"""simple docstring"""


import bisect
import copy
from collections import defaultdict

import numpy as np
from torch.utils.data import BatchSampler, Sampler

from utils import logger


def   __UpperCAmelCase     (	_snake_case		:       List[str],				_snake_case		:       Optional[Any]       ):
   _lowercase							     =       copy.deepcopy(_snake_case       )
   _lowercase							     =       sorted(_snake_case       )
   _lowercase							     =       [bisect.bisect_right(_snake_case,				_snake_case       ) for y in x]
   return quantized


def   __UpperCAmelCase     (	_snake_case		:       str,				_snake_case		:       str=0       ):
   _lowercase							     =       np.arange(start=3,				stop=_snake_case,				step=4       ).tolist() if k > 0 else [1_0]
   _lowercase							     =       _quantize(_snake_case,				_snake_case       )
   # count number of elements per group
   _lowercase							     =       np.unique(_snake_case,				return_counts=_snake_case       )[1]
   _lowercase							     =       [0] + bins + [np.inf]
   logger.info("Using {} as bins for aspect lengths quantization".format(_snake_case       )       )
   logger.info("Count of instances per bin: {}".format(_snake_case       )       )
   return groups
class   UpperCAmelCase_	(				lowercase__   ):
    def __init__(	self			:       Dict   ,						_lowercase			:       Dict   ,						_lowercase			:       Dict   ,						_lowercase			:       List[Any]		)						->    List[Any]:
       if not isinstance(_lowercase   ,						_lowercase		):
          raise ValueError(
              "sampler should be an instance of torch.utils.data.Sampler, but got sampler={}".format(_lowercase		)		)
       _lowercase							     =       sampler
       _lowercase							     =       group_ids
       _lowercase							     =       batch_size
    def __iter__(	self			:       str		)						->    str:
       _lowercase							     =       defaultdict(_lowercase		)
       _lowercase							     =       defaultdict(_lowercase		)

       _lowercase							     =       0
       for idx in self.sampler:
          _lowercase							     =       self.group_ids[idx]
          buffer_per_group[group_id].append(_lowercase		)
          samples_per_group[group_id].append(_lowercase		)
          if len(buffer_per_group[group_id]		) == self.batch_size:
             yield buffer_per_group[group_id]  # TODO
             num_batches += 1
             del buffer_per_group[group_id]
          assert len(buffer_per_group[group_id]		) < self.batch_size

       # now we have run out of elements that satisfy
       # the group criteria, let's return the remaining
       # elements so that the size of the sampler is
       # deterministic
       _lowercase							     =       len(self		)
       _lowercase							     =       expected_num_batches - num_batches
       if num_remaining > 0:
          # for the remaining batches, group the batches by similar lengths
          _lowercase							     =       []
          for group_id, idxs in sorted(buffer_per_group.items()   ,						key=lambda _lowercase		: x[0]		):
             batch_idx.extend(_lowercase		)
             if len(_lowercase		) >= self.batch_size:
                yield batch_idx[: self.batch_size]
                _lowercase							     =       batch_idx[self.batch_size :]
                num_remaining -= 1
          if len(_lowercase		) > 0:
             yield batch_idx
             num_remaining -= 1
       assert num_remaining == 0




    def __len__(	self			:       List[str]		)						->    List[str]:
       return (len(self.sampler		) + self.batch_size - 1) // self.batch_size
"""simple docstring"""


from .number_theory.prime_numbers import next_prime
class   UpperCAmelCase_	:
    def __init__(	self			:       str   ,						_lowercase			:       int   ,						_lowercase			:       int | None = None   ,						_lowercase			:       float | None = None   ,						)						->    None:
       _lowercase							     =       size_table
       _lowercase							     =       [None] * self.size_table
       _lowercase							     =       0.75 if lim_charge is None else lim_charge
       _lowercase							     =       1 if charge_factor is None else charge_factor
       _lowercase							     =       []
       _lowercase							     =       {}
    def 		_lowerCamelCase      (	self			:       Any		)						->    Optional[Any]:
       return self._keys
    def 		_lowerCamelCase      (	self			:       Dict		)						->    Dict:
       return sum(1 for slot in self.values if slot is not None		) / (
           self.size_table * self.charge_factor
       )
    def 		_lowerCamelCase      (	self			:       Union[str, Any]   ,						_lowercase			:       List[str]		)						->    str:
       return key % self.size_table
    def 		_lowerCamelCase      (	self			:       Any   ,						_lowercase			:       Union[str, Any]		)						->    Optional[Any]:
       print(f"""step {step_ord}"""		)
       print(list(range(len(self.values		)		)		)		)
       print(self.values		)
    def 		_lowerCamelCase      (	self			:       str   ,						_lowercase			:       List[Any]		)						->    List[Any]:
       _lowercase							     =       1
       _lowercase							     =       values
       for value in values:
          self.insert_data(_lowercase		)
          self._step_by_step(_lowercase		)
          i += 1
    def 		_lowerCamelCase      (	self			:       Union[str, Any]   ,						_lowercase			:       Optional[int]   ,						_lowercase			:       Union[str, Any]		)						->    List[Any]:
       _lowercase							     =       data
       _lowercase							     =       data
    def 		_lowerCamelCase      (	self			:       int   ,						_lowercase			:       Optional[Any]   ,						_lowercase			:       Tuple=None		)						->    Any:
       _lowercase							     =       self.hash_function(key + 1		)

       while self.values[new_key] is not None and self.values[new_key] != key:
          if self.values.count(_lowercase		) > 0:
             _lowercase							     =       self.hash_function(new_key + 1		)
          else:
             _lowercase							     =       None
             break

       return new_key
    def 		_lowerCamelCase      (	self			:       str		)						->    Any:
       _lowercase							     =       [value for value in self.values if value is not None]
       _lowercase							     =       next_prime(self.size_table   ,						factor=2		)
       self._keys.clear()
       _lowercase							     =       [None] * self.size_table  # hell's pointers D: don't DRY ;/
       for value in survivor_values:
          self.insert_data(_lowercase		)




    def 		_lowerCamelCase      (	self			:       Union[str, Any]   ,						_lowercase			:       Tuple		)						->    Optional[int]:
       _lowercase							     =       self.hash_function(_lowercase		)

       if self.values[key] is None:
          self._set_value(_lowercase   ,						_lowercase		)

       elif self.values[key] == data:
          pass

       else:
          _lowercase							     =       self._collision_resolution(_lowercase   ,						_lowercase		)
          if collision_resolution is not None:
             self._set_value(_lowercase   ,						_lowercase		)
          else:
             self.rehashing()
             self.insert_data(_lowercase		)