





"""simple docstring"""




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import ast
import difflib
from collections.abc import Mapping
from typing import Any, Callable, Dict




class  _a						(      _lowerCAmelCase				):
				pass





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase=None       ,						_lowercase=False   ):
						try:
												_UpperCamelCase			:					Union[str, Any]     =    ast.parse(_lowercase   )
						except SyntaxError as e:
												print('''The code generated by the agent is not valid.\n'''       ,						_lowercase   )
												return
						if state is None:
												_UpperCamelCase			:					Any     =    {}
						_UpperCamelCase			:					Tuple     =    None
						for idx, node in enumerate(expression.body   ):
												try:
																		_UpperCamelCase			:					Tuple     =    evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   )
												except InterpretorError as e:
																		_UpperCamelCase			:					Optional[int]     =    F"""Evaluation of the code stopped at line {idx} before the end because of the following error"""
																		if chat_mode:
																								msg += (
																								    F""". Copy paste the following error message and send it back to the agent:\nI get an error: '{e}'"""
																								)
																		else:
																								msg += F""":\n{e}"""
																		print(_lowercase   )
																		break
												if line_result is not None:
																		_UpperCamelCase			:					Optional[Any]     =    line_result

						return result





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						if isinstance(_lowercase       ,						ast.Assign   ):
												# Assignement -> we evaluate the assignement which should update the state
												# We return the variable assigned as it may be used to determine the final result.
												return evaluate_assign(_lowercase       ,						_lowercase       ,						_lowercase   )
						elif isinstance(_lowercase       ,						ast.Call   ):
												# Function call -> we return the value of the function call
												return evaluate_call(_lowercase       ,						_lowercase       ,						_lowercase   )
						elif isinstance(_lowercase       ,						ast.Constant   ):
												# Constant -> just return the value
												return expression.value
						elif isinstance(_lowercase       ,						ast.Dict   ):
												# Dict -> evaluate all keys and values
												_UpperCamelCase			:					str     =    [evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   ) for k in expression.keys]
												_UpperCamelCase			:					int     =    [evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   ) for v in expression.values]
												return dict(zip(_lowercase       ,						_lowercase   )   )
						elif isinstance(_lowercase       ,						ast.Expr   ):
												# Expression -> evaluate the content
												return evaluate_ast(expression.value       ,						_lowercase       ,						_lowercase   )
						elif isinstance(_lowercase       ,						ast.For   ):
												# For loop -> execute the loop
												return evaluate_for(_lowercase       ,						_lowercase       ,						_lowercase   )
						elif isinstance(_lowercase       ,						ast.FormattedValue   ):
												# Formatted value (part of f-string) -> evaluate the content and return
												return evaluate_ast(expression.value       ,						_lowercase       ,						_lowercase   )
						elif isinstance(_lowercase       ,						ast.If   ):
												# If -> execute the right branch
												return evaluate_if(_lowercase       ,						_lowercase       ,						_lowercase   )
						elif hasattr(_lowercase       ,						'''Index'''   ) and isinstance(_lowercase       ,						ast.Index   ):
												return evaluate_ast(expression.value       ,						_lowercase       ,						_lowercase   )
						elif isinstance(_lowercase       ,						ast.JoinedStr   ):
												return "".join([str(evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   )   ) for v in expression.values]   )
						elif isinstance(_lowercase       ,						ast.List   ):
												# List -> evaluate all elements
												return [evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   ) for elt in expression.elts]
						elif isinstance(_lowercase       ,						ast.Name   ):
												# Name -> pick up the value in the state
												return evaluate_name(_lowercase       ,						_lowercase       ,						_lowercase   )
						elif isinstance(_lowercase       ,						ast.Subscript   ):
												# Subscript -> return the value of the indexing
												return evaluate_subscript(_lowercase       ,						_lowercase       ,						_lowercase   )
						else:
												# For now we refuse anything else. Let's add things as we need them.
												raise InterpretorError(F"""{expression.__class__.__name__} is not supported."""   )





