
from collections import OrderedDict
from typing import List, Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_A   =			logging.get_logger(__name__)

_A   =			{
    "google/efficientnet-b7": "https://huggingface.co/google/efficientnet-b7/resolve/main/config.json",
}







class 					lowerCamelCase		(  A_  ):
     UpperCAmelCase__    :							Dict									=		"efficientnet"





     def __init__(self				:   str    ,   _A				:   List[str] = 3    ,   _A				:   Tuple = 6_0_0    ,   _A				:   Union[str, Any] = 2.0    ,   _A				:   Tuple = 3.1    ,   _A				:   Optional[Any] = 8    ,   _A				:   Union[str, Any] = [3, 3, 5, 3, 5, 5, 3]    ,   _A				:   Dict = [3_2, 1_6, 2_4, 4_0, 8_0, 1_1_2, 1_9_2]    ,   _A				:   str = [1_6, 2_4, 4_0, 8_0, 1_1_2, 1_9_2, 3_2_0]    ,   _A				:   Tuple = []    ,   _A				:   str = [1, 2, 2, 2, 1, 2, 1]    ,   _A				:   Union[str, Any] = [1, 2, 2, 3, 3, 4, 1]    ,   _A				:   Union[str, Any] = [1, 6, 6, 6, 6, 6, 6]    ,   _A				:   Any = 0.25    ,   _A				:   str = "swish"    ,   _A				:   List[str] = 2_5_6_0    ,   _A				:   Optional[int] = "mean"    ,   _A				:   Optional[Any] = 0.02    ,   _A				:   Any = 0.0_01    ,   _A				:   List[Any] = 0.99    ,   _A				:   List[Any] = 0.5    ,   _A				:   Optional[int] = 0.2    ,   **_A				:   List[Any]    ,   )						->						int:
         super().__init__(**lowerCamelCase_       )

         snake_case								= num_channels
         snake_case								= image_size
         snake_case								= width_coefficient
         snake_case								= depth_coefficient
         snake_case								= depth_divisor
         snake_case								= kernel_sizes
         snake_case								= in_channels
         snake_case								= out_channels
         snake_case								= depthwise_padding
         snake_case								= strides
         snake_case								= num_block_repeats
         snake_case								= expand_ratios
         snake_case								= squeeze_expansion_ratio
         snake_case								= hidden_act
         snake_case								= hidden_dim
         snake_case								= pooling_type
         snake_case								= initializer_range
         snake_case								= batch_norm_eps
         snake_case								= batch_norm_momentum
         snake_case								= dropout_rate
         snake_case								= drop_connect_rate
         snake_case								= sum(lowerCamelCase_       ) * 4







class 					lowerCamelCase		(  A_  ):
     UpperCAmelCase__    :							str									=		version.parse("1.11"  )





     @property
     def 		UpperCAmelCase(self				:   Tuple       )						->						Optional[int]:
         return OrderedDict(
             [
                 ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
             ]       )





     @property
     def 		UpperCAmelCase(self				:   Dict       )						->						Optional[Any]:
         return 1E-5




from collections import defaultdict







class 					lowerCamelCase		:





     def __init__(self				:   Tuple    ,   _A				:   Optional[int]    ,   _A				:   List[str]       )						->						Union[str, Any]:
         snake_case								= total  # total no of tasks (N)

         # DP table will have a dimension of (2^M)*N
         # initially all values are set to -1
         snake_case								= [
             [-1 for i in range(total + 1       )] for j in range(2 ** len(_A       )       )
         ]

         snake_case								= defaultdict(_A       )  # stores the list of persons for each task

         # final_mask is used to check if all persons are included by setting all bits
         # to 1
         snake_case								= (1 << len(_A       )) - 1





     def 		UpperCAmelCase(self				:   str    ,   _A				:   Optional[Any]    ,   _A				:   List[Any]       )						->						str:
         # if mask == self.finalmask all persons are distributed tasks, return 1
         if mask == self.final_mask:
             return 1

         # if not everyone gets the task and no more tasks are available, return 0
         if task_no > self.total_tasks:
             return 0

         # if case already considered
         if self.dp[mask][task_no] != -1:
             return self.dp[mask][task_no]

         # Number of ways when we don't this task in the arrangement
         snake_case								= self.count_ways_until(_A    ,   task_no + 1       )

         # now assign the tasks one by one to all possible persons and recursively
         # assign for the remaining tasks.
         if task_no in self.task:
             for p in self.task[task_no]:
                 # if p is already given a task
                 if mask & (1 << p):
                     continue

                 # assign this task to p and change the mask value. And recursively
                 # assign tasks with the new mask value.
                 total_ways_util += self.count_ways_until(mask | (1 << p)    ,   task_no + 1       )

        # save the value.
         snake_case								= total_ways_util

         return self.dp[mask][task_no]





     def 		UpperCAmelCase(self				:   Any    ,   _A				:   Dict       )						->						Optional[Any]:
         # Store the list of persons for each task
         for i in range(len(_A       )       ):
             for j in task_performed[i]:
                 self.task[j].append(_A       )

        # call the function to fill the DP table, final answer is stored in dp[0][1]
         return self.count_ways_until(0    ,   1       )


if __name__ == "__main__":
   _A   =			5  # total no of tasks (the value of N)

   # the list of tasks that can be done by M persons.
   _A   =			[[1, 3, 4], [1, 2, 5], [3, 4]]
   print(
       AssignmentUsingBitmask(task_performed, total_tasks).count_no_of_ways(
           task_performed
       )
   )

