




'''simple docstring'''



import unittest

from datasets import load_dataset

from transformers import load_tool

from .test_tools_common import ToolTesterMixin





class 			lowerCAmelCase      (       unittest.TestCase ,      __lowerCAmelCase):


       def 					lowerCAmelCase					(      self     )					->     str:



            '''simple docstring'''




            __snake_case			    =     load_tool('''document-question-answering'''     )
            self.tool.setup()
            __snake_case			    =     load_tool('''document-question-answering'''			,     remote=__SCREAMING_SNAKE_CASE     )


       def 					lowerCAmelCase					(      self     )					->     Optional[Any]:



            '''simple docstring'''




            __snake_case			    =     load_dataset('''hf-internal-testing/example-documents'''			,     split='''test'''     )
            __snake_case			    =     dataset[0]['''image''']

            __snake_case			    =     self.tool(__SCREAMING_SNAKE_CASE			,     '''When is the coffee break?'''     )
            self.assertEqual(__SCREAMING_SNAKE_CASE			,     '''11-14 to 11:39 a.m.'''     )


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



            '''simple docstring'''




            __snake_case			    =     load_dataset('''hf-internal-testing/example-documents'''			,     split='''test'''     )
            __snake_case			    =     dataset[0]['''image''']

            __snake_case			    =     self.remote_tool(__SCREAMING_SNAKE_CASE			,     '''When is the coffee break?'''     )
            self.assertEqual(__SCREAMING_SNAKE_CASE			,     '''11-14 to 11:39 a.m.'''     )


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



            '''simple docstring'''




            __snake_case			    =     load_dataset('''hf-internal-testing/example-documents'''			,     split='''test'''     )
            __snake_case			    =     dataset[0]['''image''']

            self.tool(document=__SCREAMING_SNAKE_CASE			,     question='''When is the coffee break?'''     )




       def 					lowerCAmelCase					(      self     )					->     Optional[int]:



            '''simple docstring'''




            __snake_case			    =     load_dataset('''hf-internal-testing/example-documents'''			,     split='''test'''     )
            __snake_case			    =     dataset[0]['''image''']

            __snake_case			    =     self.remote_tool(document=__SCREAMING_SNAKE_CASE			,     question='''When is the coffee break?'''     )
            self.assertEqual(__SCREAMING_SNAKE_CASE			,     '''11-14 to 11:39 a.m.'''     )












'''simple docstring'''



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


UpperCAmelCase_				:     int     			=						get_logger(__name__)







def 	_UpperCamelCase       (_lowerCamelCase							:   Union[str, Any]		)->      Tuple:




     '''simple docstring'''





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