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						_UpperCamelCase			:					Dict     =    assign.targets
						_UpperCamelCase			:					List[str]     =    evaluate_ast(assign.value       ,						_lowercase       ,						_lowercase   )

						if len(_lowercase   ) == 1:
												_UpperCamelCase			:					Optional[int]     =    result
						else:
												if len(_lowercase   ) != len(_lowercase   ):
																		raise InterpretorError(F"""Expected {len(_lowercase   )} values but got {len(_lowercase   )}."""   )
												for var_name, r in zip(_lowercase       ,						_lowercase   ):
																		_UpperCamelCase			:					str     =    r
						return result





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						if not isinstance(call.func       ,						ast.Name   ):
												raise InterpretorError(
												    F"""It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func} of """
												    F"""type {type(call.func   )}."""   )
						_UpperCamelCase			:					List[Any]     =    call.func.id
						if func_name not in tools:
												raise InterpretorError(
												    F"""It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func.id})."""   )

						_UpperCamelCase			:					Tuple     =    tools[func_name]
						# Todo deal with args
						_UpperCamelCase			:					List[str]     =    [evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   ) for arg in call.args]
						_UpperCamelCase			:					List[str]     =    {keyword.arg: evaluate_ast(keyword.value       ,						_lowercase       ,						_lowercase   ) for keyword in call.keywords}
						return func(*_lowercase       ,						**_lowercase   )





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						_UpperCamelCase			:					Any     =    evaluate_ast(subscript.slice       ,						_lowercase       ,						_lowercase   )
						_UpperCamelCase			:					List[Any]     =    evaluate_ast(subscript.value       ,						_lowercase       ,						_lowercase   )
						if isinstance(_lowercase       ,						(list, tuple)   ):
												return value[int(_lowercase   )]
						if index in value:
												return value[index]
						if isinstance(_lowercase       ,						_lowercase   ) and isinstance(_lowercase       ,						_lowercase   ):
												_UpperCamelCase			:					Dict     =    difflib.get_close_matches(_lowercase       ,						list(value.keys()   )   )
												if len(_lowercase   ) > 0:
																		return value[close_matches[0]]

						raise InterpretorError(F"""Could not index {value} with '{index}'."""   )





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						if name.id in state:
												return state[name.id]
						_UpperCamelCase			:					int     =    difflib.get_close_matches(name.id       ,						list(state.keys()   )   )
						if len(_lowercase   ) > 0:
												return state[close_matches[0]]
						raise InterpretorError(F"""The variable `{name.id}` is not defined."""   )





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						if len(condition.ops   ) > 1:
												raise InterpretorError('''Cannot evaluate conditions with multiple operators'''   )

						_UpperCamelCase			:					Any     =    evaluate_ast(condition.left       ,						_lowercase       ,						_lowercase   )
						_UpperCamelCase			:					Tuple     =    condition.ops[0]
						_UpperCamelCase			:					Dict     =    evaluate_ast(condition.comparators[0]       ,						_lowercase       ,						_lowercase   )

						if isinstance(_lowercase       ,						ast.Eq   ):
												return left == right
						elif isinstance(_lowercase       ,						ast.NotEq   ):
												return left != right
						elif isinstance(_lowercase       ,						ast.Lt   ):
												return left < right
						elif isinstance(_lowercase       ,						ast.LtE   ):
												return left <= right
						elif isinstance(_lowercase       ,						ast.Gt   ):
												return left > right
						elif isinstance(_lowercase       ,						ast.GtE   ):
												return left >= right
						elif isinstance(_lowercase       ,						ast.Is   ):
												return left is right
						elif isinstance(_lowercase       ,						ast.IsNot   ):
												return left is not right
						elif isinstance(_lowercase       ,						ast.In   ):
												return left in right
						elif isinstance(_lowercase       ,						ast.NotIn   ):
												return left not in right
						else:
												raise InterpretorError(F"""Operator not supported: {comparator}"""   )





