


import argparse

import torch

from transformers import (
    EncodecConfig,
    EncodecFeatureExtractor,
    EncodecModel,
    logging,
)


# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_state_dict.bin
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_48khz-7e698e3e.th


logging.set_verbosity_info()
_lowerCAmelCase:						Union[str, Any]   				=       logging.get_logger('transformers.models.encodec')

_lowerCAmelCase:						List[Any]   				=       {
    'quantizer.vq.layers.*._codebook.inited': 'quantizer.layers.*.codebook.inited',
    'quantizer.vq.layers.*._codebook.cluster_size': 'quantizer.layers.*.codebook.cluster_size',
    'quantizer.vq.layers.*._codebook.embed': 'quantizer.layers.*.codebook.embed',
    'quantizer.vq.layers.*._codebook.embed_avg': 'quantizer.layers.*.codebook.embed_avg',
}
_lowerCAmelCase:						str   				=       {
    'encoder.model.0.conv.conv': 'encoder.layers.0.conv',
    'encoder.model.1.block.1.conv.conv': 'encoder.layers.1.block.1.conv',
    'encoder.model.1.block.3.conv.conv': 'encoder.layers.1.block.3.conv',
    'encoder.model.1.shortcut.conv.conv': 'encoder.layers.1.shortcut.conv',
    'encoder.model.3.conv.conv': 'encoder.layers.3.conv',
    'encoder.model.4.block.1.conv.conv': 'encoder.layers.4.block.1.conv',
    'encoder.model.4.block.3.conv.conv': 'encoder.layers.4.block.3.conv',
    'encoder.model.4.shortcut.conv.conv': 'encoder.layers.4.shortcut.conv',
    'encoder.model.6.conv.conv': 'encoder.layers.6.conv',
    'encoder.model.7.block.1.conv.conv': 'encoder.layers.7.block.1.conv',
    'encoder.model.7.block.3.conv.conv': 'encoder.layers.7.block.3.conv',
    'encoder.model.7.shortcut.conv.conv': 'encoder.layers.7.shortcut.conv',
    'encoder.model.9.conv.conv': 'encoder.layers.9.conv',
    'encoder.model.10.block.1.conv.conv': 'encoder.layers.10.block.1.conv',
    'encoder.model.10.block.3.conv.conv': 'encoder.layers.10.block.3.conv',
    'encoder.model.10.shortcut.conv.conv': 'encoder.layers.10.shortcut.conv',
    'encoder.model.12.conv.conv': 'encoder.layers.12.conv',
    'encoder.model.13.lstm': 'encoder.layers.13.lstm',
    'encoder.model.15.conv.conv': 'encoder.layers.15.conv',
}
_lowerCAmelCase:						Optional[int]   				=       {
    'encoder.model.0.conv.norm': 'encoder.layers.0.norm',
    'encoder.model.1.block.1.conv.norm': 'encoder.layers.1.block.1.norm',
    'encoder.model.1.block.3.conv.norm': 'encoder.layers.1.block.3.norm',
    'encoder.model.1.shortcut.conv.norm': 'encoder.layers.1.shortcut.norm',
    'encoder.model.3.conv.norm': 'encoder.layers.3.norm',
    'encoder.model.4.block.1.conv.norm': 'encoder.layers.4.block.1.norm',
    'encoder.model.4.block.3.conv.norm': 'encoder.layers.4.block.3.norm',
    'encoder.model.4.shortcut.conv.norm': 'encoder.layers.4.shortcut.norm',
    'encoder.model.6.conv.norm': 'encoder.layers.6.norm',
    'encoder.model.7.block.1.conv.norm': 'encoder.layers.7.block.1.norm',
    'encoder.model.7.block.3.conv.norm': 'encoder.layers.7.block.3.norm',
    'encoder.model.7.shortcut.conv.norm': 'encoder.layers.7.shortcut.norm',
    'encoder.model.9.conv.norm': 'encoder.layers.9.norm',
    'encoder.model.10.block.1.conv.norm': 'encoder.layers.10.block.1.norm',
    'encoder.model.10.block.3.conv.norm': 'encoder.layers.10.block.3.norm',
