




"""simple docstring"""






import argparse
import os
import re


UpperCamelCase__						=			'''src/transformers'''

# Pattern that looks at the indentation in a line.
UpperCamelCase__						=			re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCamelCase__						=			re.compile(r'''^\s*"([^"]+)":''')
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
UpperCamelCase__						=			re.compile(r'''^\s*_import_structure\["([^"]+)"\]''')
# Pattern that matches `"key",` and puts `key` in group 0.
UpperCamelCase__						=			re.compile(r'''^\s*"([^"]+)",\s*$''')
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
UpperCamelCase__						=			re.compile(r'''\[([^\]]+)\]''')





def 							UpperCAmelCase		(		snake_case			:					Dict    ):
					_lowerCAmelCase:Dict									=  _re_indent.search(snake_case    )
					return "" if search is None else search.groups()[0]





def 							UpperCAmelCase		(		snake_case			:					List[str]      ,       snake_case			:					int=""      ,       snake_case			:					str=None      ,       snake_case			:					List[Any]=None    ):
					_lowerCAmelCase:Dict									=  0
					_lowerCAmelCase:Optional[Any]									=  code.split('''\n'''    )
					if start_prompt is not None:
										while not lines[index].startswith(snake_case    ):
															index += 1
										_lowerCAmelCase:int									=  ['''\n'''.join(lines[:index]    )]
					else:
										_lowerCAmelCase:str									=  []

					# We split into blocks until we get to the `end_prompt` (or the end of the block).
					_lowerCAmelCase:int									=  [lines[index]]
					index += 1
					while index < len(snake_case    ) and (end_prompt is None or not lines[index].startswith(snake_case    )):
										if len(lines[index]    ) > 0 and get_indent(lines[index]    ) == indent_level:
															if len(snake_case    ) > 0 and get_indent(current_block[-1]    ).startswith(indent_level + ''' '''    ):
																				current_block.append(lines[index]    )
																				blocks.append('''\n'''.join(snake_case    )    )
																				if index < len(snake_case    ) - 1:
																									_lowerCAmelCase:Tuple									=  [lines[index + 1]]
																									index += 1
																				else:
																									_lowerCAmelCase:Union[str, Any]									=  []
															else:
																				blocks.append('''\n'''.join(snake_case    )    )
																				_lowerCAmelCase:Union[str, Any]									=  [lines[index]]
										else:
															current_block.append(lines[index]    )
										index += 1

					# Adds current block if it's nonempty.
					if len(snake_case    ) > 0:
										blocks.append('''\n'''.join(snake_case    )    )

					# Add final block after end_prompt if provided.
					if end_prompt is not None and index < len(snake_case    ):
										blocks.append('''\n'''.join(lines[index:]    )    )

					return blocks





def 							UpperCAmelCase		(		snake_case			:					Optional[int]    ):

					def _inner(snake_case			:					Union[str, Any]    ):
										return key(snake_case    ).lower().replace('''_'''      ,       ''''''    )

					return _inner





def 							UpperCAmelCase		(		snake_case			:					List[str]      ,       snake_case			:					Optional[int]=None    ):

					# If no key is provided, we use a noop.
					def noop(snake_case			:					int    ):
										return x

					if key is None:
										_lowerCAmelCase:Dict									=  noop
					# Constants are all uppercase, they go first.
					_lowerCAmelCase:Any									=  [obj for obj in objects if key(snake_case    ).isupper()]
					# Classes are not all uppercase but start with a capital, they go second.
					_lowerCAmelCase:Union[str, Any]									=  [obj for obj in objects if key(snake_case    )[0].isupper() and not key(snake_case    ).isupper()]
					# Functions begin with a lowercase, they go last.
					_lowerCAmelCase:str									=  [obj for obj in objects if not key(snake_case    )[0].isupper()]

					_lowerCAmelCase:Union[str, Any]									=  ignore_underscore(snake_case    )
					return sorted(snake_case      ,       key=snake_case    ) + sorted(snake_case      ,       key=snake_case    ) + sorted(snake_case      ,       key=snake_case    )





def 							UpperCAmelCase		(		snake_case			:					str    ):

					# This inner function sort imports between [ ].
					def _replace(snake_case			:					int    ):
										_lowerCAmelCase:List[Any]									=  match.groups()[0]
										if "," not in imports:
															return F'[{imports}]'
										_lowerCAmelCase:List[Any]									=  [part.strip().replace('''"'''      ,       ''''''    ) for part in imports.split(''','''    )]
										# We will have a final empty element if the line finished with a comma.
										if len(keys[-1]    ) == 0:
															_lowerCAmelCase:Optional[Any]									=  keys[:-1]
										return "[" + ", ".join([F'"{k}"' for k in sort_objects(snake_case    )]    ) + "]"

