


from __future__ import annotations

import math
from collections.abc import Callable
def       UpperCAmelCase__						(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_ = 1_00							,):



     """simple docstring"""






     snake_case					=    x_start
     snake_case					=    fnc(UpperCamelCase_    )
     snake_case					=    0.0

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

          # Increment step
          snake_case					=    xa
          snake_case					=    fxa

     return length


if __name__ == "__main__":
 def       UpperCAmelCase__						(UpperCamelCase_    ):



      """simple docstring"""






      return math.sin(10 * x    )

 print("f(x) = sin(10 * x)")
 print("The length of the curve from x = -10 to x = 10 is:")
 _SCREAMING_SNAKE_CASE      :			Dict      				=   10
 while i <= 10_00_00:
  print(f'''With {i} steps: {line_length(f, -10, 10, i)}''')
  i *= 10








from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE      :			Dict      				=   logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE      :			Optional[Any]      				=   {
    "alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}

class   A__ (   snake_case__     ):







    """simple docstring"""

    __magic_name__        =		'mgp-str'
    def __init__(	self      , __snake_case=[3_2, 1_2_8]      , __snake_case=4      , __snake_case=3      , __snake_case=2_7      , __snake_case=3_8      , __snake_case=5_0_2_5_7      , __snake_case=3_0_5_2_2      , __snake_case=7_6_8      , __snake_case=1_2      , __snake_case=1_2      , __snake_case=4.0      , __snake_case=True      , __snake_case=False      , __snake_case=1E-5      , __snake_case=0.0      , __snake_case=0.0      , __snake_case=0.0      , __snake_case=False      , __snake_case=0.02      , **__snake_case      , ):
         super().__init__(**__snake_case   )

         snake_case					=    image_size
         snake_case					=    patch_size
         snake_case					=    num_channels
         snake_case					=    max_token_length
         snake_case					=    num_character_labels
         snake_case					=    num_bpe_labels
         snake_case					=    num_wordpiece_labels
         snake_case					=    hidden_size
         snake_case					=    num_hidden_layers
         snake_case					=    num_attention_heads
         snake_case					=    mlp_ratio
         snake_case					=    distilled
         snake_case					=    layer_norm_eps
         snake_case					=    drop_rate
         snake_case					=    qkv_bias
         snake_case					=    attn_drop_rate
         snake_case					=    drop_path_rate
         snake_case					=    output_aa_attentions
         snake_case					=    initializer_range




