import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs
class    A_ (       a_ ):

  def __init__(		self :      Union[str, Any]     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]     ,							__SCREAMING_SNAKE_CASE :      List[str]=None     ,							__SCREAMING_SNAKE_CASE :      Any=True     ,							__SCREAMING_SNAKE_CASE :      List[Any]=None     ,							**__SCREAMING_SNAKE_CASE :      Optional[int]       ):
   __a       =  parent
   __a       =  config_class
   __a       =  has_text_modality
   __a       =  kwargs
   __a       =  common_properties

  def 		_UpperCAmelCase   (		self :      List[str]       ):
   __a       =  self.config_class(**self.inputs_dict       )
   __a       =  (
       ["hidden_size", "num_attention_heads", "num_hidden_layers"]
       if self.common_properties is None
       else self.common_properties
   )

   # Add common fields for text models
   if self.has_text_modality:
    common_properties.extend(["vocab_size"]       )

   # Test that config has the common properties as getters
   for prop in common_properties:
    self.parent.assertTrue(hasattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )     ,							msg=f"""`{prop}` does not exist"""       )

   # Test that config has the common properties as setter
   for idx, name in enumerate(__SCREAMING_SNAKE_CASE       ):
    try:
     setattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )
     self.parent.assertEqual(
         getattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )     ,							__SCREAMING_SNAKE_CASE     ,							msg=f"""`{name} value {idx} expected, but was {getattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )}"""       )
    except NotImplementedError:
     # Some models might not be able to implement setters for common_properties
     # In that case, a NotImplementedError is raised
     pass

        # Test if config class can be called with Config(prop_name=..)
   for idx, name in enumerate(__SCREAMING_SNAKE_CASE       ):
    try:
     __a       =  self.config_class(**{name: idx}       )
     self.parent.assertEqual(
         getattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )     ,							__SCREAMING_SNAKE_CASE     ,							msg=f"""`{name} value {idx} expected, but was {getattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )}"""       )
    except NotImplementedError:
     # Some models might not be able to implement setters for common_properties
     # In that case, a NotImplementedError is raised
     pass

  def 		_UpperCAmelCase   (		self :      Union[str, Any]       ):
   __a       =  self.config_class(**self.inputs_dict       )
   __a       =  json.loads(config.to_json_string()       )
   for key, value in self.inputs_dict.items():
    self.parent.assertEqual(obj[key]     ,							__SCREAMING_SNAKE_CASE       )

  def 		_UpperCAmelCase   (		self :      Optional[int]       ):
   __a       =  self.config_class(**self.inputs_dict       )

   with tempfile.TemporaryDirectory() as tmpdirname:
    __a       =  os.path.join(__SCREAMING_SNAKE_CASE     ,							"config.json"       )
    config_first.to_json_file(__SCREAMING_SNAKE_CASE       )
    __a       =  self.config_class.from_json_file(__SCREAMING_SNAKE_CASE       )

   self.parent.assertEqual(config_second.to_dict()     ,							config_first.to_dict()       )

  def 		_UpperCAmelCase   (		self :      Union[str, Any]       ):
   __a       =  self.config_class(**self.inputs_dict       )

   with tempfile.TemporaryDirectory() as tmpdirname:
    config_first.save_pretrained(__SCREAMING_SNAKE_CASE       )
    __a       =  self.config_class.from_pretrained(__SCREAMING_SNAKE_CASE       )

   self.parent.assertEqual(config_second.to_dict()     ,							config_first.to_dict()       )

  def 		_UpperCAmelCase   (		self :      Any       ):
   __a       =  self.config_class(**self.inputs_dict       )

   __a       =  "test"
   with tempfile.TemporaryDirectory() as tmpdirname:
    __a       =  os.path.join(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )
    config_first.save_pretrained(__SCREAMING_SNAKE_CASE       )
    __a       =  self.config_class.from_pretrained(__SCREAMING_SNAKE_CASE     ,							subfolder=__SCREAMING_SNAKE_CASE       )

   self.parent.assertEqual(config_second.to_dict()     ,							config_first.to_dict()       )

  def 		_UpperCAmelCase   (		self :      Union[str, Any]       ):
   __a       =  self.config_class(**self.inputs_dict     ,							num_labels=5       )
   self.parent.assertEqual(len(config.idalabel       )     ,							5       )
   self.parent.assertEqual(len(config.labelaid       )     ,							5       )

