






"""simple docstring"""




from __future__ import annotations

import unittest

from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow


if is_tf_available():
 from transformers import (
     AutoConfig,
     BertConfig,
     GPTaConfig,
     TaConfig,
     TFAutoModel,
     TFAutoModelForCausalLM,
     TFAutoModelForMaskedLM,
     TFAutoModelForPreTraining,
     TFAutoModelForQuestionAnswering,
     TFAutoModelForSeqaSeqLM,
     TFAutoModelForSequenceClassification,
     TFAutoModelWithLMHead,
     TFBertForMaskedLM,
     TFBertForPreTraining,
     TFBertForQuestionAnswering,
     TFBertForSequenceClassification,
     TFBertModel,
     TFGPTaLMHeadModel,
     TFRobertaForMaskedLM,
     TFTaForConditionalGeneration,
 )
 from transformers.models.bert.modeling_tf_bert import TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST
 from transformers.models.gpta.modeling_tf_gpta import TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST
 from transformers.models.ta.modeling_tf_ta import TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST

if is_torch_available():
 from transformers import (
     AutoModel,
     AutoModelForCausalLM,
     AutoModelForMaskedLM,
     AutoModelForPreTraining,
     AutoModelForQuestionAnswering,
     AutoModelForSeqaSeqLM,
     AutoModelForSequenceClassification,
     AutoModelWithLMHead,
     BertForMaskedLM,
     BertForPreTraining,
     BertForQuestionAnswering,
     BertForSequenceClassification,
     BertModel,
     GPTaLMHeadModel,
     RobertaForMaskedLM,
     TaForConditionalGeneration,
 )






@is_pt_tf_cross_test
class        UpperCamelCase			(	unittest.TestCase      ):


 @slow
 def _lowercase	(     self		:						str							)					->       Any:
   # for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
   for model_name in ["bert-base-uncased"]:
     _a  :       Optional[Any]             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       Optional[int]             =	TFAutoModel.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       Any             =	AutoModel.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 @slow
 def _lowercase	(     self		:						Optional[int]							)					->       Dict:
   # for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
   for model_name in ["bert-base-uncased"]:
     _a  :       Optional[int]             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       List[str]             =	TFAutoModelForPreTraining.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       List[str]             =	AutoModelForPreTraining.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 @slow
 def _lowercase	(     self		:						int							)					->       List[str]:
   for model_name in TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _a  :       Union[str, Any]             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       Union[str, Any]             =	TFAutoModelForCausalLM.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     _a      ,  _a  :       Any             =	TFAutoModelForCausalLM.from_pretrained(
         UpperCAmelCase__							,						output_loading_info=UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       List[str]             =	AutoModelForCausalLM.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     _a      ,  _a  :       Any             =	AutoModelForCausalLM.from_pretrained(
         UpperCAmelCase__							,						output_loading_info=UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 @slow
 def _lowercase	(     self		:						Any							)					->       List[str]:
   for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _a  :       Tuple             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       Tuple             =	TFAutoModelWithLMHead.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       str             =	AutoModelWithLMHead.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 @slow
 def _lowercase	(     self		:						int							)					->       Any:
   for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _a  :       str             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       List[Any]             =	TFAutoModelForMaskedLM.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     _a      ,  _a  :       Any             =	TFAutoModelForMaskedLM.from_pretrained(
         UpperCAmelCase__							,						output_loading_info=UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       List[Any]             =	AutoModelForMaskedLM.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     _a      ,  _a  :       Any             =	AutoModelForMaskedLM.from_pretrained(
         UpperCAmelCase__							,						output_loading_info=UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 @slow
 def _lowercase	(     self		:						Optional[int]							)					->       str:
   for model_name in TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _a  :       Any             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       Tuple             =	TFAutoModelForSeqaSeqLM.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     _a      ,  _a  :       Optional[Any]             =	TFAutoModelForSeqaSeqLM.from_pretrained(
         UpperCAmelCase__							,						output_loading_info=UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       str             =	AutoModelForSeqaSeqLM.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     _a      ,  _a  :       int             =	AutoModelForSeqaSeqLM.from_pretrained(
         UpperCAmelCase__							,						output_loading_info=UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 @slow
 def _lowercase	(     self		:						int							)					->       Tuple:
   # for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
   for model_name in ["bert-base-uncased"]:
     _a  :       str             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       Optional[Any]             =	TFAutoModelForSequenceClassification.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       List[Any]             =	AutoModelForSequenceClassification.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 @slow
 def _lowercase	(     self		:						Union[str, Any]							)					->       Dict:
   # for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
   for model_name in ["bert-base-uncased"]:
     _a  :       Optional[int]             =	AutoConfig.from_pretrained(UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       Union[str, Any]             =	TFAutoModelForQuestionAnswering.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)

