


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


SCREAMING_SNAKE_CASE_      :			Union[str, Any]		  =      get_logger(__name__)



def    SCREAMING_SNAKE_CASE							(			snake_case       )		->						Union[str, Any]:
		if version.parse(snake_case       ) < version.parse(snake_case       ):
				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(snake_case       )











from __future__ import annotations



def    SCREAMING_SNAKE_CASE							(			snake_case	,      snake_case	,      snake_case	,      snake_case       )		->						None:
		__lowercase	,			__lowercase					=    m - 1, 0
		while i >= 0 and j < n:
				if key == mat[i][j]:
						print(F"Key {key} found at row- {i + 1} column- {j + 1}"       )
						return
				if key < mat[i][j]:
						i -= 1
				else:
						j += 1
		print(F"Key {key} not found"       )



def    SCREAMING_SNAKE_CASE							(			)		->						None:
		__lowercase					=    [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
		__lowercase					=    int(input('Enter the element to be searched:'       )       )
		print(snake_case       )
		search_in_a_sorted_matrix(snake_case	,      len(snake_case       )	,      len(mat[0]       )	,      snake_case       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()




