from collections import OrderedDict
from typing import Any, List, Mapping, Optional

from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging


_lowercase:	Union[str, Any]       			=		logging.get_logger(__name__)


_lowercase:	Optional[int]       			=		{
    '''Salesforce/codegen-350M-nl''': '''https://huggingface.co/Salesforce/codegen-350M-nl/resolve/main/config.json''',
    '''Salesforce/codegen-350M-multi''': '''https://huggingface.co/Salesforce/codegen-350M-multi/resolve/main/config.json''',
    '''Salesforce/codegen-350M-mono''': '''https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/config.json''',
    '''Salesforce/codegen-2B-nl''': '''https://huggingface.co/Salesforce/codegen-2B-nl/resolve/main/config.json''',
    '''Salesforce/codegen-2B-multi''': '''https://huggingface.co/Salesforce/codegen-2B-multi/resolve/main/config.json''',
    '''Salesforce/codegen-2B-mono''': '''https://huggingface.co/Salesforce/codegen-2B-mono/resolve/main/config.json''',
    '''Salesforce/codegen-6B-nl''': '''https://huggingface.co/Salesforce/codegen-6B-nl/resolve/main/config.json''',
    '''Salesforce/codegen-6B-multi''': '''https://huggingface.co/Salesforce/codegen-6B-multi/resolve/main/config.json''',
    '''Salesforce/codegen-6B-mono''': '''https://huggingface.co/Salesforce/codegen-6B-mono/resolve/main/config.json''',
    '''Salesforce/codegen-16B-nl''': '''https://huggingface.co/Salesforce/codegen-16B-nl/resolve/main/config.json''',
    '''Salesforce/codegen-16B-multi''': '''https://huggingface.co/Salesforce/codegen-16B-multi/resolve/main/config.json''',
    '''Salesforce/codegen-16B-mono''': '''https://huggingface.co/Salesforce/codegen-16B-mono/resolve/main/config.json''',
}



class        lowerCamelCase__				(   _UpperCamelCase				):
			UpperCamelCase__    							='codegen'
			UpperCamelCase__    							={
			    'max_position_embeddings': 'n_positions',
			    'hidden_size': 'n_embd',
			    'num_attention_heads': 'n_head',
			    'num_hidden_layers': 'n_layer',
			}





			def __init__(       self	:	List[str]  ,  lowercase__	:	str=5_04_00  ,  lowercase__	:	Optional[int]=20_48  ,  lowercase__	:	Optional[int]=20_48  ,  lowercase__	:	str=40_96  ,  lowercase__	:	List[str]=28  ,  lowercase__	:	Union[str, Any]=16  ,  lowercase__	:	Optional[int]=64  ,  lowercase__	:	List[Any]=None  ,  lowercase__	:	int="gelu_new"  ,  lowercase__	:	List[str]=0.0  ,  lowercase__	:	Optional[int]=0.0  ,  lowercase__	:	List[Any]=0.0  ,  lowercase__	:	int=1e-5  ,  lowercase__	:	Optional[int]=0.0_2  ,  lowercase__	:	Any=True  ,  lowercase__	:	Optional[Any]=5_02_56  ,  lowercase__	:	Dict=5_02_56  ,  lowercase__	:	List[str]=False  ,  **lowercase__	:	List[str]  ,  ):
										_lowerCAmelCase							=							vocab_size
										_lowerCAmelCase							=							n_ctx
										_lowerCAmelCase							=							n_positions
										_lowerCAmelCase							=							n_embd
										_lowerCAmelCase							=							n_layer
										_lowerCAmelCase							=							n_head
										_lowerCAmelCase							=							n_inner
										_lowerCAmelCase							=							rotary_dim
										_lowerCAmelCase							=							activation_function
										_lowerCAmelCase							=							resid_pdrop
										_lowerCAmelCase							=							embd_pdrop
										_lowerCAmelCase							=							attn_pdrop
										_lowerCAmelCase							=							layer_norm_epsilon
										_lowerCAmelCase							=							initializer_range
										_lowerCAmelCase							=							use_cache

