
from typing import TYPE_CHECKING

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


lowercase__	:Optional[int]										=					{
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

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

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__	: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

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






import logging

from transformers import PretrainedConfig


lowercase__	:int										=					logging.getLogger(__name__)


lowercase__	:Dict										=					{
    "bertabs-finetuned-cnndm": "https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json",
}







class        lowercase	(      SCREAMING_SNAKE_CASE__	):
							lowercase_ : Optional[int]       ='''bertabs'''




							def __init__(       self     ,A__=3_0_5_2_2     ,A__=5_1_2     ,A__=6     ,A__=5_1_2     ,A__=8     ,A__=5_1_2     ,A__=0.2     ,A__=6     ,A__=7_6_8     ,A__=8     ,A__=2_0_4_8     ,A__=0.2     ,**A__     ,):
												super().__init__(**A__)

												lowercase					=		vocab_size
												lowercase					=		max_pos

												lowercase					=		enc_layers
												lowercase					=		enc_hidden_size
												lowercase					=		enc_heads
												lowercase					=		enc_ff_size
												lowercase					=		enc_dropout

												lowercase					=		dec_layers
												lowercase					=		dec_hidden_size
												lowercase					=		dec_heads
												lowercase					=		dec_ff_size
												lowercase					=		dec_dropout