     _a  :       List[Any]             =	AutoModelForQuestionAnswering.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
     self.assertIsNotNone(UpperCAmelCase__							)
     self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)


 def _lowercase	(     self		:						int							)					->       Optional[int]:
   _a  :       Optional[int]             =	TFAutoModelWithLMHead.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
   self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)
   self.assertEqual(model.num_parameters()							,						14410							)
   self.assertEqual(model.num_parameters(only_trainable=UpperCAmelCase__							)							,						14410							)

   _a  :       List[Any]             =	AutoModelWithLMHead.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
   self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)
   self.assertEqual(model.num_parameters()							,						14410							)
   self.assertEqual(model.num_parameters(only_trainable=UpperCAmelCase__							)							,						14410							)







 def _lowercase	(     self		:						List[Any]							)					->       Any:
   _a  :       Tuple             =	TFAutoModelWithLMHead.from_pretrained(UpperCAmelCase__							,						from_pt=UpperCAmelCase__							)
   self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)
   self.assertEqual(model.num_parameters()							,						14410							)
   self.assertEqual(model.num_parameters(only_trainable=UpperCAmelCase__							)							,						14410							)

   _a  :       str             =	AutoModelWithLMHead.from_pretrained(UpperCAmelCase__							,						from_tf=UpperCAmelCase__							)
   self.assertIsInstance(UpperCAmelCase__							,						UpperCAmelCase__							)
   self.assertEqual(model.num_parameters()							,						14410							)
   self.assertEqual(model.num_parameters(only_trainable=UpperCAmelCase__							)							,						14410							)









"""simple docstring"""




def 			lowerCAmelCase__     (     UpperCamelCase__     ,   UpperCamelCase__				):



  '''simple docstring'''

  # Check if the input is valid
  if not len(UpperCamelCase__				) == len(UpperCamelCase__				) == 3:
    raise ValueError("""Please enter a valid equation."""				)
  if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
    raise ValueError("""Both a & b of two equations can't be zero."""				)

  # Extract the coefficients
  _a      ,  _a      ,  _a  :       Any             =	equationa
  _a      ,  _a      ,  _a  :       Tuple             =	equationa

  # Calculate the determinants of the matrices
  _a  :       int             =	aa * ba - aa * ba
  _a  :       str             =	ca * ba - ca * ba
  _a  :       str             =	aa * ca - aa * ca

  # Check if the system of linear equations has a solution (using Cramer's rule)
  if determinant == 0:
    if determinant_x == determinant_y == 0:
      raise ValueError("""Infinite solutions. (Consistent system)"""				)
    else:
      raise ValueError("""No solution. (Inconsistent system)"""				)
  else:
    if determinant_x == determinant_y == 0:
      # Trivial solution (Inconsistent system)
      return (0.0, 0.0)
    else:
      _a  :       Dict             =	determinant_x / determinant
      _a  :       str             =	determinant_y / determinant
      # Non-Trivial Solution (Consistent system)
      return (x, y)

