



"""simple docstring"""

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     lowerCAmelCase__						(	unittest.TestCase ):


	'''simple docstring'''







	def __init__(      self				:       Tuple     ,       _SCREAMING_SNAKE_CASE				:       List[str]     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]=13     ,       _SCREAMING_SNAKE_CASE				:       List[str]=7     ,       _SCREAMING_SNAKE_CASE				:       Dict=True     ,       _SCREAMING_SNAKE_CASE				:       int=True     ,       _SCREAMING_SNAKE_CASE				:       Optional[Any]=True     ,       _SCREAMING_SNAKE_CASE				:       str=True     ,       _SCREAMING_SNAKE_CASE				:       Any=99     ,       _SCREAMING_SNAKE_CASE				:       Tuple=32     ,       _SCREAMING_SNAKE_CASE				:       Tuple=5     ,       _SCREAMING_SNAKE_CASE				:       Optional[Any]=4     ,       _SCREAMING_SNAKE_CASE				:       List[str]=37     ,       _SCREAMING_SNAKE_CASE				:       Dict="gelu"     ,       _SCREAMING_SNAKE_CASE				:       Dict=0.1     ,       _SCREAMING_SNAKE_CASE				:       Any=0.1     ,       _SCREAMING_SNAKE_CASE				:       Optional[int]=512     ,       _SCREAMING_SNAKE_CASE				:       Tuple=16     ,       _SCREAMING_SNAKE_CASE				:       Optional[int]=2     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]=0.0_2     ,       _SCREAMING_SNAKE_CASE				:       int=4     ,       )						->	Tuple:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							List[str]							=     parent
					SCREAMING_SNAKE_CASE						:							List[str]							=     batch_size
					SCREAMING_SNAKE_CASE						:							Any							=     seq_length
					SCREAMING_SNAKE_CASE						:							List[Any]							=     is_training
					SCREAMING_SNAKE_CASE						:							Any							=     use_attention_mask
					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     use_token_type_ids
					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     use_labels
					SCREAMING_SNAKE_CASE						:							List[str]							=     vocab_size
					SCREAMING_SNAKE_CASE						:							str							=     hidden_size
					SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     num_hidden_layers
					SCREAMING_SNAKE_CASE						:							str							=     num_attention_heads
					SCREAMING_SNAKE_CASE						:							Any							=     intermediate_size
					SCREAMING_SNAKE_CASE						:							Dict							=     hidden_act
					SCREAMING_SNAKE_CASE						:							Any							=     hidden_dropout_prob
					SCREAMING_SNAKE_CASE						:							List[Any]							=     attention_probs_dropout_prob
					SCREAMING_SNAKE_CASE						:							str							=     max_position_embeddings
					SCREAMING_SNAKE_CASE						:							List[Any]							=     type_vocab_size
					SCREAMING_SNAKE_CASE						:							int							=     type_sequence_label_size
					SCREAMING_SNAKE_CASE						:							Tuple							=     initializer_range
					SCREAMING_SNAKE_CASE						:							int							=     num_choices





	def 			_lowerCAmelCase     (      self				:       Tuple    )						->	Optional[Any]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							Any							=     ids_tensor([self.batch_size, self.seq_length]     ,       self.vocab_size    )

					SCREAMING_SNAKE_CASE						:							str							=     None
					if self.use_attention_mask:
									SCREAMING_SNAKE_CASE						:							List[Any]							=     random_attention_mask([self.batch_size, self.seq_length]    )

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

					SCREAMING_SNAKE_CASE						:							Dict							=     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=_SCREAMING_SNAKE_CASE     ,       initializer_range=self.initializer_range     ,       )

					return config, input_ids, token_type_ids, attention_mask







	def 			_lowerCAmelCase     (      self				:       Dict    )						->	Dict:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							List[Any]							=     self.prepare_config_and_inputs()
					SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						:							Any							=     config_and_inputs
					SCREAMING_SNAKE_CASE						:							Tuple							=     {'input_ids': input_ids, 'token_type_ids': token_type_ids, 'attention_mask': attention_mask}
					return config, inputs_dict