    'encoder.model.10.shortcut.conv.norm': 'encoder.layers.10.shortcut.norm',
    'encoder.model.12.conv.norm': 'encoder.layers.12.norm',
    'encoder.model.15.conv.norm': 'encoder.layers.15.norm',
}
_lowerCAmelCase:						Dict   				=       {
    'decoder.model.0.conv.conv': 'decoder.layers.0.conv',
    'decoder.model.1.lstm': 'decoder.layers.1.lstm',
    'decoder.model.3.convtr.convtr': 'decoder.layers.3.conv',
    'decoder.model.4.block.1.conv.conv': 'decoder.layers.4.block.1.conv',
    'decoder.model.4.block.3.conv.conv': 'decoder.layers.4.block.3.conv',
    'decoder.model.4.shortcut.conv.conv': 'decoder.layers.4.shortcut.conv',
    'decoder.model.6.convtr.convtr': 'decoder.layers.6.conv',
    'decoder.model.7.block.1.conv.conv': 'decoder.layers.7.block.1.conv',
    'decoder.model.7.block.3.conv.conv': 'decoder.layers.7.block.3.conv',
    'decoder.model.7.shortcut.conv.conv': 'decoder.layers.7.shortcut.conv',
    'decoder.model.9.convtr.convtr': 'decoder.layers.9.conv',
    'decoder.model.10.block.1.conv.conv': 'decoder.layers.10.block.1.conv',
    'decoder.model.10.block.3.conv.conv': 'decoder.layers.10.block.3.conv',
    'decoder.model.10.shortcut.conv.conv': 'decoder.layers.10.shortcut.conv',
    'decoder.model.12.convtr.convtr': 'decoder.layers.12.conv',
    'decoder.model.13.block.1.conv.conv': 'decoder.layers.13.block.1.conv',
    'decoder.model.13.block.3.conv.conv': 'decoder.layers.13.block.3.conv',
    'decoder.model.13.shortcut.conv.conv': 'decoder.layers.13.shortcut.conv',
    'decoder.model.15.conv.conv': 'decoder.layers.15.conv',
}
_lowerCAmelCase:						Tuple   				=       {
    'decoder.model.0.conv.norm': 'decoder.layers.0.norm',
    'decoder.model.3.convtr.norm': 'decoder.layers.3.norm',
    'decoder.model.4.block.1.conv.norm': 'decoder.layers.4.block.1.norm',
    'decoder.model.4.block.3.conv.norm': 'decoder.layers.4.block.3.norm',
    'decoder.model.4.shortcut.conv.norm': 'decoder.layers.4.shortcut.norm',
    'decoder.model.6.convtr.norm': 'decoder.layers.6.norm',
    'decoder.model.7.block.1.conv.norm': 'decoder.layers.7.block.1.norm',
    'decoder.model.7.block.3.conv.norm': 'decoder.layers.7.block.3.norm',
    'decoder.model.7.shortcut.conv.norm': 'decoder.layers.7.shortcut.norm',
    'decoder.model.9.convtr.norm': 'decoder.layers.9.norm',
    'decoder.model.10.block.1.conv.norm': 'decoder.layers.10.block.1.norm',
    'decoder.model.10.block.3.conv.norm': 'decoder.layers.10.block.3.norm',
    'decoder.model.10.shortcut.conv.norm': 'decoder.layers.10.shortcut.norm',
    'decoder.model.12.convtr.norm': 'decoder.layers.12.norm',
    'decoder.model.13.block.1.conv.norm': 'decoder.layers.13.block.1.norm',
    'decoder.model.13.block.3.conv.norm': 'decoder.layers.13.block.3.norm',
    'decoder.model.13.shortcut.conv.norm': 'decoder.layers.13.shortcut.norm',
    'decoder.model.15.conv.norm': 'decoder.layers.15.norm',
}
_lowerCAmelCase:						str   				=       {
    **MAPPING_QUANTIZER,
    **MAPPING_ENCODER,
    **MAPPING_DECODER,
}
_lowerCAmelCase:						Dict   				=       {
    **MAPPING_QUANTIZER,
    **MAPPING_ENCODER,
    **MAPPING_ENCODER_48K,
    **MAPPING_DECODER,
    **MAPPING_DECODER_48K,
}
_lowerCAmelCase:						Tuple   				=       []
_lowerCAmelCase:						str   				=       []






