
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    _snake_case (						unittest.TestCase				):


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_=13       ,	SCREAMING_SNAKE_CASE_=7       ,	SCREAMING_SNAKE_CASE_=True       ,	SCREAMING_SNAKE_CASE_=True       ,	SCREAMING_SNAKE_CASE_=True       ,	SCREAMING_SNAKE_CASE_=True       ,	SCREAMING_SNAKE_CASE_=99       ,	SCREAMING_SNAKE_CASE_=32       ,	SCREAMING_SNAKE_CASE_=5       ,	SCREAMING_SNAKE_CASE_=4       ,	SCREAMING_SNAKE_CASE_=37       ,	SCREAMING_SNAKE_CASE_="gelu"       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=5_12       ,	SCREAMING_SNAKE_CASE_=16       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=0.0_2       ,	SCREAMING_SNAKE_CASE_=4       ,	):


   '''simple docstring'''




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


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: Dict     		=   ids_tensor([self.batch_size, self.seq_length]       ,	self.vocab_size)

   lowercase__	: Tuple     		=   None
   if self.use_attention_mask:
     lowercase__	: str     		=   random_attention_mask([self.batch_size, self.seq_length])

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

   lowercase__	: 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   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: Union[str, Any]     		=   self.prepare_config_and_inputs()
   lowercase__		,     lowercase__		,     lowercase__		,     lowercase__	: Tuple     		=   config_and_inputs
   lowercase__	: Optional[Any]     		=   {"""input_ids""": input_ids, """token_type_ids""": token_type_ids, """attention_mask""": attention_mask}
   return config, inputs_dict



@require_flax
class    _snake_case (						UpperCAmelCase_	,    unittest.TestCase				):
 __lowerCAmelCase	:  Union[str, Any]	   =      True

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


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: Dict     		=   FlaxRoFormerModelTester(self)



 @slow
 def   lowercase__  (       self):


   '''simple docstring'''




   for model_class_name in self.all_model_classes:
     lowercase__	: Optional[Any]     		=   model_class_name.from_pretrained("""junnyu/roformer_chinese_small"""       ,	from_pt=SCREAMING_SNAKE_CASE_)
     lowercase__	: str     		=   model(np.ones((1, 1)))
     self.assertIsNotNone(SCREAMING_SNAKE_CASE_)



@require_flax
class    _snake_case (						unittest.TestCase				):


 @slow
 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: List[str]     		=   FlaxRoFormerForMaskedLM.from_pretrained("""junnyu/roformer_chinese_base""")
   lowercase__	: str     		=   jnp.array([[0, 1, 2, 3, 4, 5]])
   lowercase__	: str     		=   model(SCREAMING_SNAKE_CASE_)[0]

   lowercase__	: Optional[Any]     		=   5_00_00

   lowercase__	: List[str]     		=   (1, 6, vocab_size)
   self.assertEqual(output.shape       ,	SCREAMING_SNAKE_CASE_)

   lowercase__	: List[str]     		=   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))








# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse

from ...utils.dataclasses import (
    ComputeEnvironment,
    DistributedType,
    DynamoBackend,
    PrecisionType,
    SageMakerDistributedType,
)
from ..menu import BulletMenu


lowerCamelCase__     :		Optional[int]        = [
    """EAGER""",
    """AOT_EAGER""",
    """INDUCTOR""",
    """NVFUSER""",
    """AOT_NVFUSER""",
    """AOT_CUDAGRAPHS""",
    """OFI""",
    """FX2TRT""",
    """ONNXRT""",
    """IPEX""",
]

def 		UpperCamelCase						(   lowercase_			,			lowercase_=None			,			lowercase_=None			,			lowercase_=None )		->						Optional[Any]:


  '''simple docstring'''






  lowercase__	: List[Any]     		=   True
  while ask_again:
    lowercase__	: Tuple     		=   input(lowercase_ )
    try:
      if default is not None and len(lowercase_ ) == 0:
        return default
      return convert_value(lowercase_ ) if convert_value is not None else result
    except Exception:
      if error_message is not None:
        print(lowercase_ )

def 		UpperCamelCase						(   lowercase_			,			lowercase_=[]			,			lowercase_=None			,			lowercase_=0 )		->						Union[str, Any]:


  '''simple docstring'''






  lowercase__	: List[Any]     		=   BulletMenu(lowercase_			,			lowercase_ )
  lowercase__	: Any     		=   menu.run(default_choice=lowercase_ )
  return convert_value(lowercase_ ) if convert_value is not None else result

def 		UpperCamelCase						(   lowercase_ )		->						str:


  '''simple docstring'''






  lowercase__	: Union[str, Any]     		=   int(lowercase_ )
  return ComputeEnvironment(["""LOCAL_MACHINE""", """AMAZON_SAGEMAKER"""][value] )

def 		UpperCamelCase						(   lowercase_ )		->						Optional[int]:


  '''simple docstring'''






  lowercase__	: List[str]     		=   int(lowercase_ )
  return DistributedType(["""NO""", """MULTI_CPU""", """MULTI_XPU""", """MULTI_GPU""", """MULTI_NPU""", """TPU"""][value] )

def 		UpperCamelCase						(   lowercase_ )		->						str:


  '''simple docstring'''






  lowercase__	: str     		=   int(lowercase_ )
  return DynamoBackend(DYNAMO_BACKENDS[value] ).value

def 		UpperCamelCase						(   lowercase_ )		->						Union[str, Any]:


  '''simple docstring'''






  lowercase__	: List[Any]     		=   int(lowercase_ )
  return PrecisionType(["""no""", """fp16""", """bf16""", """fp8"""][value] )

def 		UpperCamelCase						(   lowercase_ )		->						Optional[int]:


  '''simple docstring'''






  lowercase__	: List[Any]     		=   int(lowercase_ )
  return SageMakerDistributedType(["""NO""", """DATA_PARALLEL""", """MODEL_PARALLEL"""][value] )

def 		UpperCamelCase						(   lowercase_ )		->						Optional[int]:


  '''simple docstring'''






  return {"yes": True, "no": False}[value.lower()]



class    _snake_case (						argparse.RawDescriptionHelpFormatter				):


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__	: int     		=   super()._format_usage(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)
   lowercase__	: Optional[Any]     		=   usage.replace("""<command> [<args>] """       ,	"""""")
   return usage






