



from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase__					  =  logging.get_logger(__name__)

lowerCAmelCase__					  =  {
    '''xlm-mlm-en-2048''': '''https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json''',
    '''xlm-mlm-ende-1024''': '''https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json''',
    '''xlm-mlm-enfr-1024''': '''https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json''',
    '''xlm-mlm-enro-1024''': '''https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json''',
    '''xlm-mlm-tlm-xnli15-1024''': '''https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json''',
    '''xlm-mlm-xnli15-1024''': '''https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json''',
    '''xlm-clm-enfr-1024''': '''https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json''',
    '''xlm-clm-ende-1024''': '''https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json''',
    '''xlm-mlm-17-1280''': '''https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json''',
    '''xlm-mlm-100-1280''': '''https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json''',
}

class 				snake_case__(_UpperCamelCase      ):

					"""simple docstring"""






					lowercase_								=		"""xlm"""
					lowercase_								=		{
					    """hidden_size""": """emb_dim""",
					    """num_attention_heads""": """n_heads""",
					    """num_hidden_layers""": """n_layers""",
					    """n_words""": """vocab_size""",  # For backward compatibility
					}







					def __init__(							self :     List[Any]				,       SCREAMING_SNAKE_CASE :     Optional[int]=30_145				,       SCREAMING_SNAKE_CASE :     Tuple=2_048				,       SCREAMING_SNAKE_CASE :     Optional[int]=12				,       SCREAMING_SNAKE_CASE :     List[Any]=16				,       SCREAMING_SNAKE_CASE :     int=0.1				,       SCREAMING_SNAKE_CASE :     Optional[Any]=0.1				,       SCREAMING_SNAKE_CASE :     Union[str, Any]=True				,       SCREAMING_SNAKE_CASE :     int=False				,       SCREAMING_SNAKE_CASE :     Optional[Any]=False				,       SCREAMING_SNAKE_CASE :     Any=False				,       SCREAMING_SNAKE_CASE :     Any=1				,       SCREAMING_SNAKE_CASE :     int=True				,       SCREAMING_SNAKE_CASE :     Dict=512				,       SCREAMING_SNAKE_CASE :     str=2_048**-0.5				,       SCREAMING_SNAKE_CASE :     List[Any]=1E-1_2				,       SCREAMING_SNAKE_CASE :     Dict=0.02				,       SCREAMING_SNAKE_CASE :     str=0				,       SCREAMING_SNAKE_CASE :     Tuple=1				,       SCREAMING_SNAKE_CASE :     int=2				,       SCREAMING_SNAKE_CASE :     Dict=3				,       SCREAMING_SNAKE_CASE :     Dict=5				,       SCREAMING_SNAKE_CASE :     Dict=True				,       SCREAMING_SNAKE_CASE :     int="first"				,       SCREAMING_SNAKE_CASE :     Tuple=True				,       SCREAMING_SNAKE_CASE :     List[Any]=None				,       SCREAMING_SNAKE_CASE :     Tuple=True				,       SCREAMING_SNAKE_CASE :     Optional[Any]=0.1				,       SCREAMING_SNAKE_CASE :     Optional[Any]=5				,       SCREAMING_SNAKE_CASE :     int=5				,       SCREAMING_SNAKE_CASE :     Tuple=0				,       SCREAMING_SNAKE_CASE :     Optional[Any]=0				,       SCREAMING_SNAKE_CASE :     Optional[Any]=2				,       SCREAMING_SNAKE_CASE :     Optional[Any]=0				,       **SCREAMING_SNAKE_CASE :     Tuple				,       ):
									lowercase__					:   Optional[Any]													=					vocab_size
									lowercase__					:   List[Any]													=					emb_dim
									lowercase__					:   Union[str, Any]													=					n_layers
									lowercase__					:   Dict													=					n_heads
									lowercase__					:   Optional[Any]													=					dropout
									lowercase__					:   str													=					attention_dropout
									lowercase__					:   Any													=					gelu_activation
									lowercase__					:   Union[str, Any]													=					sinusoidal_embeddings
									lowercase__					:   Optional[Any]													=					causal
									lowercase__					:   Union[str, Any]													=					asm
									lowercase__					:   List[str]													=					n_langs
									lowercase__					:   int													=					use_lang_emb
									lowercase__					:   Optional[Any]													=					layer_norm_eps
									lowercase__					:   Any													=					bos_index
									lowercase__					:   Optional[Any]													=					eos_index
									lowercase__					:   Optional[int]													=					pad_index
									lowercase__					:   int													=					unk_index
									lowercase__					:   str													=					mask_index
									lowercase__					:   List[str]													=					is_encoder
									lowercase__					:   Union[str, Any]													=					max_position_embeddings
									lowercase__					:   str													=					embed_init_std
									lowercase__					:   Dict													=					init_std
									lowercase__					:   List[Any]													=					summary_type
									lowercase__					:   Any													=					summary_use_proj
									lowercase__					:   Optional[int]													=					summary_activation
									lowercase__					:   Any													=					summary_proj_to_labels
									lowercase__					:   Tuple													=					summary_first_dropout
									lowercase__					:   Any													=					start_n_top
									lowercase__					:   Optional[int]													=					end_n_top
									lowercase__					:   int													=					mask_token_id
									lowercase__					:   Union[str, Any]													=					lang_id

									if "n_words" in kwargs:
													lowercase__					:   int													=					kwargs["n_words"]

									super().__init__(pad_token_id=SCREAMING_SNAKE_CASE				,       bos_token_id=SCREAMING_SNAKE_CASE				,       **SCREAMING_SNAKE_CASE					)






class 				snake_case__(_UpperCamelCase      ):

					"""simple docstring"""






					@property
					def 			snake_case					(							self :     List[str]					):
									if self.task == "multiple-choice":
													lowercase__					:   Any													=					{0: "batch", 1: "choice", 2: "sequence"}
									else:
													lowercase__					:   str													=					{0: "batch", 1: "sequence"}
									return OrderedDict(
									    [
									        ("input_ids", dynamic_axis),
									        ("attention_mask", dynamic_axis),
									        ("token_type_ids", dynamic_axis),
									    ]					)









from typing import Union

import fire
import torch
from tqdm import tqdm


def  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__ = "cpu"					,			lowerCamelCase__ = None						):

				"""simple docstring"""


				lowercase__					:   Any													=					torch.load(lowerCamelCase__					,			map_location=lowerCamelCase__						)
				for k, v in tqdm(state_dict.items()						):
								if not isinstance(lowerCamelCase__					,			torch.Tensor						):
												raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"						)
								lowercase__					:   int													=					v.half()
				if save_path is None:  # overwrite src_path
								lowercase__					:   Optional[Any]													=					src_path
				torch.save(lowerCamelCase__					,			lowerCamelCase__						)


if __name__ == "__main__":
				fire.Fire(convert)