def   _lowercase(					__a				:						Any    ,     __a				:						List[str]    ,     __a				:						Tuple    ,     __a				:						Union[str, Any]    ,     __a				:						Optional[Any]     ):
							for attribute in key.split('.'     ):
														a__      =getattr(__a    ,     __a     )

							if weight_type is not None:
														a__      =getattr(__a    ,     __a     ).shape
							else:
														a__      =hf_pointer.shape

							if hf_shape != value.shape:
														raise ValueError(
														    f"""Shape of hf {key + '.' + weight_type if weight_type is not None else ''} is {hf_shape}, but should be"""
														    f""" {value.shape} for {full_name}"""     )

							if weight_type == "weight":
														a__      =value
							elif weight_type == "weight_g":
														a__      =value
							elif weight_type == "weight_v":
														a__      =value
							elif weight_type == "bias":
														a__      =value
							elif weight_type == "running_mean":
														a__      =value
							elif weight_type == "running_var":
														a__      =value
							elif weight_type == "num_batches_tracked":
														a__      =value
							elif weight_type == "weight_ih_l0":
														a__      =value
							elif weight_type == "weight_hh_l0":
														a__      =value
							elif weight_type == "bias_ih_l0":
														a__      =value
							elif weight_type == "bias_hh_l0":
														a__      =value
							elif weight_type == "weight_ih_l1":
														a__      =value
							elif weight_type == "weight_hh_l1":
														a__      =value
							elif weight_type == "bias_ih_l1":
														a__      =value
							elif weight_type == "bias_hh_l1":
														a__      =value
							else:
														a__      =value

							logger.info(f"""{key + ('.' + weight_type if weight_type is not None else '')} was initialized from {full_name}."""     )






def   _lowercase(					__a				:						Optional[int]    ,     __a				:						Union[str, Any]     ):
							for key in ignore_keys:
														if key.endswith('.*'     ):
																					if name.startswith(key[:-1]     ):
																												return True
														elif ".*." in key:
																					a__    ,     a__      =key.split('.*.'     )
																					if prefix in name and suffix in name:
																												return True
														elif key in name:
																					return True
							return False






def   _lowercase(					__a				:						str    ,     __a				:						int    ,     __a				:						Tuple     ):
							a__      =[]

							if model_name == "encodec_24khz" or "encodec_32khz":
														a__      =MAPPING_24K
							elif model_name == "encodec_48khz":
														a__      =MAPPING_48K
							else:
														raise ValueError(f"""Unsupported model: {model_name}"""     )

							for name, value in orig_dict.items():
														if should_ignore(__a    ,     __a     ):
																					logger.info(f"""{name} was ignored"""     )
																					continue

														a__      =False
														for key, mapped_key in MAPPING.items():
																					if "*" in key:
																												a__    ,     a__      =key.split('.*.'     )
																												if prefix in name and suffix in name:
																																			a__      =suffix

																					if key in name:
																												# HACK otherwise .embed gets initialized with .embed_avg too
																												if key.endswith('embed'     ) and name.endswith('embed_avg'     ):
																																			continue