					_lowerCAmelCase:Union[str, Any]									=  import_statement.split('''\n'''    )
					if len(snake_case    ) > 3:
										# Here we have to sort internal imports that are on several lines (one per name):
										# key: [
										#     "object1",
										#     "object2",
										#     ...
										# ]

										# We may have to ignore one or two lines on each side.
										_lowerCAmelCase:Dict									=  2 if lines[1].strip() == '''[''' else 1
										_lowerCAmelCase:Tuple									=  [(i, _re_strip_line.search(snake_case    ).groups()[0]) for i, line in enumerate(lines[idx:-idx]    )]
										_lowerCAmelCase:Optional[int]									=  sort_objects(snake_case      ,       key=lambda snake_case    : x[1]    )
										_lowerCAmelCase:Dict									=  [lines[x[0] + idx] for x in sorted_indices]
										return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]    )
					elif len(snake_case    ) == 3:
										# Here we have to sort internal imports that are on one separate line:
										# key: [
										#     "object1", "object2", ...
										# ]
										if _re_bracket_content.search(lines[1]    ) is not None:
															_lowerCAmelCase:Tuple									=  _re_bracket_content.sub(_replace      ,       lines[1]    )
										else:
															_lowerCAmelCase:Any									=  [part.strip().replace('''"'''      ,       ''''''    ) for part in lines[1].split(''','''    )]
															# We will have a final empty element if the line finished with a comma.
															if len(keys[-1]    ) == 0:
																				_lowerCAmelCase:Dict									=  keys[:-1]
															_lowerCAmelCase:Optional[Any]									=  get_indent(lines[1]    ) + ''', '''.join([F'"{k}"' for k in sort_objects(snake_case    )]    )
										return "\n".join(snake_case    )
					else:
										# Finally we have to deal with imports fitting on one line
										_lowerCAmelCase:List[str]									=  _re_bracket_content.sub(_replace      ,       snake_case    )
										return import_statement





def 							UpperCAmelCase		(		snake_case			:					Optional[int]      ,       snake_case			:					Dict=True    ):
					with open(snake_case      ,       encoding='''utf-8'''    ) as f:
										_lowerCAmelCase:Any									=  f.read()

					if "_import_structure" not in code:
										return

					# Blocks of indent level 0
					_lowerCAmelCase:List[Any]									=  split_code_in_indented_blocks(
					    snake_case      ,       start_prompt='''_import_structure = {'''      ,       end_prompt='''if TYPE_CHECKING:'''    )

					# We ignore block 0 (everything untils start_prompt) and the last block (everything after end_prompt).
					for block_idx in range(1      ,       len(snake_case    ) - 1    ):
										# Check if the block contains some `_import_structure`s thingy to sort.
										_lowerCAmelCase:Tuple									=  main_blocks[block_idx]
										_lowerCAmelCase:int									=  block.split('''\n'''    )

										# Get to the start of the imports.
										_lowerCAmelCase:Optional[int]									=  0
										while line_idx < len(snake_case    ) and "_import_structure" not in block_lines[line_idx]:
															# Skip dummy import blocks
															if "import dummy" in block_lines[line_idx]:
																				_lowerCAmelCase:Any									=  len(snake_case    )
															else:
																				line_idx += 1
										if line_idx >= len(snake_case    ):
															continue

										# Ignore beginning and last line: they don't contain anything.
										_lowerCAmelCase:List[Any]									=  '''\n'''.join(block_lines[line_idx:-1]    )
										_lowerCAmelCase:List[str]									=  get_indent(block_lines[1]    )
										# Slit the internal block into blocks of indent level 1.
										_lowerCAmelCase:Optional[Any]									=  split_code_in_indented_blocks(snake_case      ,       indent_level=snake_case    )
										# We have two categories of import key: list or _import_structure[key].append/extend
										_lowerCAmelCase:Tuple									=  _re_direct_key if '''_import_structure = {''' in block_lines[0] else _re_indirect_key
										# Grab the keys, but there is a trap: some lines are empty or just comments.
										_lowerCAmelCase:Union[str, Any]									=  [(pattern.search(snake_case    ).groups()[0] if pattern.search(snake_case    ) is not None else None) for b in internal_blocks]
										# We only sort the lines with a key.
										_lowerCAmelCase:str									=  [(i, key) for i, key in enumerate(snake_case    ) if key is not None]
										_lowerCAmelCase:List[str]									=  [x[0] for x in sorted(snake_case      ,       key=lambda snake_case    : x[1]    )]