										_lowerCAmelCase							=							bos_token_id
										_lowerCAmelCase							=							eos_token_id

										super().__init__(
										    bos_token_id=lowercase__  ,  eos_token_id=lowercase__  ,  tie_word_embeddings=lowercase__  ,  **lowercase__						)







class        lowerCamelCase__				(   _UpperCamelCase				):





			def __init__(       self	:	Union[str, Any]  ,  lowercase__	:	PretrainedConfig  ,  lowercase__	:	str = "default"  ,  lowercase__	:	List[PatchingSpec] = None  ,  lowercase__	:	bool = False  ,  ):
										super().__init__(lowercase__  ,  task=lowercase__  ,  patching_specs=lowercase__  ,  use_past=lowercase__						)
										if not getattr(self._config  ,  'pad_token_id'  ,  lowercase__						):
																	# TODO: how to do that better?
																	_lowerCAmelCase							=							0





			@property
			def   SCREAMING_SNAKE_CASE__     (       self	:	Optional[int]						):
										_lowerCAmelCase							=							OrderedDict({'input_ids': {0: 'batch', 1: 'sequence'}}						)
										if self.use_past:
																	self.fill_with_past_key_values_(lowercase__  ,  direction='inputs'						)
																	_lowerCAmelCase							=							{0: """batch""", 1: """past_sequence + sequence"""}
										else:
																	_lowerCAmelCase							=							{0: """batch""", 1: """sequence"""}

										return common_inputs





			@property
			def   SCREAMING_SNAKE_CASE__     (       self	:	str						):
										return self._config.n_layer





			@property
			def   SCREAMING_SNAKE_CASE__     (       self	:	List[Any]						):
										return self._config.n_head





			def   SCREAMING_SNAKE_CASE__     (       self	:	int  ,  lowercase__	:	PreTrainedTokenizer  ,  lowercase__	:	int = -1  ,  lowercase__	:	int = -1  ,  lowercase__	:	bool = False  ,  lowercase__	:	Optional[TensorType] = None  ,  ):
										_lowerCAmelCase							=							super(lowercase__  ,  self						).generate_dummy_inputs(
										    lowercase__  ,  batch_size=lowercase__  ,  seq_length=lowercase__  ,  is_pair=lowercase__  ,  framework=lowercase__						)

										# We need to order the input in the way they appears in the forward()
										_lowerCAmelCase							=							OrderedDict({'input_ids': common_inputs['input_ids']}						)

										# Need to add the past_keys
										if self.use_past:
																	if not is_torch_available():
																								raise ValueError('Cannot generate dummy past_keys inputs without PyTorch installed.'						)
																	else:
																								import torch

																								_lowerCAmelCase							=							common_inputs["""input_ids"""].shape
																								# Not using the same length for past_key_values
																								_lowerCAmelCase							=							seqlen + 2
																								_lowerCAmelCase							=							(
																								    batch,
																								    self.num_attention_heads,
																								    past_key_values_length,
																								    self._config.hidden_size // self.num_attention_heads,
																								)
																								_lowerCAmelCase							=							[
																								    (torch.zeros(lowercase__						), torch.zeros(lowercase__						)) for _ in range(self.num_layers						)
																								]

										_lowerCAmelCase							=							common_inputs["""attention_mask"""]
										if self.use_past:
																	_lowerCAmelCase							=							ordered_inputs["""attention_mask"""].dtype
																	_lowerCAmelCase							=							torch.cat(
																	    [ordered_inputs['attention_mask'], torch.ones(lowercase__  ,  lowercase__  ,  dtype=lowercase__						)]  ,  dim=1						)

										return ordered_inputs





			@property
			def   SCREAMING_SNAKE_CASE__     (       self	:	Any						):
										return 13












import logging
import os
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


a__		     =     {
    '''debug''': logging.DEBUG,
    '''info''': logging.INFO,
    '''warning''': logging.WARNING,
    '''error''': logging.ERROR,
    '''critical''': logging.CRITICAL,
}

a__		     =     logging.WARNING





def 				A__ ()     ->						Any:
					__UpperCamelCase					:	Union[str, Any]             =      os.getenv("""DATASETS_VERBOSITY"""		,	snake_case				)
					if env_level_str:
										if env_level_str in log_levels:
															return log_levels[env_level_str]
										else:
															logging.getLogger().warning(
															    F'''Unknown option DATASETS_VERBOSITY={env_level_str}, '''
															    F'''has to be one of: { ", ".join(log_levels.keys()				) }'''				)
					return _default_log_level





def 				A__ ()     ->						str:
					return __name__.split("""."""				)[0]





