

'''simple docstring'''





import unittest

import numpy as np

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

from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask


if is_flax_available():
							from transformers.models.roberta.modeling_flax_roberta import (
							    FlaxRobertaForCausalLM,
							    FlaxRobertaForMaskedLM,
							    FlaxRobertaForMultipleChoice,
							    FlaxRobertaForQuestionAnswering,
							    FlaxRobertaForSequenceClassification,
							    FlaxRobertaForTokenClassification,
							    FlaxRobertaModel,
							)





class 		__SCREAMING_SNAKE_CASE       ( unittest.TestCase			):







				def __init__(					self    :		Optional[Any]		,				UpperCAmelCase__    :		Tuple		,				UpperCAmelCase__    :		str=13		,				UpperCAmelCase__    :		Optional[Any]=7		,				UpperCAmelCase__    :		Dict=True		,				UpperCAmelCase__    :		int=True		,				UpperCAmelCase__    :		int=True		,				UpperCAmelCase__    :		Dict=True		,				UpperCAmelCase__    :		Dict=99		,				UpperCAmelCase__    :		str=32		,				UpperCAmelCase__    :		Optional[Any]=5		,				UpperCAmelCase__    :		Any=4		,				UpperCAmelCase__    :		List[Any]=37		,				UpperCAmelCase__    :		str="gelu"		,				UpperCAmelCase__    :		Dict=0.1		,				UpperCAmelCase__    :		List[Any]=0.1		,				UpperCAmelCase__    :		Optional[Any]=512		,				UpperCAmelCase__    :		Any=16		,				UpperCAmelCase__    :		str=2		,				UpperCAmelCase__    :		Tuple=0.02		,				UpperCAmelCase__    :		int=4		,				):
										'''simple docstring'''
										lowercase   :       int								=parent
										lowercase   :       List[str]								=batch_size
										lowercase   :       str								=seq_length
										lowercase   :       Optional[Any]								=is_training
										lowercase   :       Union[str, Any]								=use_attention_mask
										lowercase   :       Optional[Any]								=use_token_type_ids
										lowercase   :       Tuple								=use_labels
										lowercase   :       List[str]								=vocab_size
										lowercase   :       List[str]								=hidden_size
										lowercase   :       Tuple								=num_hidden_layers
										lowercase   :       Any								=num_attention_heads
										lowercase   :       List[str]								=intermediate_size
										lowercase   :       Optional[Any]								=hidden_act
										lowercase   :       Dict								=hidden_dropout_prob
										lowercase   :       List[Any]								=attention_probs_dropout_prob
										lowercase   :       Optional[Any]								=max_position_embeddings
										lowercase   :       Tuple								=type_vocab_size
										lowercase   :       Optional[int]								=type_sequence_label_size
										lowercase   :       Optional[Any]								=initializer_range
										lowercase   :       Optional[int]								=num_choices







				def    lowerCamelCase_  (					self    :		str      ):
										'''simple docstring'''
										lowercase   :       Optional[Any]								=ids_tensor([self.batch_size, self.seq_length]		,				self.vocab_size      )

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

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

										lowercase   :       int								=RobertaConfig(
										    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=UpperCAmelCase__		,				initializer_range=self.initializer_range		,				)

										return config, input_ids, token_type_ids, attention_mask







				def    lowerCamelCase_  (					self    :		Dict      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=self.prepare_config_and_inputs()
										lowercase		,  lowercase		,  lowercase		,  lowercase   :       str								=config_and_inputs
										lowercase   :       Optional[Any]								={'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
										return config, inputs_dict







				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										lowercase   :       List[str]								=self.prepare_config_and_inputs()
										lowercase		,  lowercase		,  lowercase		,  lowercase   :       Any								=config_and_inputs

										lowercase   :       List[str]								=True
										lowercase   :       Optional[Any]								=floats_tensor([self.batch_size, self.seq_length, self.hidden_size]      )
										lowercase   :       str								=ids_tensor([self.batch_size, self.seq_length]		,				vocab_size=2      )

										return (
										    config,
										    input_ids,
										    token_type_ids,
										    encoder_hidden_states,
										    encoder_attention_mask,
										)





