



import requests

try:
		from django.contrib.auth import authenticate, login
		from django.shortcuts import redirect, render
except ImportError:
		__magic_name__       =     __magic_name__       =     __magic_name__       =     __magic_name__       =     print





def 		__snake_case						(    _UpperCAmelCase				):
					"""simple docstring"""






					lowercase						   =       'secretKey'
					lowercase						   =       'https://www.google.com/recaptcha/api/siteverify'

					# when method is not POST, direct user to login page
					if request.method != "POST":
										return render(_UpperCAmelCase       ,			'login.html'				)

					# from the frontend, get username, password, and client_key
					lowercase						   =       request.POST.get('username'				)
					lowercase						   =       request.POST.get('password'				)
					lowercase						   =       request.POST.get('g-recaptcha-response'				)

					# post recaptcha response to Google's recaptcha api
					lowercase						   =       requests.post(_UpperCAmelCase       ,			data={'secret': secret_key, 'response': client_key}				)
					# if the recaptcha api verified our keys
					if response.json().get('success'       ,			_UpperCAmelCase				):
										# authenticate the user
										lowercase						   =       authenticate(_UpperCAmelCase       ,			username=_UpperCAmelCase       ,			password=_UpperCAmelCase				)
										if user_in_database:
															login(_UpperCAmelCase       ,			_UpperCAmelCase				)
															return redirect('/your-webpage'				)
					return render(_UpperCAmelCase       ,			'login.html'				)











import os

from packaging import version

from .. import __version__
from .accelerate_utils import apply_forward_hook
from .constants import (
    CONFIG_NAME,
    DEPRECATED_REVISION_ARGS,
    DIFFUSERS_CACHE,
    DIFFUSERS_DYNAMIC_MODULE_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    ONNX_EXTERNAL_WEIGHTS_NAME,
    ONNX_WEIGHTS_NAME,
    SAFETENSORS_WEIGHTS_NAME,
    TEXT_ENCODER_ATTN_MODULE,
    WEIGHTS_NAME,
)
from .deprecation_utils import deprecate
from .doc_utils import replace_example_docstring
from .dynamic_modules_utils import get_class_from_dynamic_module
from .hub_utils import (
    HF_HUB_OFFLINE,
    _add_variant,
    _get_model_file,
    extract_commit_hash,
    http_user_agent,
)
from .import_utils import (
    BACKENDS_MAPPING,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    DummyObject,
    OptionalDependencyNotAvailable,
    is_accelerate_available,
    is_accelerate_version,
    is_bsa_available,
    is_flax_available,
    is_ftfy_available,
    is_inflect_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_librosa_available,
    is_note_seq_available,
    is_omegaconf_available,
    is_onnx_available,
    is_safetensors_available,
    is_scipy_available,
    is_tensorboard_available,
    is_tf_available,
    is_torch_available,
    is_torch_version,
    is_torchsde_available,
    is_transformers_available,
    is_transformers_version,
    is_unidecode_available,
    is_wandb_available,
    is_xformers_available,
    requires_backends,
)
from .logging import get_logger
from .outputs import BaseOutput
from .pil_utils import PIL_INTERPOLATION, numpy_to_pil, pt_to_pil
from .torch_utils import is_compiled_module, randn_tensor


if is_torch_available():
		from .testing_utils import (
		    floats_tensor,
		    load_hf_numpy,
		    load_image,
		    load_numpy,
		    load_pt,
		    nightly,
		    parse_flag_from_env,
		    print_tensor_test,
		    require_torch_a,
		    require_torch_gpu,
		    skip_mps,
		    slow,
		    torch_all_close,
		    torch_device,
		)
		from .torch_utils import maybe_allow_in_graph

from .testing_utils import export_to_gif, export_to_video


__magic_name__       =     get_logger(__name__)





def 		__snake_case						(    _UpperCAmelCase				):
					"""simple docstring"""






					if version.parse(_UpperCAmelCase				) < version.parse(_UpperCAmelCase				):
										if "dev" in min_version:
															lowercase						   =       (
															    'This example requires a source install from HuggingFace diffusers (see '
															    '`https://huggingface.co/docs/diffusers/installation#install-from-source`),'
															)
										else:
															lowercase						   =       f"""This example requires a minimum version of {min_version},"""
										error_message += f""" but the version found is {__version__}.\n"""
										raise ImportError(_UpperCAmelCase				)






