

import requests

try:
      from django.contrib.auth import authenticate, login
      from django.shortcuts import redirect, render
except ImportError:
      lowerCAmelCase__							=			lowerCAmelCase__							=			lowerCAmelCase__							=			lowerCAmelCase__							=			print
def   _lowerCAmelCase(						__A      ):
  UpperCAmelCase          =	"secretKey"
  UpperCAmelCase          =	"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
  UpperCAmelCase          =	request.POST.get("username"      )
  UpperCAmelCase          =	request.POST.get("password"      )
  UpperCAmelCase          =	request.POST.get("g-recaptcha-response"      )

  # post recaptcha response to Google's recaptcha api
  UpperCAmelCase          =	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
    UpperCAmelCase          =	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				)






