


'''simple docstring'''






from typing import List

import numpy as np





def lowerCamelCase__      (						__lowerCamelCase	:							dict							):







   '''simple docstring'''




   _UpperCAmelCase       :       str							   ={key: len(__lowerCamelCase							) for key, value in gen_kwargs.items() if isinstance(__lowerCamelCase	,   __lowerCamelCase							)}
   if len(set(lists_lengths.values()							)							) > 1:
      raise RuntimeError(
          (
              'Sharding is ambiguous for this dataset: '
              + 'we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'
              + '\n'.join(f"\t- key {key} has length {length}" for key, length in lists_lengths.items()							)
              + '\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '
              + 'and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'
          )							)
   _UpperCAmelCase       :       Dict							   =max(lists_lengths.values()	,   default=0							)
   return max(1	,   __lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							int	,   __lowerCamelCase	:							int							):







   '''simple docstring'''




   _UpperCAmelCase       :       Optional[int]							   =[]
   for group_idx in range(__lowerCamelCase							):
      _UpperCAmelCase       :       List[Any]							   =num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
      if num_shards_to_add == 0:
         break
      _UpperCAmelCase       :       List[Any]							   =shards_indices_per_group[-1].stop if shards_indices_per_group else 0
      _UpperCAmelCase       :       Tuple							   =range(__lowerCamelCase	,   start + num_shards_to_add							)
      shards_indices_per_group.append(__lowerCamelCase							)
   return shards_indices_per_group





def lowerCamelCase__      (						__lowerCamelCase	:							dict	,   __lowerCamelCase	:							int							):







   '''simple docstring'''




   _UpperCAmelCase       :       List[Any]							   =_number_of_shards_in_gen_kwargs(__lowerCamelCase							)
   if num_shards == 1:
      return [dict(__lowerCamelCase							)]
   else:
      _UpperCAmelCase       :       Union[str, Any]							   =_distribute_shards(num_shards=__lowerCamelCase	,   max_num_jobs=__lowerCamelCase							)
      return [
          {
              key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
              if isinstance(__lowerCamelCase	,   __lowerCamelCase							)
              else value
              for key, value in gen_kwargs.items()
          }
          for group_idx in range(len(__lowerCamelCase							)							)
      ]





def lowerCamelCase__      (						__lowerCamelCase	:							List[dict]							):







   '''simple docstring'''




   return {
       key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
       if isinstance(gen_kwargs_list[0][key]	,   __lowerCamelCase							)
       else gen_kwargs_list[0][key]
       for key in gen_kwargs_list[0]
   }





def lowerCamelCase__      (						__lowerCamelCase	:							np.random.Generator	,   __lowerCamelCase	:							dict							):







   '''simple docstring'''




   _UpperCAmelCase       :       int							   ={len(__lowerCamelCase							) for value in gen_kwargs.values() if isinstance(__lowerCamelCase	,   __lowerCamelCase							)}
   _UpperCAmelCase       :       List[Any]							   ={}
   for size in list_sizes:
      _UpperCAmelCase       :       List[Any]							   =list(range(__lowerCamelCase							)							)
      rng.shuffle(indices_per_size[size]							)
   # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
   _UpperCAmelCase       :       Any							   =dict(__lowerCamelCase							)
   for key, value in shuffled_kwargs.items():
      if isinstance(__lowerCamelCase	,   __lowerCamelCase							):
         _UpperCAmelCase       :       Optional[int]							   =[value[i] for i in indices_per_size[len(__lowerCamelCase							)]]
   return shuffled_kwargs





'''simple docstring'''






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


lowercase							=logging.get_logger(__name__)

lowercase							={
    'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="glpn"






       def __init__(      self  ,							snake_case=3  ,							snake_case=4  ,							snake_case=[2, 2, 2, 2]  ,							snake_case=[8, 4, 2, 1]  ,							snake_case=[3_2, 6_4, 1_6_0, 2_5_6]  ,							snake_case=[7, 3, 3, 3]  ,							snake_case=[4, 2, 2, 2]  ,							snake_case=[1, 2, 5, 8]  ,							snake_case=[4, 4, 4, 4]  ,							snake_case="gelu"  ,							snake_case=0.0  ,							snake_case=0.0  ,							snake_case=0.02  ,							snake_case=0.1  ,							snake_case=1E-6  ,							snake_case=6_4  ,							snake_case=1_0  ,							snake_case=-1  ,							**snake_case  ,							)						->  Tuple:




          '''simple docstring'''
          super().__init__(**snake_case)

          _UpperCAmelCase       :       Any							   =num_channels
          _UpperCAmelCase       :       List[str]							   =num_encoder_blocks
          _UpperCAmelCase       :       Optional[Any]							   =depths
          _UpperCAmelCase       :       str							   =sr_ratios
          _UpperCAmelCase       :       Dict							   =hidden_sizes
          _UpperCAmelCase       :       List[str]							   =patch_sizes
          _UpperCAmelCase       :       Any							   =strides
          _UpperCAmelCase       :       List[str]							   =mlp_ratios
          _UpperCAmelCase       :       Dict							   =num_attention_heads
          _UpperCAmelCase       :       List[str]							   =hidden_act
          _UpperCAmelCase       :       int							   =hidden_dropout_prob
          _UpperCAmelCase       :       List[Any]							   =attention_probs_dropout_prob
          _UpperCAmelCase       :       Union[str, Any]							   =initializer_range
          _UpperCAmelCase       :       Tuple							   =drop_path_rate
          _UpperCAmelCase       :       str							   =layer_norm_eps
          _UpperCAmelCase       :       Optional[int]							   =decoder_hidden_size
          _UpperCAmelCase       :       List[str]							   =max_depth
          _UpperCAmelCase       :       Dict							   =head_in_index