@require_flax
class     lowerCAmelCase__						(	_lowerCamelCase							,							unittest.TestCase ):


	'''simple docstring'''







	_SCREAMING_SNAKE_CASE	:		List[Any]  						= True

	_SCREAMING_SNAKE_CASE	:		Optional[Any]  						= (
	    (
	        FlaxRoFormerModel,
	        FlaxRoFormerForMaskedLM,
	        FlaxRoFormerForSequenceClassification,
	        FlaxRoFormerForTokenClassification,
	        FlaxRoFormerForMultipleChoice,
	        FlaxRoFormerForQuestionAnswering,
	    )
	    if is_flax_available()
	    else ()
	)





	def 			_lowerCAmelCase     (      self				:       Dict    )						->	Any:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							Any							=     FlaxRoFormerModelTester(self    )







	@slow
	def 			_lowerCAmelCase     (      self				:       Optional[Any]    )						->	Optional[int]:





					"""simple docstring"""


					for model_class_name in self.all_model_classes:
									SCREAMING_SNAKE_CASE						:							Any							=     model_class_name.from_pretrained('junnyu/roformer_chinese_small'     ,       from_pt=_SCREAMING_SNAKE_CASE    )
									SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     model(np.ones((1, 1)    )    )
									self.assertIsNotNone(_SCREAMING_SNAKE_CASE    )




@require_flax
class     lowerCAmelCase__						(	unittest.TestCase ):


	'''simple docstring'''







	@slow
	def 			_lowerCAmelCase     (      self				:       Optional[Any]    )						->	str:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							Optional[int]							=     FlaxRoFormerForMaskedLM.from_pretrained('junnyu/roformer_chinese_base'    )
					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     jnp.array([[0, 1, 2, 3, 4, 5]]    )
					SCREAMING_SNAKE_CASE						:							Tuple							=     model(_SCREAMING_SNAKE_CASE    )[0]

					SCREAMING_SNAKE_CASE						:							List[str]							=     50_000

					SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     (1, 6, vocab_size)
					self.assertEqual(output.shape     ,       _SCREAMING_SNAKE_CASE    )

					SCREAMING_SNAKE_CASE						:							Optional[int]							=     jnp.array(
					    [[[-0.1_2_0_5, -1.0_2_6_5, 0.2_9_2_2], [-1.5_1_3_4, 0.1_9_7_4, 0.1_5_1_9], [-5.0_1_3_5, -3.9_0_0_3, -0.8_4_0_4]]]    )

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










"""simple docstring"""

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A_						:    Any				=      logging.get_logger(__name__)

A_						:    Optional[int]				=      {
    'facebook/xmod-base': 'https://huggingface.co/facebook/xmod-base/resolve/main/config.json',
    'facebook/xmod-large-prenorm': 'https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json',
    'facebook/xmod-base-13-125k': 'https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json',
    'facebook/xmod-base-30-125k': 'https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json',
    'facebook/xmod-base-30-195k': 'https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json',
    'facebook/xmod-base-60-125k': 'https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json',
    'facebook/xmod-base-60-265k': 'https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json',
    'facebook/xmod-base-75-125k': 'https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json',
    'facebook/xmod-base-75-269k': 'https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json',
}
class     lowerCAmelCase__						(	_lowerCamelCase ):


	'''simple docstring'''







	_SCREAMING_SNAKE_CASE	:		int  						= '''xmod'''