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						_UpperCamelCase			:					Union[str, Any]     =    None
						if evaluate_condition(if_statement.test       ,						_lowercase       ,						_lowercase   ):
												for line in if_statement.body:
																		_UpperCamelCase			:					Union[str, Any]     =    evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   )
																		if line_result is not None:
																								_UpperCamelCase			:					Optional[Any]     =    line_result
						else:
												for line in if_statement.orelse:
																		_UpperCamelCase			:					Any     =    evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   )
																		if line_result is not None:
																								_UpperCamelCase			:					str     =    line_result
						return result






def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase   ):
						_UpperCamelCase			:					Union[str, Any]     =    None
						_UpperCamelCase			:					Union[str, Any]     =    evaluate_ast(for_loop.iter       ,						_lowercase       ,						_lowercase   )
						for counter in iterator:
												_UpperCamelCase			:					Union[str, Any]     =    counter
												for expression in for_loop.body:
																		_UpperCamelCase			:					Optional[Any]     =    evaluate_ast(_lowercase       ,						_lowercase       ,						_lowercase   )
																		if line_result is not None:
																								_UpperCamelCase			:					Union[str, Any]     =    line_result
						return result










"""simple docstring"""




import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urllib.parse import urlparse
from zipfile import ZipFile, is_zipfile

import cva
import numpy as np
import requests
import wget
from filelock import FileLock
from PIL import Image
from tqdm.auto import tqdm
from yaml import Loader, dump, load


try:
						import torch

						UpperCamelCase_           =True
except ImportError:
						UpperCamelCase_           =False


try:
						from torch.hub import _get_torch_home

						UpperCamelCase_           =_get_torch_home()
except ImportError:
						UpperCamelCase_           =os.path.expanduser(
						    os.getenv("""TORCH_HOME""", os.path.join(os.getenv("""XDG_CACHE_HOME""", """~/.cache"""), """torch"""))
						)

UpperCamelCase_           =os.path.join(torch_cache_home, """transformers""")

UpperCamelCase_           ="""https://cdn.huggingface.co"""
UpperCamelCase_           ="""https://s3.amazonaws.com/models.huggingface.co/bert"""
UpperCamelCase_           ="""/""".join(str(Path(__file__).resolve()).split("""/""")[:-1])
UpperCamelCase_           =os.path.join(PATH, """config.yaml""")
UpperCamelCase_           =os.path.join(PATH, """attributes.txt""")
UpperCamelCase_           =os.path.join(PATH, """objects.txt""")
UpperCamelCase_           =os.getenv("""PYTORCH_PRETRAINED_BERT_CACHE""", default_cache_path)
UpperCamelCase_           =os.getenv("""PYTORCH_TRANSFORMERS_CACHE""", PYTORCH_PRETRAINED_BERT_CACHE)
UpperCamelCase_           =os.getenv("""TRANSFORMERS_CACHE""", PYTORCH_TRANSFORMERS_CACHE)
UpperCamelCase_           ="""pytorch_model.bin"""
UpperCamelCase_           ="""config.yaml"""





def        a_				(							_lowercase=OBJECTS       ,						_lowercase=ATTRIBUTES   ):
						_UpperCamelCase			:					Optional[int]     =    []
						with open(_lowercase   ) as f:
												for object in f.readlines():
																		vg_classes.append(object.split(''','''   )[0].lower().strip()   )

						_UpperCamelCase			:					str     =    []
						with open(_lowercase   ) as f:
												for object in f.readlines():
																		vg_attrs.append(object.split(''','''   )[0].lower().strip()   )
						return vg_classes, vg_attrs





def        a_				(							_lowercase   ):
						_UpperCamelCase			:					int     =    OrderedDict()
						with open(_lowercase       ,						'''rb'''   ) as f:
												_UpperCamelCase			:					Dict     =    pkl.load(_lowercase   )['''model''']
						for k in copy.deepcopy(list(ckp.keys()   )   ):
												_UpperCamelCase			:					Dict     =    ckp.pop(_lowercase   )
												if isinstance(_lowercase       ,						np.ndarray   ):
																		_UpperCamelCase			:					Dict     =    torch.tensor(_lowercase   )
												else:
																		assert isinstance(_lowercase       ,						torch.tensor   ), type(_lowercase   )
												_UpperCamelCase			:					Optional[int]     =    v
						return r




class  _a						:
				UpperCamelCase								=    {}






				def __init__( self		:    List[Any], lowerCAmelCase__		:    dict, lowerCAmelCase__		:    str = "root", lowerCAmelCase__		:    Optional[int]=0							)	->      Tuple:




										'''simple docstring'''



