




'''simple docstring'''





_SCREAMING_SNAKE_CASE							:       Any						=			frozenset(
    [
        "prompt",
        "height",
        "width",
        "guidance_scale",
        "negative_prompt",
        "prompt_embeds",
        "negative_prompt_embeds",
        "cross_attention_kwargs",
    ]
)

_SCREAMING_SNAKE_CASE							:       List[Any]						=			frozenset(["prompt", "negative_prompt"])

_SCREAMING_SNAKE_CASE							:       Optional[Any]						=			frozenset([])

_SCREAMING_SNAKE_CASE							:       List[str]						=			frozenset(["image"])

_SCREAMING_SNAKE_CASE							:       Optional[Any]						=			frozenset(
    [
        "image",
        "height",
        "width",
        "guidance_scale",
    ]
)

_SCREAMING_SNAKE_CASE							:       Optional[int]						=			frozenset(["image"])

_SCREAMING_SNAKE_CASE							:       Any						=			frozenset(
    [
        "prompt",
        "image",
        "height",
        "width",
        "guidance_scale",
        "negative_prompt",
        "prompt_embeds",
        "negative_prompt_embeds",
    ]
)

_SCREAMING_SNAKE_CASE							:       Any						=			frozenset(["prompt", "image", "negative_prompt"])

_SCREAMING_SNAKE_CASE							:       Dict						=			frozenset(
    [
        # Text guided image variation with an image mask
        "prompt",
        "image",
        "mask_image",
        "height",
        "width",
        "guidance_scale",
        "negative_prompt",
        "prompt_embeds",
        "negative_prompt_embeds",
    ]
)

_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			frozenset(["prompt", "image", "mask_image", "negative_prompt"])

_SCREAMING_SNAKE_CASE							:       Dict						=			frozenset(
    [
        # image variation with an image mask
        "image",
        "mask_image",
        "height",
        "width",
        "guidance_scale",
    ]
)

_SCREAMING_SNAKE_CASE							:       List[Any]						=			frozenset(["image", "mask_image"])

_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			frozenset(
    [
        "example_image",
        "image",
        "mask_image",
        "height",
        "width",
        "guidance_scale",
    ]
)

_SCREAMING_SNAKE_CASE							:       Dict						=			frozenset(["example_image", "image", "mask_image"])

_SCREAMING_SNAKE_CASE							:       List[str]						=			frozenset(["class_labels"])

_SCREAMING_SNAKE_CASE							:       Optional[Any]						=			frozenset(["class_labels"])

_SCREAMING_SNAKE_CASE							:       List[Any]						=			frozenset(["batch_size"])

_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			frozenset([])

_SCREAMING_SNAKE_CASE							:       Dict						=			frozenset(["batch_size"])

_SCREAMING_SNAKE_CASE							:       int						=			frozenset([])

_SCREAMING_SNAKE_CASE							:       str						=			frozenset(
    [
        "prompt",
        "audio_length_in_s",
        "guidance_scale",
        "negative_prompt",
        "prompt_embeds",
        "negative_prompt_embeds",
        "cross_attention_kwargs",
    ]
)

_SCREAMING_SNAKE_CASE							:       Optional[int]						=			frozenset(["prompt", "negative_prompt"])
_SCREAMING_SNAKE_CASE							:       Optional[Any]						=			frozenset(["input_tokens"])

_SCREAMING_SNAKE_CASE							:       Dict						=			frozenset(["input_tokens"])










'''simple docstring'''





from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403


def 					UpperCamelCase_(     snake_case							:	str							,    snake_case							:	complex							,    snake_case							:	str = "x"							,    snake_case							:	float = 1_0**-1_0							,    snake_case							:	int = 1							,    ):

							'''simple docstring'''






							snake_case_      =				symbols(snake_case					)
							snake_case_      =				lambdify(snake_case							,    snake_case					)
							snake_case_      =				lambdify(snake_case							,    diff(snake_case							,    snake_case					)					)

							snake_case_      =				starting_point

							while True:
														if diff_function(snake_case					) != 0:
																					snake_case_      =				prev_guess - multiplicity * func(snake_case					) / diff_function(
																					    snake_case					)
														else:
																					raise ZeroDivisionError("Could not find root"					) from None

														# Precision is checked by comparing the difference of consecutive guesses
														if abs(next_guess - prev_guess					) < precision:
																					return next_guess

														snake_case_      =				next_guess


# Let's Execute
if __name__ == "__main__":
		# Find root of trigonometric function
		# Find value of pi
		print(F"The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}")

		# Find root of polynomial
		# Find fourth Root of 5
		print(F"The root of x**4 - 5 = 0 is {newton_raphson('x**4 -5', 0.4 +5j)}")

		# Find value of e
		print(
		    "The root of log(y) - 1 = 0 is ",
		    F"{newton_raphson('log(y) - 1', 2, variable='y')}",
		)

		# Exponential Roots
		print(
		    "The root of exp(x) - 1 = 0 is",
		    F"{newton_raphson('exp(x) - 1', 10, precision=0.0_0_5)}",
		)

		# Find root of cos(x)
		print(F"The root of cos(x) = 0 is {newton_raphson('cos(x)', 0)}")




