
from __future__ import annotations

import unittest

from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
     import tensorflow as tf

     from transformers import TFAutoModelForSeqaSeqLM, TFBlenderbotForConditionalGeneration, TFBlenderbotModel



@require_tf
class       _snake_case   :
 __lowerCAmelCase  :     Tuple        =			BlenderbotConfig
 __lowerCAmelCase  :     Optional[Any]        =			{}
 __lowerCAmelCase  :     List[Any]        =			'gelu'


 def __init__(					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_=13					,  SCREAMING_SNAKE_CASE_=7					,  SCREAMING_SNAKE_CASE_=True					,  SCREAMING_SNAKE_CASE_=False					,  SCREAMING_SNAKE_CASE_=99					,  SCREAMING_SNAKE_CASE_=32					,  SCREAMING_SNAKE_CASE_=2					,  SCREAMING_SNAKE_CASE_=4					,  SCREAMING_SNAKE_CASE_=37					,  SCREAMING_SNAKE_CASE_=0.1					,  SCREAMING_SNAKE_CASE_=0.1					,  SCREAMING_SNAKE_CASE_=20					,  SCREAMING_SNAKE_CASE_=2					,  SCREAMING_SNAKE_CASE_=1					,  SCREAMING_SNAKE_CASE_=0					,  ):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      parent
   lowercase__  :   Union[str, Any]    		=      batch_size
   lowercase__  :   str    		=      seq_length
   lowercase__  :   Tuple    		=      is_training
   lowercase__  :   Any    		=      use_labels
   lowercase__  :   Tuple    		=      vocab_size
   lowercase__  :   Dict    		=      hidden_size
   lowercase__  :   Any    		=      num_hidden_layers
   lowercase__  :   Dict    		=      num_attention_heads
   lowercase__  :   Optional[Any]    		=      intermediate_size

   lowercase__  :   str    		=      hidden_dropout_prob
   lowercase__  :   Dict    		=      attention_probs_dropout_prob
   lowercase__  :   Dict    		=      max_position_embeddings
   lowercase__  :   Optional[int]    		=      eos_token_id
   lowercase__  :   List[Any]    		=      pad_token_id
   lowercase__  :   Union[str, Any]    		=      bos_token_id


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   List[str]    		=      ids_tensor([self.batch_size, self.seq_length - 1]					,  self.vocab_size)
   lowercase__  :   Any    		=      tf.expand_dims(tf.constant([self.eos_token_id] * self.batch_size)					,  1)
   lowercase__  :   str    		=      tf.concat([input_ids, eos_tensor]					,  axis=1)

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

   lowercase__  :   Optional[Any]    		=      self.config_cls(
       vocab_size=self.vocab_size					,  d_model=self.hidden_size					,  encoder_layers=self.num_hidden_layers					,  decoder_layers=self.num_hidden_layers					,  encoder_attention_heads=self.num_attention_heads					,  decoder_attention_heads=self.num_attention_heads					,  encoder_ffn_dim=self.intermediate_size					,  decoder_ffn_dim=self.intermediate_size					,  dropout=self.hidden_dropout_prob					,  attention_dropout=self.attention_probs_dropout_prob					,  max_position_embeddings=self.max_position_embeddings					,  eos_token_ids=[2]					,  bos_token_id=self.bos_token_id					,  pad_token_id=self.pad_token_id					,  decoder_start_token_id=self.pad_token_id					,  **self.config_updates					,  )
   lowercase__  :   str    		=      prepare_blenderbot_inputs_dict(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
   return config, inputs_dict



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      TFBlenderbotModel(config=SCREAMING_SNAKE_CASE_).get_decoder()
   lowercase__  :   Dict    		=      inputs_dict["""input_ids"""]

   lowercase__  :   Optional[Any]    		=      input_ids[:1, :]
   lowercase__  :   Union[str, Any]    		=      inputs_dict["""attention_mask"""][:1, :]
   lowercase__  :   Optional[Any]    		=      inputs_dict["""head_mask"""]
   lowercase__  :   Any    		=      1

   # first forward pass
   lowercase__  :   Any    		=      model(SCREAMING_SNAKE_CASE_					,  attention_mask=SCREAMING_SNAKE_CASE_					,  head_mask=SCREAMING_SNAKE_CASE_					,  use_cache=SCREAMING_SNAKE_CASE_)

   lowercase__		,    lowercase__  :   Optional[Any]    		=      outputs.to_tuple()

   # create hypothetical next token and extent to next_input_ids
   lowercase__  :   Optional[int]    		=      ids_tensor((self.batch_size, 3)					,  config.vocab_size)
   lowercase__  :   List[str]    		=      tf.cast(ids_tensor((self.batch_size, 3)					,  2)					,  tf.inta)