										_UpperCamelCase			:					Union[str, Any]     =    name
										_UpperCamelCase			:					Optional[int]     =    level
										_UpperCamelCase			:					List[str]     =    {}
										for k, v in dictionary.items():
																if v is None:
																						raise ValueError()
																_UpperCamelCase			:					str     =    copy.deepcopy(lowerCAmelCase__							)
																_UpperCamelCase			:					str     =    copy.deepcopy(lowerCAmelCase__							)
																if isinstance(lowerCAmelCase__, lowerCAmelCase__							):
																						_UpperCamelCase			:					List[str]     =    Config(lowerCAmelCase__, name=lowerCAmelCase__, level=level + 1							)
																_UpperCamelCase			:					Any     =    v
																setattr(self, lowerCAmelCase__, lowerCAmelCase__							)

										_UpperCamelCase			:					Optional[Any]     =    d






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




										'''simple docstring'''



										return str(list((self._pointer.keys())							)							)






				def __setattr__( self		:    int, lowerCAmelCase__		:    List[str], lowerCAmelCase__		:    List[Any]							)	->      int:




										'''simple docstring'''



										_UpperCamelCase			:					int     =    val
										_UpperCamelCase			:					int     =    val
										_UpperCamelCase			:					List[str]     =    key.split('''.'''							)
										_UpperCamelCase			:					List[str]     =    len(lowerCAmelCase__							) - 1
										_UpperCamelCase			:					Optional[Any]     =    self._pointer
										if len(lowerCAmelCase__							) > 1:
																for i, l in enumerate(lowerCAmelCase__							):
																						if hasattr(self, lowerCAmelCase__							) and isinstance(getattr(self, lowerCAmelCase__							), lowerCAmelCase__							):
																												setattr(getattr(self, lowerCAmelCase__							), '''.'''.join(levels[i:]							), lowerCAmelCase__							)
																						if l == last_level:
																												_UpperCamelCase			:					Optional[Any]     =    val
																						else:
																												_UpperCamelCase			:					Dict     =    pointer[l]






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




										'''simple docstring'''



										return self._pointer






				def 				snake_case	( self		:    int, lowerCAmelCase__		:    List[str], lowerCAmelCase__		:    Union[str, Any]							)	->      Tuple:




										'''simple docstring'''



										with open(f"""{file_name}""", '''w'''							) as stream:
																dump(lowerCAmelCase__, lowerCAmelCase__							)






				def 				snake_case	( self		:    Tuple, lowerCAmelCase__		:    Optional[Any], lowerCAmelCase__		:    Tuple							)	->      Optional[Any]:




										'''simple docstring'''



										with open(f"""{file_name}""", '''w'''							) as stream:
																json.dump(lowerCAmelCase__, lowerCAmelCase__							)






				@staticmethod
				def 				snake_case	( lowerCAmelCase__		:    List[Any]							)	->      List[str]:




										'''simple docstring'''



										with open(lowerCAmelCase__							) as stream:
																_UpperCamelCase			:					List[str]     =    load(lowerCAmelCase__, Loader=lowerCAmelCase__							)
										return data






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




										'''simple docstring'''



										_UpperCamelCase			:					List[Any]     =    '''    '''
										if self._name != "root":
																_UpperCamelCase			:					Any     =    f"""{t * (self._level-1)}{self._name}:\n"""
										else:
																_UpperCamelCase			:					List[str]     =    ''''''
										_UpperCamelCase			:					List[Any]     =    self._level
										for i, (k, v) in enumerate(self._pointer.items()							):
																if isinstance(lowerCAmelCase__, lowerCAmelCase__							):
																						r += f"""{t * (self._level)}{v}\n"""
																						self._level += 1
																else:
																						r += f"""{t * (self._level)}{k}: {v} ({type(lowerCAmelCase__							).__name__})\n"""
																_UpperCamelCase			:					Union[str, Any]     =    level
										return r[:-1]






				@classmethod
				def 				snake_case	( cls		:    Optional[int], lowerCAmelCase__		:    str, **lowerCAmelCase__		:    Tuple							)	->      List[str]:




										'''simple docstring'''



										_UpperCamelCase   ,							_UpperCamelCase			:					int     =    cls.get_config_dict(lowerCAmelCase__, **lowerCAmelCase__							)
										return cls(lowerCAmelCase__							)