																												a__      =True
																												if "*" in mapped_key:
																																			a__      =name.split(__a     )[0].split('.'     )[-2]
																																			a__      =mapped_key.replace('*'    ,     __a     )
																												if "weight_g" in name:
																																			a__      ='weight_g'
																												elif "weight_v" in name:
																																			a__      ='weight_v'
																												elif "weight_ih_l0" in name:
																																			a__      ='weight_ih_l0'
																												elif "weight_hh_l0" in name:
																																			a__      ='weight_hh_l0'
																												elif "bias_ih_l0" in name:
																																			a__      ='bias_ih_l0'
																												elif "bias_hh_l0" in name:
																																			a__      ='bias_hh_l0'
																												elif "weight_ih_l1" in name:
																																			a__      ='weight_ih_l1'
																												elif "weight_hh_l1" in name:
																																			a__      ='weight_hh_l1'
																												elif "bias_ih_l1" in name:
																																			a__      ='bias_ih_l1'
																												elif "bias_hh_l1" in name:
																																			a__      ='bias_hh_l1'
																												elif "bias" in name:
																																			a__      ='bias'
																												elif "weight" in name:
																																			a__      ='weight'
																												elif "running_mean" in name:
																																			a__      ='running_mean'
																												elif "running_var" in name:
																																			a__      ='running_var'
																												elif "num_batches_tracked" in name:
																																			a__      ='num_batches_tracked'
																												else:
																																			a__      =None
																												set_recursively(__a    ,     __a    ,     __a    ,     __a    ,     __a     )
																					continue
														if not is_used:
																					unused_weights.append(__a     )

							logger.warning(f"""Unused weights: {unused_weights}"""     )






@torch.no_grad()
def   _lowercase(					__a				:						str    ,     __a				:						int    ,     __a				:						str    ,     __a				:						Tuple=None    ,     __a				:						Optional[int]=None    ,     ):
							if config_path is not None:
														a__      =EncodecConfig.from_pretrained(__a     )
							else:
														a__      =EncodecConfig()

							if model_name == "encodec_24khz":
														pass  # config is already correct
							elif model_name == "encodec_32khz":
														a__      =[8, 5, 4, 4]
														a__      =[2.2]
														a__      =64
														a__      =3_2000
														a__      =2048
														a__      =False
														a__      =False
														a__      =False
							elif model_name == "encodec_48khz":
														a__      =[8, 5, 4, 2]
														a__      =[3.0, 6.0, 12.0, 24.0]
														a__      =4_8000
														a__      =2
														a__      =False
														a__      ='time_group_norm'
														a__      =True
														a__      =1.0
														a__      =0.01
							else:
														raise ValueError(f"""Unknown model name: {model_name}"""     )

							a__      =EncodecModel(__a     )

							a__      =EncodecFeatureExtractor(
							    feature_size=config.audio_channels    ,     sampling_rate=config.sampling_rate    ,     chunk_length_s=config.chunk_length_s    ,     overlap=config.overlap    ,     )
							feature_extractor.save_pretrained(__a     )

							a__      =torch.load(__a     )
							if "best_state" in original_checkpoint:
														# we might have a training state saved, in which case discard the yaml results and just retain the weights
														a__      =original_checkpoint['best_state']
							recursively_load_weights(__a    ,     __a    ,     __a     )
							model.save_pretrained(__a     )

							if repo_id:
														print('Pushing to the hub...'     )
														feature_extractor.push_to_hub(__a     )
														model.push_to_hub(__a     )


if __name__ == "__main__":
	_lowerCAmelCase:						str   				=       argparse.ArgumentParser()
	parser.add_argument(
	    '--model',
	    default='encodec_24khz',
	    type=str,
	    help='The model to convert. Should be one of \'encodec_24khz\', \'encodec_32khz\', \'encodec_48khz\'.',
	)
	parser.add_argument('--checkpoint_path', required=True, default=None, type=str, help='Path to original checkpoint')
	parser.add_argument('--config_path', default=None, type=str, help='Path to hf config.json of model to convert')
	parser.add_argument(
	    '--pytorch_dump_folder_path', required=True, default=None, type=str, help='Path to the output PyTorch model.'
	)
	parser.add_argument(
	    '--push_to_hub', default=None, type=str, help='Where to upload the converted model on the 🤗 hub.'
	)

	_lowerCAmelCase:						str   				=       parser.parse_args()
	convert_checkpoint(
	    args.model,
	    args.checkpoint_path,
	    args.pytorch_dump_folder_path,
	    args.config_path,
	    args.push_to_hub,
	)





import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional

import yaml

from transformers import HfArgumentParser, TrainingArguments
from transformers.hf_argparser import make_choice_type_function, string_to_bool