										# We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
										_lowerCAmelCase:List[Any]									=  0
										_lowerCAmelCase:int									=  []
										for i in range(len(snake_case    )    ):
															if keys[i] is None:
																				reorderded_blocks.append(internal_blocks[i]    )
															else:
																				_lowerCAmelCase:Optional[int]									=  sort_objects_in_import(internal_blocks[sorted_indices[count]]    )
																				reorderded_blocks.append(snake_case    )
																				count += 1

        # And we put our main block back together with its first and last line.
										_lowerCAmelCase:Tuple									=  '''\n'''.join(block_lines[:line_idx] + reorderded_blocks + [block_lines[-1]]    )

					if code != "\n".join(snake_case    ):
										if check_only:
															return True
										else:
															print(F'Overwriting {file}.'    )
															with open(snake_case      ,       '''w'''      ,       encoding='''utf-8'''    ) as f:
																				f.write('''\n'''.join(snake_case    )    )





def 							UpperCAmelCase		(		snake_case			:					Tuple=True    ):
					_lowerCAmelCase:List[str]									=  []
					for root, _, files in os.walk(snake_case    ):
										if "__init__.py" in files:
															_lowerCAmelCase:List[Any]									=  sort_imports(os.path.join(snake_case      ,       '''__init__.py'''    )      ,       check_only=snake_case    )
															if result:
																				_lowerCAmelCase:List[str]									=  [os.path.join(snake_case      ,       '''__init__.py'''    )]
					if len(snake_case    ) > 0:
										raise ValueError(F'Would overwrite {len(snake_case    )} files, run `make style`.'    )


if __name__ == "__main__":
				UpperCamelCase__						=			argparse.ArgumentParser()
				parser.add_argument('''--check_only''', action='''store_true''', help='''Whether to only check or fix style.''')
				UpperCamelCase__						=			parser.parse_args()

				sort_imports_in_all_inits(check_only=args.check_only)












"""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()
UpperCamelCase__						=			logging.get_logger(__name__)





def 							UpperCAmelCase		(		snake_case			:					Optional[int]    ):
					_lowerCAmelCase:List[Any]									=  MobileNetVaConfig(layer_norm_eps=0.0_01    )

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

					_lowerCAmelCase:List[Any]									=  re.match(R'''^mobilenet_v1_([^_]*)_([^_]*)$'''      ,       snake_case    )
					if matches:
										_lowerCAmelCase:str									=  float(matches[1]    )
										_lowerCAmelCase:str									=  int(matches[2]    )

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

					return config





def 							UpperCAmelCase		(		):
					_lowerCAmelCase:Tuple									=  '''http://images.cocodataset.org/val2017/000000039769.jpg'''
					_lowerCAmelCase:Optional[Any]									=  Image.open(requests.get(snake_case      ,       stream=snake_case    ).raw    )
					return im





@torch.no_grad()
def 							UpperCAmelCase		(		snake_case			:					Any      ,       snake_case			:					Union[str, Any]      ,       snake_case			:					List[Any]      ,       snake_case			:					Any=False    ):
					_lowerCAmelCase:List[str]									=  get_mobilenet_va_config(snake_case    )

					# Load 🤗 model
					_lowerCAmelCase:Any									=  MobileNetVaForImageClassification(snake_case    ).eval()

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

					# Check outputs on an image, prepared by MobileNetV1ImageProcessor
					_lowerCAmelCase:Dict									=  MobileNetVaImageProcessor(
					    crop_size={'''width''': config.image_size, '''height''': config.image_size}      ,       size={'''shortest_edge''': config.image_size + 32}      ,       )
					_lowerCAmelCase:List[str]									=  image_processor(images=prepare_img()      ,       return_tensors='''pt'''    )
					_lowerCAmelCase:List[str]									=  model(**snake_case    )
					_lowerCAmelCase:int									=  outputs.logits

					assert logits.shape == (1, 1001)

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

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

					Path(snake_case    ).mkdir(exist_ok=snake_case    )
					print(F'Saving model {model_name} to {pytorch_dump_folder_path}'    )
					model.save_pretrained(snake_case    )
					print(F'Saving image processor to {pytorch_dump_folder_path}'    )
					image_processor.save_pretrained(snake_case    )

					if push_to_hub:
										print('''Pushing to the hub...'''    )
										_lowerCAmelCase:List[str]									=  '''google/''' + model_name
										image_processor.push_to_hub(snake_case    )
										model.push_to_hub(snake_case    )


if __name__ == "__main__":
				UpperCamelCase__						=			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.'''
				)

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






