



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


UpperCAmelCase :				Optional[int]							=logging.get_logger(__name__)

UpperCAmelCase :				int							={
    """uclanlp/plbart-base""": """https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json""",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}


class    _lowercase (a_   ):
				'''simple docstring'''







				lowercase__     =    """plbart"""
				lowercase__     =    ["""past_key_values"""]
				lowercase__     =    {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}

				def __init__(			self  ,			snake_case__=5_0005  ,			snake_case__=1024  ,			snake_case__=6  ,			snake_case__=3072  ,			snake_case__=12  ,			snake_case__=6  ,			snake_case__=3072  ,			snake_case__=12  ,			snake_case__=0.0  ,			snake_case__=0.0  ,			snake_case__=True  ,			snake_case__=True  ,			snake_case__="gelu"  ,			snake_case__=768  ,			snake_case__=0.1  ,			snake_case__=0.1  ,			snake_case__=0.0  ,			snake_case__=0.02  ,			snake_case__=0.0  ,			snake_case__=True  ,			snake_case__=1  ,			snake_case__=0  ,			snake_case__=2  ,			snake_case__=2  ,			**snake_case__  ,			):

									'''simple docstring'''


									UpperCamelCase_			= vocab_size
									UpperCamelCase_			= max_position_embeddings
									UpperCamelCase_			= d_model
									UpperCamelCase_			= encoder_ffn_dim
									UpperCamelCase_			= encoder_layers
									UpperCamelCase_			= encoder_attention_heads
									UpperCamelCase_			= decoder_ffn_dim
									UpperCamelCase_			= decoder_layers
									UpperCamelCase_			= decoder_attention_heads
									UpperCamelCase_			= dropout
									UpperCamelCase_			= attention_dropout
									UpperCamelCase_			= activation_dropout
									UpperCamelCase_			= activation_function
									UpperCamelCase_			= init_std
									UpperCamelCase_			= encoder_layerdrop
									UpperCamelCase_			= decoder_layerdrop
									UpperCamelCase_			= classifier_dropout
									UpperCamelCase_			= use_cache
									UpperCamelCase_			= encoder_layers
									UpperCamelCase_			= scale_embedding  # scale factor will be sqrt(d_model) if True
									super().__init__(
									    pad_token_id=snake_case__  ,			bos_token_id=snake_case__  ,			eos_token_id=snake_case__  ,			is_encoder_decoder=snake_case__  ,			forced_eos_token_id=snake_case__  ,			**snake_case__  ,			)




class    _lowercase (a_   ):
				'''simple docstring'''







				@property
				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									return OrderedDict(
									    [
									        ("input_ids", {0: "batch", 1: "sequence"}),
									        ("attention_mask", {0: "batch", 1: "sequence"}),
									    ]     )

				@property
				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									if self.use_past:
														return OrderedDict(
														    [
														        ("last_hidden_state", {0: "batch", 1: "sequence"}),
														        ("past_keys", {0: "batch", 2: "sequence"}),
														        ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
														    ]     )
									else:
														return OrderedDict(
														    [
														        ("last_hidden_state", {0: "batch", 1: "sequence"}),
														        ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
														    ]     )





UpperCAmelCase :				Optional[int]							="""
# Diffusers installation
! pip install diffusers transformers datasets accelerate
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/diffusers.git
"""

UpperCAmelCase :				List[Any]							=[{"""type""": """code""", """content""": INSTALL_CONTENT}]