				@classmethod
				def 				snake_case	( cls		:    str, lowerCAmelCase__		:    str, **lowerCAmelCase__		:    Tuple							)	->      Tuple:




										'''simple docstring'''



										_UpperCamelCase			:					List[Any]     =    kwargs.pop('''cache_dir''', lowerCAmelCase__							)
										_UpperCamelCase			:					Optional[int]     =    kwargs.pop('''force_download''', lowerCAmelCase__							)
										_UpperCamelCase			:					List[str]     =    kwargs.pop('''resume_download''', lowerCAmelCase__							)
										_UpperCamelCase			:					str     =    kwargs.pop('''proxies''', lowerCAmelCase__							)
										_UpperCamelCase			:					Any     =    kwargs.pop('''local_files_only''', lowerCAmelCase__							)

										if os.path.isdir(lowerCAmelCase__							):
																_UpperCamelCase			:					Any     =    os.path.join(lowerCAmelCase__, lowerCAmelCase__							)
										elif os.path.isfile(lowerCAmelCase__							) or is_remote_url(lowerCAmelCase__							):
																_UpperCamelCase			:					Union[str, Any]     =    pretrained_model_name_or_path
										else:
																_UpperCamelCase			:					str     =    hf_bucket_url(lowerCAmelCase__, filename=lowerCAmelCase__, use_cdn=lowerCAmelCase__							)

										try:
																# Load from URL or cache if already cached
																_UpperCamelCase			:					Union[str, Any]     =    cached_path(
																    lowerCAmelCase__, cache_dir=lowerCAmelCase__, force_download=lowerCAmelCase__, proxies=lowerCAmelCase__, resume_download=lowerCAmelCase__, local_files_only=lowerCAmelCase__, )
																# Load config dict
																if resolved_config_file is None:
																						raise EnvironmentError

																_UpperCamelCase			:					int     =    Config.load_yaml(lowerCAmelCase__							)

										except EnvironmentError:
																_UpperCamelCase			:					List[Any]     =    '''Can\'t load config for'''
																raise EnvironmentError(lowerCAmelCase__							)

										if resolved_config_file == config_file:
																print('''loading configuration file from path'''							)
										else:
																print('''loading configuration file cache'''							)

										return Config.load_yaml(lowerCAmelCase__							), kwargs





def        a_				(							_lowercase   ):
						_UpperCamelCase			:					List[Any]     =    torch.load('''dump.pt'''       ,						map_location=in_tensor.device   )
						_UpperCamelCase			:					Tuple     =    in_tensor.numpy()
						_UpperCamelCase			:					str     =    out_tensor.numpy()[0]
						print(na.shape       ,						na[0, 0, :5]   )
						print(na.shape       ,						na[0, 0, :5]   )
						assert np.allclose(_lowercase       ,						_lowercase       ,						rtol=0.01       ,						atol=0.1   ), (
						    F"""{sum([1 for x in np.isclose(_lowercase       ,						_lowercase       ,						rtol=0.01       ,						atol=0.1   ).flatten() if x is False]   )/len(na.flatten()   )*100:.4f} %"""
						    " element-wise mismatch"
						)
						raise Exception('''tensors are all good'''   )

						# Hugging face functions below





def        a_				(							_lowercase   ):
						_UpperCamelCase			:					Dict     =    urlparse(_lowercase   )
						return parsed.scheme in ("http", "https")





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase=True   ):
						_UpperCamelCase			:					List[str]     =    CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
						_UpperCamelCase			:					Optional[int]     =    '''/''' not in model_id
						if legacy_format:
												return F"""{endpoint}/{model_id}-{filename}"""
						else:
												return F"""{endpoint}/{model_id}/{filename}"""