def 				A__ ()     ->						logging.Logger:
					return logging.getLogger(_get_library_name()				)





def 				A__ ()     ->						None:
					# Apply our default configuration to the library root logger.
					__UpperCamelCase					:	Any             =      _get_library_root_logger()
					library_root_logger.setLevel(_get_default_logging_level()				)





def 				A__ ()     ->						None:
					__UpperCamelCase					:	List[Any]             =      _get_library_root_logger()
					library_root_logger.setLevel(logging.NOTSET				)





def 				A__ (snake_case   :		Optional[str] = None				)     ->						logging.Logger:
					if name is None:
										__UpperCamelCase					:	Optional[int]             =      _get_library_name()
					return logging.getLogger(snake_case				)





def 				A__ ()     ->						int:
					return _get_library_root_logger().getEffectiveLevel()





def 				A__ (snake_case   :		int				)     ->						None:
					_get_library_root_logger().setLevel(snake_case				)





def 				A__ ()     ->						Dict:
					return set_verbosity(snake_case				)





def 				A__ ()     ->						Any:
					return set_verbosity(snake_case				)





def 				A__ ()     ->						Dict:
					return set_verbosity(snake_case				)





def 				A__ ()     ->						str:
					return set_verbosity(snake_case				)





def 				A__ ()     ->						None:
					__UpperCamelCase					:	str             =      False





def 				A__ ()     ->						None:
					__UpperCamelCase					:	List[str]             =      True


# Configure the library root logger at the module level (singleton-like)
_configure_library_root_logger()


class    SCREAMING_SNAKE_CASE_				:



	"""simple docstring"""


	def __init__(					self		:						Optional[int]					,     *lowerCAmelCase		:						str					,     **lowerCAmelCase		:						List[str]	)	->       Union[str, Any]:  # pylint: disable=unused-argument







						"""simple docstring"""







						__UpperCamelCase					:	List[str]             =      args[0] if args else None






	def __iter__(					self		:						List[Any]	)	->       List[Any]:







						"""simple docstring"""







						return iter(self._iterator	)






	def __getattr__(					self		:						int					,     lowerCAmelCase		:						List[str]	)	->       Dict:







						"""simple docstring"""







						def empty_fn(*lowerCAmelCase		:						List[Any]					,     **lowerCAmelCase		:						Dict	):  # pylint: disable=unused-argument
											return

						return empty_fn






	def __enter__(					self		:						Tuple	)	->       Any:







						"""simple docstring"""







						return self






	def __exit__(					self		:						str					,     lowerCAmelCase		:						Dict					,     lowerCAmelCase		:						Dict					,     lowerCAmelCase		:						List[str]	)	->       Tuple:







						"""simple docstring"""







						return






a__		     =     True


class    SCREAMING_SNAKE_CASE_				:



	"""simple docstring"""


	def __call__(					self		:						str					,     *lowerCAmelCase		:						List[Any]					,     lowerCAmelCase		:						Dict=False					,     **lowerCAmelCase		:						Tuple	)	->       Optional[Any]:







						"""simple docstring"""







						if _tqdm_active and not disable:
											return tqdm_lib.tqdm(*lowerCAmelCase					,     **lowerCAmelCase	)
						else:
											return EmptyTqdm(*lowerCAmelCase					,     **lowerCAmelCase	)






	def 					lowerCamelCase__     (					self		:						Any					,     *lowerCAmelCase		:						List[str]					,     **lowerCAmelCase		:						str	)	->       Dict:







						"""simple docstring"""







						__UpperCamelCase					:	Any             =      None
						if _tqdm_active:
											return tqdm_lib.tqdm.set_lock(*lowerCAmelCase					,     **lowerCAmelCase	)






	def 					lowerCamelCase__     (					self		:						Dict	)	->       Union[str, Any]:







						"""simple docstring"""







						if _tqdm_active:
											return tqdm_lib.tqdm.get_lock()






a__		     =     _tqdm_cls()





def 				A__ ()     ->						bool:
					global _tqdm_active
					return bool(_tqdm_active				)





def 				A__ ()     ->						List[str]:
					global _tqdm_active
					__UpperCamelCase					:	Tuple             =      True







def 				A__ ()     ->						int:
					global _tqdm_active
					__UpperCamelCase					:	Any             =      False






