



"""simple docstring"""







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
A    =			sys.version_info >= (3, 1_0)

def   lowerCAmelCase__			(     lowerCamelCase__=None				,      lowerCamelCase__=None			) ->							Any:
       return field(default_factory=lambda: default				,      metadata=lowerCamelCase__			)






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	int
  lowerCAmelCase_       :	float
  lowerCAmelCase_       :	str
  lowerCAmelCase_       :	bool






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	int 							=     42
  lowerCAmelCase_       :	str 							=     field(default="""toto"""   ,metadata={"""help""": """help message"""}     )






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	bool 							=     False
  lowerCAmelCase_       :	bool 							=     True
  lowerCAmelCase_       :	Optional[bool] 							=     None






class      UpperCAmelCase__		(      UpperCamelCase     ):
  lowerCAmelCase_       :	Tuple 							=     """titi"""
  lowerCAmelCase_       :	Optional[int] 							=     """toto"""






class      UpperCAmelCase__		(      UpperCamelCase     ):
  lowerCAmelCase_       :	List[str] 							=     """titi"""
  lowerCAmelCase_       :	Dict 							=     """toto"""
  lowerCAmelCase_       :	Dict 							=     42






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	BasicEnum 							=     "toto"



  def 					A_		( self  :    List[str]				)			->						Union[str, Any]:






         '''simple docstring'''

         A         =					BasicEnum(self.foo				)






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	MixedTypeEnum 							=     "toto"



  def 					A_		( self  :    int				)			->						Dict:






         '''simple docstring'''

         A         =					MixedTypeEnum(self.foo				)






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	Optional[int] 							=     None
  lowerCAmelCase_       :	Optional[float] 							=     field(default=UpperCamelCase   ,metadata={"""help""": """help message"""}     )
  lowerCAmelCase_       :	Optional[str] 							=     None
  lowerCAmelCase_       :	Optional[List[str]] 							=     list_field(default=[]     )
  lowerCAmelCase_       :	Optional[List[int]] 							=     list_field(default=[]     )






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	List[int] 							=     list_field(default=[]     )
  lowerCAmelCase_       :	List[int] 							=     list_field(default=[1, 2, 3]     )
  lowerCAmelCase_       :	List[str] 							=     list_field(default=["""Hallo""", """Bonjour""", """Hello"""]     )
  lowerCAmelCase_       :	List[float] 							=     list_field(default=[0.1, 0.2, 0.3]     )






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	List[int] 							=     field()
  lowerCAmelCase_       :	str 							=     field()
  lowerCAmelCase_       :	BasicEnum 							=     field()



  def 					A_		( self  :    Optional[Any]				)			->						int:






         '''simple docstring'''

         A         =					BasicEnum(self.required_enum				)






@dataclass
class      UpperCAmelCase__		:
  lowerCAmelCase_       :	int
  lowerCAmelCase_       :	"BasicEnum" 							=     field()
  lowerCAmelCase_       :	"Optional[bool]" 							=     None
  lowerCAmelCase_       :	"str" 							=     field(default="""toto"""   ,metadata={"""help""": """help message"""}     )
  lowerCAmelCase_       :	"List[str]" 							=     list_field(default=["""Hallo""", """Bonjour""", """Hello"""]     )


if is_python_no_less_than_3_10:






       @dataclass
       class      UpperCAmelCase__		:
         lowerCAmelCase_       :	bool 							=     False
         lowerCAmelCase_       :	bool 							=     True
         lowerCAmelCase_       :	bool | None 							=     None






       @dataclass
       class      UpperCAmelCase__		:
         lowerCAmelCase_       :	int | None 							=     None
         lowerCAmelCase_       :	float | None 							=     field(default=UpperCamelCase   ,metadata={"""help""": """help message"""}     )
         lowerCAmelCase_       :	str | None 							=     None
         lowerCAmelCase_       :	list[str] | None 							=     list_field(default=[]     )
         lowerCAmelCase_       :	list[int] | None 							=     list_field(default=[]     )






class      UpperCAmelCase__		(      unittest.TestCase     ):



  def 					A_		( self  :    Dict      ,							snake_case  :    argparse.ArgumentParser      ,							snake_case  :    argparse.ArgumentParser				)			->						str:






         '''simple docstring'''

