder_input_ids=UpperCAmelCase_				,	decoder_attention_mask=UpperCAmelCase_				,	encoder_outputs=UpperCAmelCase_				,	)

																with self.subTest("""JIT Enabled"""							):
																				lowerCamelCase			=decode_jitted(**UpperCAmelCase_							).to_tuple()

																with self.subTest("""JIT Disabled"""							):
																				with jax.disable_jit():
																								lowerCamelCase			=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 _snake_case    (						self							):
								for model_class_name in self.all_model_classes:
												lowerCamelCase			=model_class_name.from_pretrained("""google/pegasus-large"""				,	from_pt=UpperCAmelCase_							)
												lowerCamelCase			=np.ones((1, 1)							)
												lowerCamelCase			=model(UpperCAmelCase_							)
												self.assertIsNotNone(UpperCAmelCase_							)


				@slow
				def _snake_case    (						self							):
								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(UpperCAmelCase_				,	return_tensors="""np"""				,	truncation=UpperCAmelCase_				,	max_length=512				,	padding=UpperCAmelCase_							)
								lowerCamelCase			=model.generate(**UpperCAmelCase_				,	num_beams=2							).sequences
								lowerCamelCase			=tokenizer.batch_decode(UpperCAmelCase_				,	skip_special_tokens=UpperCAmelCase_							)
								assert tgt_text == decoded












import inspect
import unittest

class  __A       (  unittest.TestCase      ):


				def _snake_case    (						self							):
								try:
												import diffusers  # noqa: F401
								except ImportError:
												assert False


				def _snake_case    (						self							):
								import diffusers
								from diffusers.dependency_versions_table import deps

								lowerCamelCase			=inspect.getmembers(UpperCAmelCase_				,	inspect.isclass							)

								for cls_name, cls_module in all_classes:
												if "dummy_" in cls_module.__module__:
																for backend in cls_module._backends:
																				if backend == "k_diffusion":
																								lowerCamelCase			="""k-diffusion"""
																				elif backend == "invisible_watermark":
																								lowerCamelCase			="""invisible-watermark"""
																				assert backend in deps, f"""{backend} is not in the deps table!"""