# Since Python 3.10, we can use the builtin `|` operator for Union types
# See PEP 604: https://peps.python.org/pep-0604
_lowerCAmelCase:						Any   				=       sys.version_info >= (3, 10)






def   _lowercase(					__a				:						int=None    ,     __a				:						Any=None     ):
							return field(default_factory=lambda: default    ,     metadata=__a     )




@dataclass
class       lowercase_					:
				snake_case	    =42
				snake_case	    =42
				snake_case	    =42
				snake_case	    =42







@dataclass
class       lowercase_					:
				snake_case	    =42
				snake_case	    =field(default='toto'      ,					metadata={'help': 'help message'}   )







@dataclass
class       lowercase_					:
				snake_case	    =False
				snake_case	    =True
				snake_case	    =None







class       lowercase_					(lowercase__   ):
				snake_case	    ='titi'
				snake_case	    ='toto'







class       lowercase_					(lowercase__   ):
				snake_case	    ='titi'
				snake_case	    ='toto'
				snake_case	    =42







@dataclass
class       lowercase_					:
				snake_case	    ="toto"





				def 						__UpperCamelCase    (				self)  -> List[str]:
											a__      =BasicEnum(self.foo)







@dataclass
class       lowercase_					:
				snake_case	    ="toto"





				def 						__UpperCamelCase    (				self)  -> List[str]:
											a__      =MixedTypeEnum(self.foo)







@dataclass
class       lowercase_					:
				snake_case	    =None
				snake_case	    =field(default=lowercase__      ,					metadata={'help': 'help message'}   )
				snake_case	    =None
				snake_case	    =list_field(default=[]   )
				snake_case	    =list_field(default=[]   )







@dataclass
class       lowercase_					:
				snake_case	    =list_field(default=[]   )
				snake_case	    =list_field(default=[1, 2, 3]   )
				snake_case	    =list_field(default=['Hallo', 'Bonjour', 'Hello']   )
				snake_case	    =list_field(default=[0.1, 0.2, 0.3]   )







@dataclass
class       lowercase_					:
				snake_case	    =field()
				snake_case	    =field()
				snake_case	    =field()





				def 						__UpperCamelCase    (				self)  -> List[Any]:
											a__      =BasicEnum(self.required_enum)







@dataclass
class       lowercase_					:
				snake_case	    =42
				snake_case	    =field()
				snake_case	    =None
				snake_case	    =field(default='toto'      ,					metadata={'help': 'help message'}   )
				snake_case	    =list_field(default=['Hallo', 'Bonjour', 'Hello']   )


if is_python_no_less_than_3_10:




	@dataclass
	class       lowercase_					:
					snake_case	    =False
					snake_case	    =True
					snake_case	    =None







	@dataclass
	class       lowercase_					:
					snake_case	    =None
					snake_case	    =field(default=lowercase__      ,					metadata={'help': 'help message'}   )
					snake_case	    =None
					snake_case	    =list_field(default=[]   )
					snake_case	    =list_field(default=[]   )







class       lowercase_					(unittest.TestCase   ):





				def 						__UpperCamelCase    (				self       ,  lowercase_       ,  lowercase_)  -> int:
											self.assertEqual(len(a._actions)       ,  len(b._actions))
											for x, y in zip(a._actions       ,  b._actions):
																		a__      ={k: v for k, v in vars(lowercase_).items() if k != 'container'}
																		a__      ={k: v for k, v in vars(lowercase_).items() if k != 'container'}

																		# Choices with mixed type have custom function as "type"
																		# So we need to compare results directly for equality
																		if xx.get('choices'       ,  lowercase_) and yy.get('choices'       ,  lowercase_):
																									for expected_choice in yy["choices"] + xx["choices"]:
																																self.assertEqual(xx['type'](lowercase_)       ,  yy['type'](lowercase_))
																									del xx["type"], yy["type"]

																		self.assertEqual(lowercase_       ,  lowercase_)





				def 						__UpperCamelCase    (				self)  -> List[Any]:
											a__      =HfArgumentParser(lowercase_)