         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(snake_case				).items() if k != 'container'}
                A         =					{k: v for k, v in vars(snake_case				).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'      ,							snake_case				) and yy.get('choices'      ,							snake_case				):
                       for expected_choice in yy["choices"] + xx["choices"]:
                              self.assertEqual(xx['type'](snake_case				)      ,							yy['type'](snake_case				)				)
                       del xx["type"], yy["type"]

                self.assertEqual(snake_case      ,							snake_case				)



  def 					A_		( self  :    str				)			->						Any:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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

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



  def 					A_		( self  :    int				)			->						Optional[Any]:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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



  def 					A_		( self  :    Any				)			->						Any:






         '''simple docstring'''

         A         =					argparse.ArgumentParser()
         expected.add_argument('--foo'      ,							type=snake_case      ,							default=snake_case      ,							const=snake_case      ,							nargs='?'				)
         expected.add_argument('--baz'      ,							type=snake_case      ,							default=snake_case      ,							const=snake_case      ,							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=snake_case      ,							dest='baz'				)
         expected.add_argument('--opt'      ,							type=snake_case      ,							default=snake_case				)

         A         =					[WithDefaultBoolExample]
         if is_python_no_less_than_3_10:
                dataclass_types.append(snake_case				)

         for dataclass_type in dataclass_types:
                A         =					HfArgumentParser(snake_case				)
                self.argparsersEqual(snake_case      ,							snake_case				)

                A         =					parser.parse_args([]				)
                self.assertEqual(snake_case      ,							Namespace(foo=snake_case      ,							baz=snake_case      ,							opt=snake_case				)				)

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

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

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

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



  def 					A_		( self  :    str				)			->						str:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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

         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 					A_		( self  :    List[str]				)			->						Tuple:






         '''simple docstring'''

         @dataclass
         class      UpperCAmelCase__		:
           lowerCAmelCase_       :	Literal["titi", "toto", 42] 							=     "toto"



         A         =					HfArgumentParser(snake_case				)

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

         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 					A_		( self  :    Union[str, Any]				)			->						Optional[int]:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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

         self.argparsersEqual(snake_case      ,							snake_case				)

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



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






         '''simple docstring'''

         A         =					argparse.ArgumentParser()
         expected.add_argument('--foo'      ,							default=snake_case      ,							type=snake_case				)
         expected.add_argument('--bar'      ,							default=snake_case      ,							type=snake_case      ,							help='help message'				)
         expected.add_argument('--baz'      ,							default=snake_case      ,							type=snake_case				)
         expected.add_argument('--ces'      ,							nargs='+'      ,							default=[]      ,							type=snake_case				)
         expected.add_argument('--des'      ,							nargs='+'      ,							default=[]      ,							type=snake_case				)

         A         =					[OptionalExample]
         if is_python_no_less_than_3_10:
                dataclass_types.append(snake_case				)

         for dataclass_type in dataclass_types:
                A         =					HfArgumentParser(snake_case				)

                self.argparsersEqual(snake_case      ,							snake_case				)

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

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



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






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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



  def 					A_		( self  :    List[str]				)			->						Optional[Any]:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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



  def 					A_		( self  :    List[str]				)			->						Optional[int]:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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

         A         =					parser.parse_dict(snake_case				)[0]
         A         =					BasicExample(**snake_case				)
         self.assertEqual(snake_case      ,							snake_case				)



  def 					A_		( self  :    List[Any]				)			->						Optional[int]:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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

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



  def 					A_		( self  :    str				)			->						List[str]:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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

         A         =					BasicExample(**snake_case				)
         self.assertEqual(snake_case      ,							snake_case				)



  def 					A_		( self  :    Dict				)			->						Tuple:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)

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



  def 					A_		( self  :    Union[str, Any]				)			->						Optional[int]:






         '''simple docstring'''

         A         =					HfArgumentParser(snake_case				)
         self.assertIsNotNone(snake_case				)








"""simple docstring"""







import argparse
import json
import re
from pathlib import Path

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import (
    MobileNetVaConfig,
    MobileNetVaForImageClassification,
    MobileNetVaImageProcessor,
    load_tf_weights_in_mobilenet_va,
)
from transformers.utils import logging


logging.set_verbosity_info()
A    =			logging.get_logger(__name__)

def   lowerCAmelCase__			(     lowerCamelCase__			) ->							Union[str, Any]:
							A         =					MobileNetVaConfig(layer_norm_eps=0.0_01			)

							if "_quant" in model_name:
														raise ValueError('Quantized models are not supported.'			)

