





from __future__ import annotations

import math
from collections.abc import Callable

def       __A (     a_  :Callable[[int | float], int | float]				,    a_  :int | float				,    a_  :int | float				,    a_  :int = 1_00				,    )						->						float:
				__a	:  Union[str, Any]         =					x_start
				__a	:  int         =					fnc(a_)
				__a	:  Optional[int]         =					0.0

				for _ in range(a_):
								# Approximates curve as a sequence of linear lines and sums their length
								__a	:  Any         =					(x_end - x_start) / steps + xa
								__a	:  str         =					fnc(a_)
								length += math.hypot(xa - xa				,    fxa - fxa)

								# Increment step
								__a	:  Dict         =					xa
								__a	:  Tuple         =					fxa

				return length


if __name__ == "__main__":

		def       __A (     a_  :Optional[Any])						->						Dict:
						return math.sin(10 * x)

		print('''f(x) = sin(10 * x)''')
		print('''The length of the curve from x = -10 to x = 10 is:''')
		A	     =					10
		while i <= 100_000:
				print(F'With {i} steps: {line_length(f, -10, 10, i)}')
				i *= 10






"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A	     =					{
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					[
		    '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''InstructBlipQFormerModel''',
		    '''InstructBlipPreTrainedModel''',
		    '''InstructBlipForConditionalGeneration''',
		    '''InstructBlipVisionModel''',
		]

if TYPE_CHECKING:
		from .configuration_instructblip import (
		    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    InstructBlipConfig,
		    InstructBlipQFormerConfig,
		    InstructBlipVisionConfig,
		)
		from .processing_instructblip import InstructBlipProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_instructblip import (
				    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    InstructBlipForConditionalGeneration,
				    InstructBlipPreTrainedModel,
				    InstructBlipQFormerModel,
				    InstructBlipVisionModel,
				)

else:
		import sys

		A	     =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)