											a__      =argparse.ArgumentParser()
											expected.add_argument('--foo'       ,  type=lowercase_       ,  required=lowercase_)
											expected.add_argument('--bar'       ,  type=lowercase_       ,  required=lowercase_)
											expected.add_argument('--baz'       ,  type=lowercase_       ,  required=lowercase_)
											expected.add_argument('--flag'       ,  type=lowercase_       ,  default=lowercase_       ,  const=lowercase_       ,  nargs='?')
											self.argparsersEqual(lowercase_       ,  lowercase_)

											a__      =['--foo', '1', '--baz', 'quux', '--bar', '0.5']
											((a__)    ,     )      =parser.parse_args_into_dataclasses(lowercase_       ,  look_for_args_file=lowercase_)
											self.assertFalse(example.flag)





				def 						__UpperCamelCase    (				self)  -> Union[str, Any]:
											a__      =HfArgumentParser(lowercase_)

											a__      =argparse.ArgumentParser()
											expected.add_argument('--foo'       ,  default=42       ,  type=lowercase_)
											expected.add_argument('--baz'       ,  default='toto'       ,  type=lowercase_       ,  help='help message')
											self.argparsersEqual(lowercase_       ,  lowercase_)





				def 						__UpperCamelCase    (				self)  -> Optional[Any]:
											a__      =argparse.ArgumentParser()
											expected.add_argument('--foo'       ,  type=lowercase_       ,  default=lowercase_       ,  const=lowercase_       ,  nargs='?')
											expected.add_argument('--baz'       ,  type=lowercase_       ,  default=lowercase_       ,  const=lowercase_       ,  nargs='?')
											# A boolean no_* argument always has to come after its "default: True" regular counter-part
											# and its default must be set to False
											expected.add_argument('--no_baz'       ,  action='store_false'       ,  default=lowercase_       ,  dest='baz')
											expected.add_argument('--opt'       ,  type=lowercase_       ,  default=lowercase_)

											a__      =[WithDefaultBoolExample]
											if is_python_no_less_than_3_10:
																		dataclass_types.append(lowercase_)

											for dataclass_type in dataclass_types:
																		a__      =HfArgumentParser(lowercase_)
																		self.argparsersEqual(lowercase_       ,  lowercase_)

																		a__      =parser.parse_args([])
																		self.assertEqual(lowercase_       ,  Namespace(foo=lowercase_       ,  baz=lowercase_       ,  opt=lowercase_))

																		a__      =parser.parse_args(['--foo', '--no_baz'])
																		self.assertEqual(lowercase_       ,  Namespace(foo=lowercase_       ,  baz=lowercase_       ,  opt=lowercase_))

																		a__      =parser.parse_args(['--foo', '--baz'])
																		self.assertEqual(lowercase_       ,  Namespace(foo=lowercase_       ,  baz=lowercase_       ,  opt=lowercase_))

																		a__      =parser.parse_args(['--foo', 'True', '--baz', 'True', '--opt', 'True'])
																		self.assertEqual(lowercase_       ,  Namespace(foo=lowercase_       ,  baz=lowercase_       ,  opt=lowercase_))

																		a__      =parser.parse_args(['--foo', 'False', '--baz', 'False', '--opt', 'False'])
																		self.assertEqual(lowercase_       ,  Namespace(foo=lowercase_       ,  baz=lowercase_       ,  opt=lowercase_))





				def 						__UpperCamelCase    (				self)  -> str:
											a__      =HfArgumentParser(lowercase_)

											a__      =argparse.ArgumentParser()
											expected.add_argument(
											    '--foo'       ,  default='toto'       ,  choices=['titi', 'toto', 42]       ,  type=make_choice_type_function(['titi', 'toto', 42])       ,  )
											self.argparsersEqual(lowercase_       ,  lowercase_)

											a__      =parser.parse_args([])
											self.assertEqual(args.foo       ,  'toto')
											a__      =parser.parse_args_into_dataclasses([])[0]
											self.assertEqual(enum_ex.foo       ,  MixedTypeEnum.toto)

											a__      =parser.parse_args(['--foo', 'titi'])
											self.assertEqual(args.foo       ,  'titi')
											a__      =parser.parse_args_into_dataclasses(['--foo', 'titi'])[0]
											self.assertEqual(enum_ex.foo       ,  MixedTypeEnum.titi)

											a__      =parser.parse_args(['--foo', '42'])
											self.assertEqual(args.foo       ,  42)
											a__      =parser.parse_args_into_dataclasses(['--foo', '42'])[0]
											self.assertEqual(enum_ex.foo       ,  MixedTypeEnum.fourtytwo)