def        a_				(							_lowercase       ,						_lowercase       ,						_lowercase=None       ,						_lowercase=0       ,						_lowercase=None       ,						):
						_UpperCamelCase			:					str     =    '''python/{}'''.format(sys.version.split()[0]   )
						if _torch_available:
												ua += "; torch/{}".format(torch.__version__   )
						if isinstance(_lowercase       ,						_lowercase   ):
												ua += "; " + "; ".join('''{}/{}'''.format(_lowercase       ,						_lowercase   ) for k, v in user_agent.items()   )
						elif isinstance(_lowercase       ,						_lowercase   ):
												ua += "; " + user_agent
						_UpperCamelCase			:					Dict     =    {'''user-agent''': ua}
						if resume_size > 0:
												_UpperCamelCase			:					List[str]     =    '''bytes=%d-''' % (resume_size,)
						_UpperCamelCase			:					Optional[int]     =    requests.get(_lowercase       ,						stream=_lowercase       ,						proxies=_lowercase       ,						headers=_lowercase   )
						if response.status_code == 416:  # Range not satisfiable
												return
						_UpperCamelCase			:					Optional[Any]     =    response.headers.get('''Content-Length'''   )
						_UpperCamelCase			:					Any     =    resume_size + int(_lowercase   ) if content_length is not None else None
						_UpperCamelCase			:					int     =    tqdm(
						    unit='''B'''       ,						unit_scale=_lowercase       ,						total=_lowercase       ,						initial=_lowercase       ,						desc='''Downloading'''       ,						)
						for chunk in response.iter_content(chunk_size=1024   ):
												if chunk:  # filter out keep-alive new chunks
																		progress.update(len(_lowercase   )   )
																		temp_file.write(_lowercase   )
						progress.close()





def        a_				(							_lowercase       ,						_lowercase=None       ,						_lowercase=False       ,						_lowercase=None       ,						_lowercase=10       ,						_lowercase=False       ,						_lowercase=None       ,						_lowercase=False       ,						):
						if cache_dir is None:
												_UpperCamelCase			:					Any     =    TRANSFORMERS_CACHE
						if isinstance(_lowercase       ,						_lowercase   ):
												_UpperCamelCase			:					int     =    str(_lowercase   )

						os.makedirs(_lowercase       ,						exist_ok=_lowercase   )

						_UpperCamelCase			:					Optional[Any]     =    None
						if not local_files_only:
												try:
																		_UpperCamelCase			:					Optional[Any]     =    requests.head(_lowercase       ,						allow_redirects=_lowercase       ,						proxies=_lowercase       ,						timeout=_lowercase   )
																		if response.status_code == 200:
																								_UpperCamelCase			:					str     =    response.headers.get('''ETag'''   )
												except (EnvironmentError, requests.exceptions.Timeout):
																		# etag is already None
																		pass

						_UpperCamelCase			:					Optional[Any]     =    url_to_filename(_lowercase       ,						_lowercase   )

						# get cache path to put the file
						_UpperCamelCase			:					Any     =    os.path.join(_lowercase       ,						_lowercase   )

						# etag is None = we don't have a connection, or url doesn't exist, or is otherwise inaccessible.
						# try to get the last downloaded one
						if etag is None:
												if os.path.exists(_lowercase   ):
																		return cache_path
												else:
																		_UpperCamelCase			:					Dict     =    [
																		    file
																		    for file in fnmatch.filter(os.listdir(_lowercase   )       ,						filename + '''.*'''   )
																		    if not file.endswith('''.json'''   ) and not file.endswith('''.lock'''   )
																		]
																		if len(_lowercase   ) > 0:
																								return os.path.join(_lowercase       ,						matching_files[-1]   )
																		else:
																								# If files cannot be found and local_files_only=True,
																								# the models might've been found if local_files_only=False
																								# Notify the user about that
																								if local_files_only:
																														raise ValueError(
																														    '''Cannot find the requested files in the cached path and outgoing traffic has been'''
																														    ''' disabled. To enable model look-ups and downloads online, set \'local_files_only\''''
																														    ''' to False.'''   )
																								return None

    # From now on, etag is not None.
						if os.path.exists(_lowercase   ) and not force_download:
												return cache_path

						# Prevent parallel downloads of the same file with a lock.
						_UpperCamelCase			:					int     =    cache_path + '''.lock'''
						with FileLock(_lowercase   ):
												# If the download just completed while the lock was activated.
												if os.path.exists(_lowercase   ) and not force_download:
																		# Even if returning early like here, the lock will be released.
																		return cache_path

												if resume_download:
																		_UpperCamelCase			:					Any     =    cache_path + '''.incomplete'''