							A         =					re.match(R'^mobilenet_v1_([^_]*)_([^_]*)$'				,      lowerCamelCase__			)
							if matches:
														A         =					float(matches[1]			)
														A         =					int(matches[2]			)

							# The TensorFlow version of MobileNetV1 predicts 1001 classes instead of
							# the usual 1000. The first class (index 0) is "background".
							A         =					1001
							A         =					'imagenet-1k-id2label.json'
							A         =					'huggingface/label-files'
							A         =					json.load(open(hf_hub_download(lowerCamelCase__				,      lowerCamelCase__				,      repo_type='dataset'			)				,      'r'			)			)
							A         =					{int(lowerCamelCase__			) + 1: v for k, v in idalabel.items()}
							A         =					'background'
							A         =					idalabel
							A         =					{v: k for k, v in idalabel.items()}

							return config

def   lowerCAmelCase__			(     ) ->							List[Any]:
							A         =					'http://images.cocodataset.org/val2017/000000039769.jpg'
							A         =					Image.open(requests.get(lowerCamelCase__				,      stream=lowerCamelCase__			).raw			)
							return im

@torch.no_grad()
def   lowerCAmelCase__			(     lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__=False			) ->							Dict:
							A         =					get_mobilenet_va_config(lowerCamelCase__			)

							# Load 🤗 model
							A         =					MobileNetVaForImageClassification(lowerCamelCase__			).eval()

							# Load weights from TensorFlow checkpoint
							load_tf_weights_in_mobilenet_va(lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__			)

							# Check outputs on an image, prepared by MobileNetV1ImageProcessor
							A         =					MobileNetVaImageProcessor(
							    crop_size={'width': config.image_size, 'height': config.image_size}				,      size={'shortest_edge': config.image_size + 32}				,      )
							A         =					image_processor(images=prepare_img()				,      return_tensors='pt'			)
							A         =					model(**lowerCamelCase__			)
							A         =					outputs.logits

							assert logits.shape == (1, 1001)

							if model_name == "mobilenet_v1_1.0_224":
														A         =					torch.tensor([-4.17_39, -1.12_33, 3.12_05]			)
							elif model_name == "mobilenet_v1_0.75_192":
														A         =					torch.tensor([-3.94_40, -2.31_41, -0.33_33]			)
							else:
														A         =					None

							if expected_logits is not None:
														assert torch.allclose(logits[0, :3]				,      lowerCamelCase__				,      atol=1E-4			)

							Path(lowerCamelCase__			).mkdir(exist_ok=lowerCamelCase__			)
							print(f"""Saving model {model_name} to {pytorch_dump_folder_path}"""			)
							model.save_pretrained(lowerCamelCase__			)
							print(f"""Saving image processor to {pytorch_dump_folder_path}"""			)
							image_processor.save_pretrained(lowerCamelCase__			)

							if push_to_hub:
														print('Pushing to the hub...'			)
														A         =					'google/' + model_name
														image_processor.push_to_hub(lowerCamelCase__			)
														model.push_to_hub(lowerCamelCase__			)


if __name__ == "__main__":
							A    =			argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    '--model_name',
							    default='mobilenet_v1_1.0_224',
							    type=str,
							    help='Name of the MobileNetV1 model you\'d like to convert. Should in the form \'mobilenet_v1_<depth>_<size>\'.',
							)
							parser.add_argument(
							    '--checkpoint_path', required=True, type=str, help='Path to the original TensorFlow checkpoint (.ckpt file).'
							)
							parser.add_argument(
							    '--pytorch_dump_folder_path', required=True, type=str, help='Path to the output PyTorch model directory.'
							)
							parser.add_argument(
							    '--push_to_hub', action='store_true', help='Whether or not to push the converted model to the 🤗 hub.'
							)

							A    =			parser.parse_args()
							convert_movilevit_checkpoint(
							    args.model_name, args.checkpoint_path, args.pytorch_dump_folder_path, args.push_to_hub
							)