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




											@dataclass
											class       lowercase_					:
															snake_case	    ="toto"







											a__      =HfArgumentParser(lowercase_)

											a__      =argparse.ArgumentParser()
											expected.add_argument(
											    '--foo'       ,  default='toto'       ,  choices=('titi', 'toto', 42)       ,  type=make_choice_type_function(['titi', 'toto', 42])       ,  )
											self.argparsersEqual(lowercase_       ,  lowercase_)

											a__      =parser.parse_args([])
											self.assertEqual(args.foo       ,  'toto')

											a__      =parser.parse_args(['--foo', 'titi'])
											self.assertEqual(args.foo       ,  'titi')

											a__      =parser.parse_args(['--foo', '42'])
											self.assertEqual(args.foo       ,  42)





				def 						__UpperCamelCase    (				self)  -> Optional[int]:
											a__      =HfArgumentParser(lowercase_)

											a__      =argparse.ArgumentParser()
											expected.add_argument('--foo_int'       ,  nargs='+'       ,  default=[]       ,  type=lowercase_)
											expected.add_argument('--bar_int'       ,  nargs='+'       ,  default=[1, 2, 3]       ,  type=lowercase_)
											expected.add_argument('--foo_str'       ,  nargs='+'       ,  default=['Hallo', 'Bonjour', 'Hello']       ,  type=lowercase_)
											expected.add_argument('--foo_float'       ,  nargs='+'       ,  default=[0.1, 0.2, 0.3]       ,  type=lowercase_)

											self.argparsersEqual(lowercase_       ,  lowercase_)

											a__      =parser.parse_args([])
											self.assertEqual(
											    lowercase_       ,  Namespace(foo_int=[]       ,  bar_int=[1, 2, 3]       ,  foo_str=['Hallo', 'Bonjour', 'Hello']       ,  foo_float=[0.1, 0.2, 0.3])       ,  )

											a__      =parser.parse_args('--foo_int 1 --bar_int 2 3 --foo_str a b c --foo_float 0.1 0.7'.split())
											self.assertEqual(lowercase_       ,  Namespace(foo_int=[1]       ,  bar_int=[2, 3]       ,  foo_str=['a', 'b', 'c']       ,  foo_float=[0.1, 0.7]))





				def 						__UpperCamelCase    (				self)  -> Dict:
											a__      =argparse.ArgumentParser()
											expected.add_argument('--foo'       ,  default=lowercase_       ,  type=lowercase_)
											expected.add_argument('--bar'       ,  default=lowercase_       ,  type=lowercase_       ,  help='help message')
											expected.add_argument('--baz'       ,  default=lowercase_       ,  type=lowercase_)
											expected.add_argument('--ces'       ,  nargs='+'       ,  default=[]       ,  type=lowercase_)
											expected.add_argument('--des'       ,  nargs='+'       ,  default=[]       ,  type=lowercase_)

											a__      =[OptionalExample]
											if is_python_no_less_than_3_10:
																		dataclass_types.append(lowercase_)

											for dataclass_type in dataclass_types:
																		a__      =HfArgumentParser(lowercase_)

																		self.argparsersEqual(lowercase_       ,  lowercase_)

																		a__      =parser.parse_args([])
																		self.assertEqual(lowercase_       ,  Namespace(foo=lowercase_       ,  bar=lowercase_       ,  baz=lowercase_       ,  ces=[]       ,  des=[]))

																		a__      =parser.parse_args('--foo 12 --bar 3.14 --baz 42 --ces a b c --des 1 2 3'.split())
																		self.assertEqual(lowercase_       ,  Namespace(foo=12       ,  bar=3.14       ,  baz='42'       ,  ces=['a', 'b', 'c']       ,  des=[1, 2, 3]))





