





'''simple docstring'''

def lowerCamelCase						(     __lowerCamelCase :    int					,       __lowerCamelCase :    list    )						->Union[str, Any]:
    _enforce_args(__lowerCamelCase					,       __lowerCamelCase    )
    if n == 0:
        return 0
    _SCREAMING_SNAKE_CASE									=			float("""-inf"""    )
    for i in range(1					,       n + 1    ):
        _SCREAMING_SNAKE_CASE									=			max(
            __lowerCamelCase					,       prices[i - 1] + naive_cut_rod_recursive(n - i					,       __lowerCamelCase    )    )

    return max_revue





def lowerCamelCase						(     __lowerCamelCase :    int					,       __lowerCamelCase :    list    )						->Optional[Any]:
    _enforce_args(__lowerCamelCase					,       __lowerCamelCase    )
    _SCREAMING_SNAKE_CASE									=			[float("""-inf"""    ) for _ in range(n + 1    )]
    return _top_down_cut_rod_recursive(__lowerCamelCase					,       __lowerCamelCase					,       __lowerCamelCase    )





def lowerCamelCase						(     __lowerCamelCase :    int					,       __lowerCamelCase :    list					,       __lowerCamelCase :    list    )						->Tuple:
    if max_rev[n] >= 0:
        return max_rev[n]
    elif n == 0:
        return 0
    else:
        _SCREAMING_SNAKE_CASE									=			float("""-inf"""    )
        for i in range(1					,       n + 1    ):
            _SCREAMING_SNAKE_CASE									=			max(
                __lowerCamelCase					,       prices[i - 1] + _top_down_cut_rod_recursive(n - i					,       __lowerCamelCase					,       __lowerCamelCase    )					,       )

        _SCREAMING_SNAKE_CASE									=			max_revenue

    return max_rev[n]





def lowerCamelCase						(     __lowerCamelCase :    int					,       __lowerCamelCase :    list    )						->Union[str, Any]:
    _enforce_args(__lowerCamelCase					,       __lowerCamelCase    )

    # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
    # length 0.
    _SCREAMING_SNAKE_CASE									=			[float("""-inf"""    ) for _ in range(n + 1    )]
    _SCREAMING_SNAKE_CASE									=			0

    for i in range(1					,       n + 1    ):
        _SCREAMING_SNAKE_CASE									=			max_rev[i]
        for j in range(1					,       i + 1    ):
            _SCREAMING_SNAKE_CASE									=			max(__lowerCamelCase					,       prices[j - 1] + max_rev[i - j]    )

        _SCREAMING_SNAKE_CASE									=			max_revenue_i

    return max_rev[n]





def lowerCamelCase						(     __lowerCamelCase :    int					,       __lowerCamelCase :    list    )						->int:
    if n < 0:
        _SCREAMING_SNAKE_CASE									=			F'n must be greater than or equal to 0. Got n = {n}'
        raise ValueError(__lowerCamelCase    )

    if n > len(__lowerCamelCase    ):
        _SCREAMING_SNAKE_CASE									=			(
            """Each integral piece of rod must have a corresponding price. """
            F'Got n = {n} but length of prices = {len(__lowerCamelCase    )}'
        )
        raise ValueError(__lowerCamelCase    )





def lowerCamelCase						(     )						->Tuple:
    _SCREAMING_SNAKE_CASE									=			[6, 10, 12, 15, 20, 23]
    _SCREAMING_SNAKE_CASE									=			len(__lowerCamelCase    )

    # the best revenue comes from cutting the rod into 6 pieces, each
    # of length 1 resulting in a revenue of 6 * 6 = 36.
    _SCREAMING_SNAKE_CASE									=			36

    _SCREAMING_SNAKE_CASE									=			top_down_cut_rod(__lowerCamelCase					,       __lowerCamelCase    )
    _SCREAMING_SNAKE_CASE									=			bottom_up_cut_rod(__lowerCamelCase					,       __lowerCamelCase    )
    _SCREAMING_SNAKE_CASE									=			naive_cut_rod_recursive(__lowerCamelCase					,       __lowerCamelCase    )

    assert expected_max_revenue == max_rev_top_down
    assert max_rev_top_down == max_rev_bottom_up
    assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
      main()










'''simple docstring'''

import os

from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home


lowercase_					= HUGGINGFACE_HUB_CACHE


lowercase_					= """config.json"""
lowercase_					= """diffusion_pytorch_model.bin"""
lowercase_					= """diffusion_flax_model.msgpack"""
lowercase_					= """model.onnx"""
lowercase_					= """diffusion_pytorch_model.safetensors"""
lowercase_					= """weights.pb"""
lowercase_					= """https://huggingface.co"""
lowercase_					= default_cache_path
lowercase_					= """diffusers_modules"""
lowercase_					= os.getenv("""HF_MODULES_CACHE""", os.path.join(hf_cache_home, """modules"""))
lowercase_					= ["""fp16""", """non-ema"""]
lowercase_					= """.self_attn"""



