





from __future__ import annotations

from collections.abc import Callable





def   _lowercase       (    _UpperCAmelCase      ,   _UpperCAmelCase      ,   _UpperCAmelCase      ,   _UpperCAmelCase = 1_00      ,   )    ->	float:
				lowerCamelCase									=x_start
				lowerCamelCase									=fnc(_UpperCAmelCase					)
				lowerCamelCase									=0.0

				for _ in range(_UpperCAmelCase					):
								# Approximates small segments of curve as linear and solve
								# for trapezoidal area
								lowerCamelCase									=(x_end - x_start) / steps + xa
								lowerCamelCase									=fnc(_UpperCAmelCase					)
								area += abs(fxa + fxa					) * (xa - xa) / 2

								# Increment step
								lowerCamelCase									=xa
								lowerCamelCase									=fxa
				return area


if __name__ == "__main__":





							def   _lowercase       (    _UpperCAmelCase					)    ->	Any:
											return x**3

							print('''f(x) = x^3''')
							print('''The area between the curve, x = -10, x = 10 and the x axis is:''')
							UpperCAmelCase__    :      int       					=10
							while i <= 10_00_00:
														UpperCAmelCase__    :      int       					=trapezoidal_area(f, -5, 5, i)
														print(F"with {i} steps: {area}")
														i *= 10












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase__    :      Optional[Any]       					={
    '''configuration_rwkv''': ['''RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RwkvConfig''', '''RwkvOnnxConfig'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Optional[Any]       					=[
							    '''RWKV_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''RwkvForCausalLM''',
							    '''RwkvModel''',
							    '''RwkvPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_rwkv import (
														    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
														    RwkvForCausalLM,
														    RwkvModel,
														    RwkvPreTrainedModel,
														)
else:
							import sys

							UpperCAmelCase__    :      int       					=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