				def 						__UpperCamelCase    (				self)  -> str:
											a__      =HfArgumentParser(lowercase_)

											a__      =argparse.ArgumentParser()
											expected.add_argument('--required_list'       ,  nargs='+'       ,  type=lowercase_       ,  required=lowercase_)
											expected.add_argument('--required_str'       ,  type=lowercase_       ,  required=lowercase_)
											expected.add_argument(
											    '--required_enum'       ,  type=make_choice_type_function(['titi', 'toto'])       ,  choices=['titi', 'toto']       ,  required=lowercase_       ,  )
											self.argparsersEqual(lowercase_       ,  lowercase_)





				def 						__UpperCamelCase    (				self)  -> str:
											a__      =HfArgumentParser(lowercase_)

											a__      =argparse.ArgumentParser()
											expected.add_argument('--foo'       ,  type=lowercase_       ,  required=lowercase_)
											expected.add_argument(
											    '--required_enum'       ,  type=make_choice_type_function(['titi', 'toto'])       ,  choices=['titi', 'toto']       ,  required=lowercase_       ,  )
											expected.add_argument('--opt'       ,  type=lowercase_       ,  default=lowercase_)
											expected.add_argument('--baz'       ,  default='toto'       ,  type=lowercase_       ,  help='help message')
											expected.add_argument('--foo_str'       ,  nargs='+'       ,  default=['Hallo', 'Bonjour', 'Hello']       ,  type=lowercase_)
											self.argparsersEqual(lowercase_       ,  lowercase_)





				def 						__UpperCamelCase    (				self)  -> List[Any]:
											a__      =HfArgumentParser(lowercase_)

											a__      ={
											    'foo': 12,
											    'bar': 3.14,
											    'baz': '42',
											    'flag': True,
											}

											a__      =parser.parse_dict(lowercase_)[0]
											a__      =BasicExample(**lowercase_)
											self.assertEqual(lowercase_       ,  lowercase_)





				def 						__UpperCamelCase    (				self)  -> Union[str, Any]:
											a__      =HfArgumentParser(lowercase_)

											a__      ={
											    'foo': 12,
											    'bar': 3.14,
											    'baz': '42',
											    'flag': True,
											    'extra': 42,
											}

											self.assertRaises(lowercase_       ,  parser.parse_dict       ,  lowercase_       ,  allow_extra_keys=lowercase_)





				def 						__UpperCamelCase    (				self)  -> List[Any]:
											a__      =HfArgumentParser(lowercase_)

											a__      ={
											    'foo': 12,
											    'bar': 3.14,
											    'baz': '42',
											    'flag': True,
											}
											with tempfile.TemporaryDirectory() as tmp_dir:
																		a__      =os.path.join(lowercase_       ,  'temp_json')
																		os.mkdir(lowercase_)
																		with open(temp_local_path + '.json'       ,  'w+') as f:
																									json.dump(lowercase_       ,  lowercase_)
																		a__      =parser.parse_yaml_file(Path(temp_local_path + '.json'))[0]

											a__      =BasicExample(**lowercase_)
											self.assertEqual(lowercase_       ,  lowercase_)





				def 						__UpperCamelCase    (				self)  -> Any:
											a__      =HfArgumentParser(lowercase_)

											a__      ={
											    'foo': 12,
											    'bar': 3.14,
											    'baz': '42',
											    'flag': True,
											}
											with tempfile.TemporaryDirectory() as tmp_dir:
																		a__      =os.path.join(lowercase_       ,  'temp_yaml')
																		os.mkdir(lowercase_)
																		with open(temp_local_path + '.yaml'       ,  'w+') as f:
																									yaml.dump(lowercase_       ,  lowercase_)
																		a__      =parser.parse_yaml_file(Path(temp_local_path + '.yaml'))[0]
											a__      =BasicExample(**lowercase_)
											self.assertEqual(lowercase_       ,  lowercase_)





				def 						__UpperCamelCase    (				self)  -> Union[str, Any]:
											a__      =HfArgumentParser(lowercase_)
											self.assertIsNotNone(lowercase_)