   # append to next input_ids and
   lowercase__  :   Dict    		=      tf.concat([input_ids, next_tokens]					,  axis=-1)
   lowercase__  :   str    		=      tf.concat([attention_mask, next_attn_mask]					,  axis=-1)

   lowercase__  :   Optional[int]    		=      model(SCREAMING_SNAKE_CASE_					,  attention_mask=SCREAMING_SNAKE_CASE_)[0]
   lowercase__  :   List[str]    		=      model(SCREAMING_SNAKE_CASE_					,  attention_mask=SCREAMING_SNAKE_CASE_					,  past_key_values=SCREAMING_SNAKE_CASE_)[0]

   self.parent.assertEqual(next_tokens.shape[1]					,  output_from_past.shape[1])

   # select random slice
   lowercase__  :   int    		=      int(ids_tensor((1,)					,  output_from_past.shape[-1]))
   lowercase__  :   int    		=      output_from_no_past[:, -3:, random_slice_idx]
   lowercase__  :   Dict    		=      output_from_past[:, :, random_slice_idx]

   # test that outputs are equal for slice
   tf.debugging.assert_near(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  rtol=1E-3)

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


  '''simple docstring'''






  if attention_mask is None:
    lowercase__  :   int    		=      tf.cast(tf.math.not_equal(lowercase_ , config.pad_token_id   ) , tf.inta   )
  if decoder_attention_mask is None:
    lowercase__  :   List[str]    		=      tf.concat(
        [
            tf.ones(decoder_input_ids[:, :1].shape , dtype=tf.inta   ),
            tf.cast(tf.math.not_equal(decoder_input_ids[:, 1:] , config.pad_token_id   ) , tf.inta   ),
        ] , axis=-1 , )
  if head_mask is None:
    lowercase__  :   Optional[Any]    		=      tf.ones((config.encoder_layers, config.encoder_attention_heads)   )
  if decoder_head_mask is None:
    lowercase__  :   Union[str, Any]    		=      tf.ones((config.decoder_layers, config.decoder_attention_heads)   )
  if cross_attn_head_mask is None:
    lowercase__  :   List[str]    		=      tf.ones((config.decoder_layers, config.decoder_attention_heads)   )
  return {
      "input_ids": input_ids,
      "decoder_input_ids": decoder_input_ids,
      "attention_mask": attention_mask,
      "decoder_attention_mask": decoder_attention_mask,
      "head_mask": head_mask,
      "decoder_head_mask": decoder_head_mask,
      "cross_attn_head_mask": cross_attn_head_mask,
  }



@require_tf
class       _snake_case   (	UpperCAmelCase_  ,						UpperCAmelCase_  ,						unittest.TestCase							):
 __lowerCAmelCase  :     Optional[Any]        =			(TFBlenderbotForConditionalGeneration, TFBlenderbotModel) if is_tf_available() else ()
 __lowerCAmelCase  :     List[str]        =			(TFBlenderbotForConditionalGeneration,) if is_tf_available() else ()
 __lowerCAmelCase  :     str        =			(
     {
         'conversational': TFBlenderbotForConditionalGeneration,
         'feature-extraction': TFBlenderbotModel,
         'summarization': TFBlenderbotForConditionalGeneration,
         'text2text-generation': TFBlenderbotForConditionalGeneration,
         'translation': TFBlenderbotForConditionalGeneration,
     }
     if is_tf_available()
     else {}
 )
 __lowerCAmelCase  :     Optional[int]        =			True
 __lowerCAmelCase  :     List[Any]        =			False
 __lowerCAmelCase  :     str        =			False


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   int    		=      TFBlenderbotModelTester(self)
   lowercase__  :   List[str]    		=      ConfigTester(self					,  config_class=SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self):


   '''simple docstring'''




   self.config_tester.run_common_tests()



 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   int    		=      self.model_tester.prepare_config_and_inputs_for_common()
   self.model_tester.check_decoder_model_past_large_inputs(*SCREAMING_SNAKE_CASE_)



@require_tokenizers
@require_tf
class       _snake_case   (	unittest.TestCase							):
 __lowerCAmelCase  :     List[Any]        =			['My friends are cool but they eat too many carbs.']
 __lowerCAmelCase  :     Tuple        =			'facebook/blenderbot-400M-distill'


 @cached_property
 def      lowercase__     (					self):


   '''simple docstring'''




   return BlenderbotTokenizer.from_pretrained(self.model_name)


 @cached_property
 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   int    		=      TFAutoModelForSeqaSeqLM.from_pretrained(self.model_name)
   return model