																		@contextmanager
																		def _resumable_file_manager():
																								with open(_lowercase       ,						'''a+b'''   ) as f:
																														yield f

																		_UpperCamelCase			:					List[str]     =    _resumable_file_manager
																		if os.path.exists(_lowercase   ):
																								_UpperCamelCase			:					str     =    os.stat(_lowercase   ).st_size
																		else:
																								_UpperCamelCase			:					Tuple     =    0
												else:
																		_UpperCamelCase			:					Tuple     =    partial(tempfile.NamedTemporaryFile       ,						dir=_lowercase       ,						delete=_lowercase   )
																		_UpperCamelCase			:					Optional[int]     =    0

												# Download to temporary file, then copy to cache dir once finished.
												# Otherwise you get corrupt cache entries if the download gets interrupted.
												with temp_file_manager() as temp_file:
																		print(
																		    '''%s not found in cache or force_download set to True, downloading to %s'''       ,						_lowercase       ,						temp_file.name       ,						)

																		http_get(
																		    _lowercase       ,						_lowercase       ,						proxies=_lowercase       ,						resume_size=_lowercase       ,						user_agent=_lowercase       ,						)

												os.replace(temp_file.name       ,						_lowercase   )

												_UpperCamelCase			:					List[str]     =    {'''url''': url, '''etag''': etag}
												_UpperCamelCase			:					List[Any]     =    cache_path + '''.json'''
												with open(_lowercase       ,						'''w'''   ) as meta_file:
																		json.dump(_lowercase       ,						_lowercase   )

						return cache_path





def        a_				(							_lowercase       ,						_lowercase=None   ):
						_UpperCamelCase			:					str     =    url.encode('''utf-8'''   )
						_UpperCamelCase			:					Any     =    shaaaa(_lowercase   )
						_UpperCamelCase			:					Union[str, Any]     =    url_hash.hexdigest()

						if etag:
												_UpperCamelCase			:					List[Any]     =    etag.encode('''utf-8'''   )
												_UpperCamelCase			:					Union[str, Any]     =    shaaaa(_lowercase   )
												filename += "." + etag_hash.hexdigest()

						if url.endswith('''.h5'''   ):
												filename += ".h5"

						return filename





def        a_				(							_lowercase       ,						_lowercase=None       ,						_lowercase=False       ,						_lowercase=None       ,						_lowercase=False       ,						_lowercase=None       ,						_lowercase=False       ,						_lowercase=False       ,						_lowercase=False       ,						):
						if cache_dir is None:
												_UpperCamelCase			:					Union[str, Any]     =    TRANSFORMERS_CACHE
						if isinstance(_lowercase       ,						_lowercase   ):
												_UpperCamelCase			:					Tuple     =    str(_lowercase   )
						if isinstance(_lowercase       ,						_lowercase   ):
												_UpperCamelCase			:					str     =    str(_lowercase   )

						if is_remote_url(_lowercase   ):
												# URL, so get it from the cache (downloading if necessary)
												_UpperCamelCase			:					Optional[Any]     =    get_from_cache(
												    _lowercase       ,						cache_dir=_lowercase       ,						force_download=_lowercase       ,						proxies=_lowercase       ,						resume_download=_lowercase       ,						user_agent=_lowercase       ,						local_files_only=_lowercase       ,						)
						elif os.path.exists(_lowercase   ):
												# File, and it exists.
												_UpperCamelCase			:					List[Any]     =    url_or_filename
						elif urlparse(_lowercase   ).scheme == "":
												# File, but it doesn't exist.
												raise EnvironmentError('''file {} not found'''.format(_lowercase   )   )
						else:
												# Something unknown
												raise ValueError('''unable to parse {} as a URL or as a local path'''.format(_lowercase   )   )

						if extract_compressed_file:
												if not is_zipfile(_lowercase   ) and not tarfile.is_tarfile(_lowercase   ):
																		return output_path

												# Path where we extract compressed archives
												# We avoid '.' in dir name and add "-extracted" at the end: "./model.zip" => "./model-zip-extracted/"
												_UpperCamelCase   ,							_UpperCamelCase			:					str     =    os.path.split(_lowercase   )
												_UpperCamelCase			:					str     =    output_file.replace('''.'''       ,						'''-'''   ) + '''-extracted'''
												_UpperCamelCase			:					Tuple     =    os.path.join(_lowercase       ,						_lowercase   )

												if os.path.isdir(_lowercase   ) and os.listdir(_lowercase   ) and not force_extract:
																		return output_path_extracted

