
import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
							import jax.numpy as jnp

							from transformers.models.roformer.modeling_flax_roformer import (
							    FlaxRoFormerForMaskedLM,
							    FlaxRoFormerForMultipleChoice,
							    FlaxRoFormerForQuestionAnswering,
							    FlaxRoFormerForSequenceClassification,
							    FlaxRoFormerForTokenClassification,
							    FlaxRoFormerModel,
							)







class        lowercase	(      unittest.TestCase	):




							def __init__(       self     ,A__     ,A__=1_3     ,A__=7     ,A__=True     ,A__=True     ,A__=True     ,A__=True     ,A__=9_9     ,A__=3_2     ,A__=5     ,A__=4     ,A__=3_7     ,A__="gelu"     ,A__=0.1     ,A__=0.1     ,A__=5_1_2     ,A__=1_6     ,A__=2     ,A__=0.02     ,A__=4     ,):
												lowercase					=		parent
												lowercase					=		batch_size
												lowercase					=		seq_length
												lowercase					=		is_training
												lowercase					=		use_attention_mask
												lowercase					=		use_token_type_ids
												lowercase					=		use_labels
												lowercase					=		vocab_size
												lowercase					=		hidden_size
												lowercase					=		num_hidden_layers
												lowercase					=		num_attention_heads
												lowercase					=		intermediate_size
												lowercase					=		hidden_act
												lowercase					=		hidden_dropout_prob
												lowercase					=		attention_probs_dropout_prob
												lowercase					=		max_position_embeddings
												lowercase					=		type_vocab_size
												lowercase					=		type_sequence_label_size
												lowercase					=		initializer_range
												lowercase					=		num_choices




							def 				A__   (       self):
												lowercase					=		ids_tensor([self.batch_size, self.seq_length]     ,self.vocab_size)

												lowercase					=		None
												if self.use_attention_mask:
																	lowercase					=		random_attention_mask([self.batch_size, self.seq_length])

												lowercase					=		None
												if self.use_token_type_ids:
																	lowercase					=		ids_tensor([self.batch_size, self.seq_length]     ,self.type_vocab_size)

												lowercase					=		RoFormerConfig(
												    vocab_size=self.vocab_size     ,hidden_size=self.hidden_size     ,num_hidden_layers=self.num_hidden_layers     ,num_attention_heads=self.num_attention_heads     ,intermediate_size=self.intermediate_size     ,hidden_act=self.hidden_act     ,hidden_dropout_prob=self.hidden_dropout_prob     ,attention_probs_dropout_prob=self.attention_probs_dropout_prob     ,max_position_embeddings=self.max_position_embeddings     ,type_vocab_size=self.type_vocab_size     ,is_decoder=A__     ,initializer_range=self.initializer_range     ,)

												return config, input_ids, token_type_ids, attention_mask





							def 				A__   (       self):
												lowercase					=		self.prepare_config_and_inputs()
												lowercase			,		lowercase			,		lowercase			,		lowercase					=		config_and_inputs
												lowercase					=		{'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
												return config, inputs_dict







@require_flax
class        lowercase	(      SCREAMING_SNAKE_CASE__ ,						unittest.TestCase	):
							lowercase_ : Tuple       =True

							lowercase_ : Union[str, Any]       =(
							    (
							        FlaxRoFormerModel,
							        FlaxRoFormerForMaskedLM,
							        FlaxRoFormerForSequenceClassification,
							        FlaxRoFormerForTokenClassification,
							        FlaxRoFormerForMultipleChoice,
							        FlaxRoFormerForQuestionAnswering,
							    )
							    if is_flax_available()
							    else ()
							)




							def 				A__   (       self):
												lowercase					=		FlaxRoFormerModelTester(self)





							@slow
							def 				A__   (       self):
												for model_class_name in self.all_model_classes:
																	lowercase					=		model_class_name.from_pretrained('''junnyu/roformer_chinese_small'''     ,from_pt=A__)
																	lowercase					=		model(np.ones((1, 1)))
																	self.assertIsNotNone(A__)







@require_flax
class        lowercase	(      unittest.TestCase	):




							@slow
							def 				A__   (       self):
												lowercase					=		FlaxRoFormerForMaskedLM.from_pretrained('''junnyu/roformer_chinese_base''')
												lowercase					=		jnp.array([[0, 1, 2, 3, 4, 5]])
												lowercase					=		model(A__)[0]

												lowercase					=		5_0_0_0_0

												lowercase					=		(1, 6, vocab_size)
												self.assertEqual(output.shape     ,A__)

												lowercase					=		jnp.array(
												    [[[-0.1205, -1.0265, 0.2922], [-1.5134, 0.1974, 0.1519], [-5.0135, -3.9003, -0.8404]]])

												self.assertTrue(jnp.allclose(output[:, :3, :3]     ,A__     ,atol=1E-4))






import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    "The `inpainting.py` script is outdated. Please use directly `from diffusers import"
    " StableDiffusionInpaintPipeline` instead."
)