   __a       =  3
   self.parent.assertEqual(len(config.idalabel       )     ,							3       )
   self.parent.assertEqual(len(config.labelaid       )     ,							3       )

  def 		_UpperCAmelCase   (		self :      List[str]       ):
   if self.config_class.is_composition:
    return
   __a       =  self.config_class()
   self.parent.assertIsNotNone(__SCREAMING_SNAKE_CASE       )

  def 		_UpperCAmelCase   (		self :      int       ):
   __a       =  copy.deepcopy(__SCREAMING_SNAKE_CASE       )
   __a       =  self.config_class(**__SCREAMING_SNAKE_CASE       )
   __a       =  []
   for key, value in config_common_kwargs.items():
    if key == "torch_dtype":
     if not is_torch_available():
      continue
     else:
      import torch

      if config.torch_dtype != torch.floataa:
       wrong_values.append(("torch_dtype", config.torch_dtype, torch.floataa)       )
    elif getattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       ) != value:
     wrong_values.append((key, getattr(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       ), value)       )

   if len(__SCREAMING_SNAKE_CASE       ) > 0:
    __a       =  "\n".join([f"""- {v[0]}: got {v[1]} instead of {v[2]}""" for v in wrong_values]       )
    raise ValueError(f"""The following keys were not properly set in the config:\n{errors}"""       )

  def 		_UpperCAmelCase   (		self :      Optional[Any]       ):
   self.create_and_test_config_common_properties()
   self.create_and_test_config_to_json_string()
   self.create_and_test_config_to_json_file()
   self.create_and_test_config_from_and_save_pretrained()
   self.create_and_test_config_from_and_save_pretrained_subfolder()
   self.create_and_test_config_with_num_labels()
   self.check_config_can_be_init_without_params()
   self.check_config_arguments_init()



from __future__ import annotations
class    A_ :

  def __init__(		self :      Union[str, Any]     ,							__SCREAMING_SNAKE_CASE :      int       ):
   __a       =  order

   # a_{0} ... a_{k}
   __a       =  [1.0] + [0.0] * order
   # b_{0} ... b_{k}
   __a       =  [1.0] + [0.0] * order

   # x[n-1] ... x[n-k]
   __a       =  [0.0] * self.order
   # y[n-1] ... y[n-k]
   __a       =  [0.0] * self.order

  def 		_UpperCAmelCase   (		self :      Union[str, Any]     ,							__SCREAMING_SNAKE_CASE :      list[float]     ,							__SCREAMING_SNAKE_CASE :      list[float]       ):
   if len(__SCREAMING_SNAKE_CASE       ) < self.order:
    __a       =  [1.0, *a_coeffs]

   if len(__SCREAMING_SNAKE_CASE       ) != self.order + 1:
    __a       =  (
        f"""Expected a_coeffs to have {self.order + 1} elements """
        f"""for {self.order}-order filter, got {len(__SCREAMING_SNAKE_CASE       )}"""
    )
    raise ValueError(__SCREAMING_SNAKE_CASE       )

   if len(__SCREAMING_SNAKE_CASE       ) != self.order + 1:
    __a       =  (
        f"""Expected b_coeffs to have {self.order + 1} elements """
        f"""for {self.order}-order filter, got {len(__SCREAMING_SNAKE_CASE       )}"""
    )
    raise ValueError(__SCREAMING_SNAKE_CASE       )

   __a       =  a_coeffs
   __a       =  b_coeffs

  def 		_UpperCAmelCase   (		self :      Optional[Any]     ,							__SCREAMING_SNAKE_CASE :      float       ):
   __a       =  0.0

   # Start at index 1 and do index 0 at the end.
   for i in range(1     ,							self.order + 1       ):
    result += (
        self.b_coeffs[i] * self.input_history[i - 1]
        - self.a_coeffs[i] * self.output_history[i - 1]
    )

   __a       =  (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

   __a       =  self.input_history[:-1]
   __a       =  self.output_history[:-1]

   __a       =  sample
   __a       =  result

   return result