	def __init__(      self				:       Union[str, Any]     ,       _SCREAMING_SNAKE_CASE				:       Tuple=30_522     ,       _SCREAMING_SNAKE_CASE				:       Tuple=768     ,       _SCREAMING_SNAKE_CASE				:       Optional[int]=12     ,       _SCREAMING_SNAKE_CASE				:       List[str]=12     ,       _SCREAMING_SNAKE_CASE				:       Optional[Any]=3_072     ,       _SCREAMING_SNAKE_CASE				:       Any="gelu"     ,       _SCREAMING_SNAKE_CASE				:       List[Any]=0.1     ,       _SCREAMING_SNAKE_CASE				:       Dict=0.1     ,       _SCREAMING_SNAKE_CASE				:       str=512     ,       _SCREAMING_SNAKE_CASE				:       Tuple=2     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]=0.0_2     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]=1E-1_2     ,       _SCREAMING_SNAKE_CASE				:       List[str]=1     ,       _SCREAMING_SNAKE_CASE				:       Optional[Any]=0     ,       _SCREAMING_SNAKE_CASE				:       Optional[Any]=2     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]="absolute"     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]=True     ,       _SCREAMING_SNAKE_CASE				:       Optional[Any]=None     ,       _SCREAMING_SNAKE_CASE				:       str=False     ,       _SCREAMING_SNAKE_CASE				:       Dict=2     ,       _SCREAMING_SNAKE_CASE				:       str=False     ,       _SCREAMING_SNAKE_CASE				:       int=True     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]=True     ,       _SCREAMING_SNAKE_CASE				:       Tuple=("en_XX",)     ,       _SCREAMING_SNAKE_CASE				:       Optional[int]=None     ,       **_SCREAMING_SNAKE_CASE				:       List[Any]     ,       )						->	List[str]:





					"""simple docstring"""


					super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE     ,       bos_token_id=_SCREAMING_SNAKE_CASE     ,       eos_token_id=_SCREAMING_SNAKE_CASE     ,       **_SCREAMING_SNAKE_CASE    )

					SCREAMING_SNAKE_CASE						:							Any							=     vocab_size
					SCREAMING_SNAKE_CASE						:							Any							=     hidden_size
					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     num_hidden_layers
					SCREAMING_SNAKE_CASE						:							str							=     num_attention_heads
					SCREAMING_SNAKE_CASE						:							List[Any]							=     hidden_act
					SCREAMING_SNAKE_CASE						:							Any							=     intermediate_size
					SCREAMING_SNAKE_CASE						:							Any							=     hidden_dropout_prob
					SCREAMING_SNAKE_CASE						:							str							=     attention_probs_dropout_prob
					SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     max_position_embeddings
					SCREAMING_SNAKE_CASE						:							str							=     type_vocab_size
					SCREAMING_SNAKE_CASE						:							List[str]							=     initializer_range
					SCREAMING_SNAKE_CASE						:							Optional[int]							=     layer_norm_eps
					SCREAMING_SNAKE_CASE						:							Tuple							=     position_embedding_type
					SCREAMING_SNAKE_CASE						:							int							=     use_cache
					SCREAMING_SNAKE_CASE						:							Optional[int]							=     classifier_dropout
					SCREAMING_SNAKE_CASE						:							List[Any]							=     pre_norm
					SCREAMING_SNAKE_CASE						:							int							=     adapter_reduction_factor
					SCREAMING_SNAKE_CASE						:							List[Any]							=     adapter_layer_norm
					SCREAMING_SNAKE_CASE						:							Any							=     adapter_reuse_layer_norm
					SCREAMING_SNAKE_CASE						:							Any							=     ln_before_adapter
					SCREAMING_SNAKE_CASE						:							Tuple							=     list(_SCREAMING_SNAKE_CASE    )
					SCREAMING_SNAKE_CASE						:							List[Any]							=     default_language




class     lowerCAmelCase__						(	_lowerCamelCase ):


	'''simple docstring'''







	@property
	def 			_lowerCAmelCase     (      self				:       Union[str, Any]    )						->	Mapping[str, Mapping[int, str]]:





					"""simple docstring"""


					if self.task == "multiple-choice":
									SCREAMING_SNAKE_CASE						:							Optional[int]							=     {0: 'batch', 1: 'choice', 2: 'sequence'}
					else:
									SCREAMING_SNAKE_CASE						:							List[str]							=     {0: 'batch', 1: 'sequence'}
					return OrderedDict(
					    [
					        ('input_ids', dynamic_axis),
					        ('attention_mask', dynamic_axis),
					    ]    )





