

def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		list       ):





    """simple docstring"""


    _enforce_args(_A ,   _A       )
    if n == 0:
        return 0
    SCREAMING_SNAKE_CASE_									=						float('-inf'       )
    for i in range(1 ,   n + 1       ):
        SCREAMING_SNAKE_CASE_									=						max(
            _A ,   prices[i - 1] + naive_cut_rod_recursive(n - i ,   _A       )       )

    return max_revue


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		list       ):





    """simple docstring"""


    _enforce_args(_A ,   _A       )
    SCREAMING_SNAKE_CASE_									=						[float('-inf'       ) for _ in range(n + 1       )]
    return _top_down_cut_rod_recursive(_A ,   _A ,   _A       )


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		list ,   _SCREAMING_SNAKE_CASE					:		list       ):





    """simple docstring"""


    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(
                _A ,   prices[i - 1] + _top_down_cut_rod_recursive(n - i ,   _A ,   _A       ) ,   )

        SCREAMING_SNAKE_CASE_									=						max_revenue

    return max_rev[n]


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		list       ):





    """simple docstring"""


    _enforce_args(_A ,   _A       )

    # 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(_A ,   prices[j - 1] + max_rev[i - j]       )

        SCREAMING_SNAKE_CASE_									=						max_revenue_i

    return max_rev[n]


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		list       ):





    """simple docstring"""


    if n < 0:
        SCREAMING_SNAKE_CASE_									=						f"""n must be greater than or equal to 0. Got n = {n}"""
        raise ValueError(_A       )

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


def 					_UpperCAmelCase       (  ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						[6, 10, 12, 15, 20, 23]
    SCREAMING_SNAKE_CASE_									=						len(_A       )

    # 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(_A ,   _A       )
    SCREAMING_SNAKE_CASE_									=						bottom_up_cut_rod(_A ,   _A       )
    SCREAMING_SNAKE_CASE_									=						naive_cut_rod_recursive(_A ,   _A       )

    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()








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCamelCase__  :      Any			=    {
    "configuration_mvp": ["MVP_PRETRAINED_CONFIG_ARCHIVE_MAP", "MvpConfig", "MvpOnnxConfig"],
    "tokenization_mvp": ["MvpTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      Optional[int]			=    ["MvpTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      str			=    [
           "MVP_PRETRAINED_MODEL_ARCHIVE_LIST",
           "MvpForCausalLM",
           "MvpForConditionalGeneration",
           "MvpForQuestionAnswering",
           "MvpForSequenceClassification",
           "MvpModel",
           "MvpPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
       from .tokenization_mvp import MvpTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_mvp_fast import MvpTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mvp import (
                  MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MvpForCausalLM,
                  MvpForConditionalGeneration,
                  MvpForQuestionAnswering,
                  MvpForSequenceClassification,
                  MvpModel,
                  MvpPreTrainedModel,
              )

else:
       import sys

       UpperCamelCase__  :      Dict			=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