@require_flax
class 		__SCREAMING_SNAKE_CASE       ( lowercase__	,       unittest.TestCase			):
				lowerCamelCase_							=						True

				lowerCamelCase_							=						(
				    (
				        FlaxRobertaModel,
				        FlaxRobertaForCausalLM,
				        FlaxRobertaForMaskedLM,
				        FlaxRobertaForSequenceClassification,
				        FlaxRobertaForTokenClassification,
				        FlaxRobertaForMultipleChoice,
				        FlaxRobertaForQuestionAnswering,
				    )
				    if is_flax_available()
				    else ()
				)







				def    lowerCamelCase_  (					self    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       str								=FlaxRobertaModelTester(self      )







				@slow
				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										for model_class_name in self.all_model_classes:
																lowercase   :       Optional[int]								=model_class_name.from_pretrained('''roberta-base'''		,				from_pt=UpperCAmelCase__      )
																lowercase   :       List[Any]								=model(np.ones((1, 1)      )      )
																self.assertIsNotNone(UpperCAmelCase__      )








'''simple docstring'''





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin





class 		__SCREAMING_SNAKE_CASE       ( lowercase__	,       unittest.TestCase			):
				lowerCamelCase_							=						BioGptTokenizer
				lowerCamelCase_							=						False







				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										super().setUp()

										# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
										lowercase   :       List[str]								=[
										    '''l''',
										    '''o''',
										    '''w''',
										    '''e''',
										    '''r''',
										    '''s''',
										    '''t''',
										    '''i''',
										    '''d''',
										    '''n''',
										    '''w</w>''',
										    '''r</w>''',
										    '''t</w>''',
										    '''lo''',
										    '''low''',
										    '''er</w>''',
										    '''low</w>''',
										    '''lowest</w>''',
										    '''newer</w>''',
										    '''wider</w>''',
										    '''<unk>''',
										]
										lowercase   :       Any								=dict(zip(UpperCAmelCase__		,				range(len(UpperCAmelCase__      )      )      )      )
										lowercase   :       Union[str, Any]								=['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

										lowercase   :       Optional[int]								=os.path.join(self.tmpdirname		,				VOCAB_FILES_NAMES['''vocab_file''']      )
										lowercase   :       Union[str, Any]								=os.path.join(self.tmpdirname		,				VOCAB_FILES_NAMES['''merges_file''']      )
										with open(self.vocab_file		,				'''w'''      ) as fp:
																fp.write(json.dumps(UpperCAmelCase__      )      )
										with open(self.merges_file		,				'''w'''      ) as fp:
																fp.write('''\n'''.join(UpperCAmelCase__      )      )







				def    lowerCamelCase_  (					self    :		List[Any]		,				UpperCAmelCase__    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       Dict								='''lower newer'''
										lowercase   :       str								='''lower newer'''
										return input_text, output_text







				def    lowerCamelCase_  (					self    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=BioGptTokenizer(self.vocab_file		,				self.merges_file      )

										lowercase   :       Any								='''lower'''
										lowercase   :       int								=['''low''', '''er</w>''']
										lowercase   :       Optional[Any]								=tokenizer.tokenize(UpperCAmelCase__      )
										self.assertListEqual(UpperCAmelCase__		,				UpperCAmelCase__      )

										lowercase   :       Optional[int]								=tokens + ['''<unk>''']
										lowercase   :       Any								=[14, 15, 20]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase__      )		,				UpperCAmelCase__      )







				@slow
				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										lowercase   :       Dict								=BioGptTokenizer.from_pretrained('''microsoft/biogpt'''      )

										lowercase   :       List[str]								=tokenizer.encode('''sequence builders'''		,				add_special_tokens=UpperCAmelCase__      )
										lowercase   :       Optional[int]								=tokenizer.encode('''multi-sequence build'''		,				add_special_tokens=UpperCAmelCase__      )

										lowercase   :       str								=tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__      )
										lowercase   :       Optional[Any]								=tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__		,				UpperCAmelCase__      )

										self.assertTrue(encoded_sentence == [2] + text      )
										self.assertTrue(encoded_pair == [2] + text + [2] + text_a      )





