

from __future__ import annotations






class 	__magic_name__    :





			def __init__(		self					,  __snake_case					)   -> None:




						'''simple docstring'''
						__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 		__magic_name__    (		self					,  __snake_case					,  __snake_case					)   -> None:




						'''simple docstring'''
						if len(__snake_case					) < self.order:
									__a        =[1.0, *a_coeffs]

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

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

						__a        =a_coeffs
						__a        =b_coeffs





			def 		__magic_name__    (		self					,  __snake_case					)   -> float:




						'''simple docstring'''
						__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









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCAmelCase					:			Tuple  				=			{
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase					:			Optional[int]  				=			["LlamaTokenizer"]

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase					:			Optional[int]  				=			["LlamaTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase					:			List[Any]  				=			[
						    "LlamaForCausalLM",
						    "LlamaModel",
						    "LlamaPreTrainedModel",
						    "LlamaForSequenceClassification",
						]


if TYPE_CHECKING:
						from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_llama import LlamaTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_llama_fast import LlamaTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
						import sys

						_lowerCAmelCase					:			int  				=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