 @slow
 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Dict    		=      self.tokenizer(self.src_text					,  return_tensors="""tf""")
   lowercase__  :   Optional[Any]    		=      self.model.generate(
       model_inputs.input_ids					,  )
   lowercase__  :   Dict    		=      self.tokenizer.batch_decode(generated_ids.numpy()					,  skip_special_tokens=SCREAMING_SNAKE_CASE_)[0]
   assert (
       generated_words
       == " That's unfortunate. Are they trying to lose weight or are they just trying to be healthier?"
   )








from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload



class       _snake_case   :


 def __init__(					self					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   if components is None:
     lowercase__  :   List[str]    		=      []
   lowercase__  :   Dict    		=      list(SCREAMING_SNAKE_CASE_)


 def __len__(					self):


   '''simple docstring'''




   return len(self.__components)


 def __str__(					self):


   '''simple docstring'''




   return "(" + ",".join(map(SCREAMING_SNAKE_CASE_					,  self.__components)) + ")"


 def __add__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Optional[Any]    		=      len(self)
   if size == len(SCREAMING_SNAKE_CASE_):
     lowercase__  :   List[str]    		=      [self.__components[i] + other.component(SCREAMING_SNAKE_CASE_) for i in range(SCREAMING_SNAKE_CASE_)]
     return Vector(SCREAMING_SNAKE_CASE_)
   else:
     raise Exception("""must have the same size""")


 def __sub__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      len(self)
   if size == len(SCREAMING_SNAKE_CASE_):
     lowercase__  :   Optional[Any]    		=      [self.__components[i] - other.component(SCREAMING_SNAKE_CASE_) for i in range(SCREAMING_SNAKE_CASE_)]
     return Vector(SCREAMING_SNAKE_CASE_)
   else:  # error case
     raise Exception("""must have the same size""")


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if isinstance(SCREAMING_SNAKE_CASE_					,  (float, int)):
     lowercase__  :   Optional[int]    		=      [c * other for c in self.__components]
     return Vector(SCREAMING_SNAKE_CASE_)
   elif isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_) and len(self) == len(SCREAMING_SNAKE_CASE_):
     lowercase__  :   Dict    		=      len(self)
     lowercase__  :   Optional[Any]    		=      [self.__components[i] * other.component(SCREAMING_SNAKE_CASE_) for i in range(SCREAMING_SNAKE_CASE_)]
     return sum(SCREAMING_SNAKE_CASE_)
   else:  # error case
     raise Exception("""invalid operand!""")


 def      lowercase__     (					self):


   '''simple docstring'''




   return Vector(self.__components)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_) and -len(self.__components) <= i < len(self.__components):
     return self.__components[i]
   else:
     raise Exception("""index out of range""")


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   assert -len(self.__components) <= pos < len(self.__components)
   lowercase__  :   List[Any]    		=      value


 def      lowercase__     (					self):


   '''simple docstring'''




   if len(self.__components) == 0:
     raise Exception("""Vector is empty""")
   lowercase__  :   Union[str, Any]    		=      [c**2 for c in self.__components]
   return math.sqrt(sum(SCREAMING_SNAKE_CASE_))



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


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      self * other
   lowercase__  :   Optional[Any]    		=      self.euclidean_length() * other.euclidean_length()
   if deg:
     return math.degrees(math.acos(num / den))
   else:
     return math.acos(num / den)

def 		UpperCamelCase	(      lowercase_   )		->	Vector:


  '''simple docstring'''






  assert isinstance(lowercase_ , lowercase_   )
  return Vector([0] * dimension   )

def 		UpperCamelCase	(      lowercase_ , lowercase_   )		->	Vector:


  '''simple docstring'''






  assert isinstance(lowercase_ , lowercase_   ) and (isinstance(lowercase_ , lowercase_   ))
  lowercase__  :   Union[str, Any]    		=      [0] * dimension
  lowercase__  :   Any    		=      1
  return Vector(lowercase_   )

def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	Vector:


  '''simple docstring'''






  assert (
      isinstance(lowercase_ , lowercase_   )
      and isinstance(lowercase_ , lowercase_   )
      and (isinstance(lowercase_ , (int, float)   ))
  )
  return x * scalar + y

def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	Vector:


  '''simple docstring'''






  random.seed(lowercase_   )
  lowercase__  :   int    		=      [random.randint(lowercase_ , lowercase_   ) for _ in range(lowercase_   )]
  return Vector(lowercase_   )



class       _snake_case   :


 def __init__(					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      matrix
   lowercase__  :   Any    		=      w
   lowercase__  :   Any    		=      h


 def __str__(					self):