												# Prevent parallel extractions
												_UpperCamelCase			:					Optional[int]     =    output_path + '''.lock'''
												with FileLock(_lowercase   ):
																		shutil.rmtree(_lowercase       ,						ignore_errors=_lowercase   )
																		os.makedirs(_lowercase   )
																		if is_zipfile(_lowercase   ):
																								with ZipFile(_lowercase       ,						'''r'''   ) as zip_file:
																														zip_file.extractall(_lowercase   )
																														zip_file.close()
																		elif tarfile.is_tarfile(_lowercase   ):
																								_UpperCamelCase			:					List[Any]     =    tarfile.open(_lowercase   )
																								tar_file.extractall(_lowercase   )
																								tar_file.close()
																		else:
																								raise EnvironmentError('''Archive format of {} could not be identified'''.format(_lowercase   )   )

												return output_path_extracted

						return output_path





def        a_				(							_lowercase       ,						_lowercase=","   ):
						assert isinstance(_lowercase       ,						_lowercase   )
						if os.path.isfile(_lowercase   ):
												with open(_lowercase   ) as f:
																		_UpperCamelCase			:					int     =    eval(f.read()   )
						else:
												_UpperCamelCase			:					List[str]     =    requests.get(_lowercase   )
												try:
																		_UpperCamelCase			:					List[str]     =    requests.json()
												except Exception:
																		_UpperCamelCase			:					Tuple     =    req.content.decode()
																		assert data is not None, "could not connect"
																		try:
																								_UpperCamelCase			:					int     =    eval(_lowercase   )
																		except Exception:
																								_UpperCamelCase			:					Union[str, Any]     =    data.split('''\n'''   )
												req.close()
						return data





def        a_				(							_lowercase   ):
						_UpperCamelCase			:					Union[str, Any]     =    requests.get(_lowercase   )
						_UpperCamelCase			:					List[Any]     =    np.array(Image.open(BytesIO(response.content   )   )   )
						return img





def        a_				(							_lowercase   ):
						_UpperCamelCase			:					int     =    url.split('''/'''   )[-1]
						if fn not in os.listdir(os.getcwd()   ):
												wget.download(_lowercase   )
						with open(_lowercase       ,						'''rb'''   ) as stream:
												_UpperCamelCase			:					Tuple     =    pkl.load(_lowercase   )
						_UpperCamelCase			:					Dict     =    weights.pop('''model'''   )
						_UpperCamelCase			:					Dict     =    {}
						for k, v in model.items():
												_UpperCamelCase			:					Tuple     =    torch.from_numpy(_lowercase   )
												if "running_var" in k:
																		_UpperCamelCase			:					List[Any]     =    torch.tensor([0]   )
																		_UpperCamelCase			:					List[Any]     =    k.replace('''running_var'''       ,						'''num_batches_tracked'''   )
																		_UpperCamelCase			:					Dict     =    zero
						return new





def        a_				(							):
						print(F"""{os.path.abspath(os.path.join(_lowercase       ,						os.pardir   )   )}/demo.ipynb"""   )





def        a_				(							_lowercase       ,						_lowercase="RGB"   ):
						assert isinstance(_lowercase       ,						_lowercase   )
						if os.path.isfile(_lowercase   ):
												_UpperCamelCase			:					Tuple     =    cva.imread(_lowercase   )
						else:
												_UpperCamelCase			:					List[str]     =    get_image_from_url(_lowercase   )
												assert img is not None, F"""could not connect to: {im}"""
						_UpperCamelCase			:					Any     =    cva.cvtColor(_lowercase       ,						cva.COLOR_BGR2RGB   )
						if input_format == "RGB":
												_UpperCamelCase			:					List[Any]     =    img[:, :, ::-1]
						return img






def        a_				(							_lowercase       ,						_lowercase=1   ):
						return (images[i : i + batch] for i in range(0       ,						len(_lowercase   )       ,						_lowercase   ))



