
"""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


SCREAMING_SNAKE_CASE_			      =					get_logger(__name__)

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


"""simple docstring"""
def 				lowercase      (_lowerCAmelCase		):
						# must be
						__lowerCAmelCase        =       [list(_lowerCAmelCase		) for row in matrix]
						if matrix and isinstance(_lowerCAmelCase				,  _lowerCAmelCase		):
												if isinstance(matrix[0]				,  _lowerCAmelCase		):
																		__lowerCAmelCase        =       0
																		for row in matrix:
																								if prev_len == 0:
																														__lowerCAmelCase        =       len(_lowerCAmelCase		)
																														__lowerCAmelCase        =       True
																								else:
																														__lowerCAmelCase        =       prev_len == len(_lowerCAmelCase		)
												else:
																		__lowerCAmelCase        =       True
						else:
												__lowerCAmelCase        =       False

						return result

def 				lowercase      (_lowerCAmelCase		):
						if check_matrix(_lowerCAmelCase		) and len(_lowerCAmelCase		) > 0:
												__lowerCAmelCase        =       [list(_lowerCAmelCase		) for row in a]
												__lowerCAmelCase        =       len(_lowerCAmelCase		)
												if isinstance(a[0]				,  _lowerCAmelCase		):
																		__lowerCAmelCase        =       len(a[0]		)
												else:
																		for dat in a:
																								print(_lowerCAmelCase		)
																		return

												# horizotal printing increasing
												for i in range(0				,  _lowerCAmelCase		):
																		print(a[0][i]		)
												# vertical printing down
												for i in range(1				,  _lowerCAmelCase		):
																		print(a[i][mat_col - 1]		)
												# horizotal printing decreasing
												if mat_row > 1:
																		for i in range(mat_col - 2				,  -1				,  -1		):
																								print(a[mat_row - 1][i]		)
        # vertical printing up
												for i in range(mat_row - 2				,  0				,  -1		):
																		print(a[i][0]		)
												__lowerCAmelCase        =       [row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
												if len(_lowerCAmelCase		) > 0:
																		spiral_print_clockwise(_lowerCAmelCase		)
												else:
																		return
						else:
												print("""Not a valid matrix"""		)
												return

def 				lowercase      (_lowerCAmelCase		):
						if matrix:
												return list(matrix.pop(0		)		) + spiral_traversal(list(zip(*_lowerCAmelCase		)		)[::-1]		)
						else:
												return []


# driver code
if __name__ == "__main__":
			import doctest

			doctest.testmod()

			SCREAMING_SNAKE_CASE_			      =					[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
			spiral_print_clockwise(a)