   '''simple docstring'''




   lowercase__  :   str    		=      """"""
   for i in range(self.__height):
     ans += "|"
     for j in range(self.__width):
       if j < self.__width - 1:
         ans += str(self.__matrix[i][j]) + ","
       else:
         ans += str(self.__matrix[i][j]) + "|\n"
   return ans


 def __add__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__width == other.width() and self.__height == other.height():
     lowercase__  :   Tuple    		=      []
     for i in range(self.__height):
       lowercase__  :   Tuple    		=      [
           self.__matrix[i][j] + other.component(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
           for j in range(self.__width)
       ]
       matrix.append(SCREAMING_SNAKE_CASE_)
     return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width					,  self.__height)
   else:
     raise Exception("""matrix must have the same dimension!""")


 def __sub__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__width == other.width() and self.__height == other.height():
     lowercase__  :   Optional[int]    		=      []
     for i in range(self.__height):
       lowercase__  :   List[str]    		=      [
           self.__matrix[i][j] - other.component(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
           for j in range(self.__width)
       ]
       matrix.append(SCREAMING_SNAKE_CASE_)
     return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width					,  self.__height)
   else:
     raise Exception("""matrices must have the same dimension!""")


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):  # matrix-vector
     if len(SCREAMING_SNAKE_CASE_) == self.__width:
       lowercase__  :   List[Any]    		=      zero_vector(self.__height)
       for i in range(self.__height):
         lowercase__  :   Union[str, Any]    		=      [
             self.__matrix[i][j] * other.component(SCREAMING_SNAKE_CASE_)
             for j in range(self.__width)
         ]
         ans.change_component(SCREAMING_SNAKE_CASE_					,  sum(SCREAMING_SNAKE_CASE_))
       return ans
     else:
       raise Exception(
           """vector must have the same size as the """
           """number of columns of the matrix!""")
   elif isinstance(SCREAMING_SNAKE_CASE_					,  (int, float)):  # matrix-scalar
     lowercase__  :   Tuple    		=      [
         [self.__matrix[i][j] * other for j in range(self.__width)]
         for i in range(self.__height)
     ]
     return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width					,  self.__height)
   return None


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.__height


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.__width


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if 0 <= x < self.__height and 0 <= y < self.__width:
     return self.__matrix[x][y]
   else:
     raise Exception("""change_component: indices out of bounds""")


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


   '''simple docstring'''




   if 0 <= x < self.__height and 0 <= y < self.__width:
     lowercase__  :   Tuple    		=      value
   else:
     raise Exception("""change_component: indices out of bounds""")


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__height != self.__width:
     raise Exception("""Matrix is not square""")
   lowercase__  :   List[Any]    		=      self.__matrix[:x] + self.__matrix[x + 1 :]
   for i in range(len(SCREAMING_SNAKE_CASE_)):
     lowercase__  :   List[str]    		=      minor[i][:y] + minor[i][y + 1 :]
   return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width - 1					,  self.__height - 1).determinant()


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__height != self.__width:
     raise Exception("""Matrix is not square""")
   if 0 <= x < self.__height and 0 <= y < self.__width:
     return (-1) ** (x + y) * self.minor(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
   else:
     raise Exception("""Indices out of bounds""")



 def      lowercase__     (					self):


   '''simple docstring'''




   if self.__height != self.__width:
     raise Exception("""Matrix is not square""")
   if self.__height < 1:
     raise Exception("""Matrix has no element""")
   elif self.__height == 1:
     return self.__matrix[0][0]
   elif self.__height == 2:
     return (
         self.__matrix[0][0] * self.__matrix[1][1]
         - self.__matrix[0][1] * self.__matrix[1][0]
     )
   else:
     lowercase__  :   Optional[int]    		=      [
         self.__matrix[0][y] * self.cofactor(0					,  SCREAMING_SNAKE_CASE_) for y in range(self.__width)
     ]
     return sum(SCREAMING_SNAKE_CASE_)

def 		UpperCamelCase	(      lowercase_   )		->	Matrix:


  '''simple docstring'''






  lowercase__  :   list[list[float]]    		=      [[0] * n for _ in range(lowercase_   )]
  return Matrix(lowercase_ , lowercase_ , lowercase_   )



def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_ , lowercase_   )		->	Matrix:


  '''simple docstring'''






  random.seed(lowercase_   )
  lowercase__  :   list[list[float]]    		=      [
      [random.randint(lowercase_ , lowercase_   ) for _ in range(lowercase_   )] for _ in range(lowercase_   )
  ]
  return Matrix(lowercase_ , lowercase_ , lowercase_   )






