'''simple docstring'''




from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap

def 	UpperCamelCase_							(					_UpperCAmelCase  :      List[str]    )    ->    Any:


       """simple docstring"""







       return getitem, k

def 	UpperCamelCase_							(					_UpperCAmelCase  :      List[Any]			,	_UpperCAmelCase  :      str    )    ->    List[str]:


       """simple docstring"""







       return setitem, k, v

def 	UpperCamelCase_							(					_UpperCAmelCase  :      Optional[Any]    )    ->    Dict:


       """simple docstring"""







       return delitem, k

def 	UpperCamelCase_							(					_UpperCAmelCase  :      Tuple			,	_UpperCAmelCase  :      Tuple			,	*_UpperCAmelCase  :      Optional[int]    )    ->    List[str]:


       """simple docstring"""







       try:
              return fun(UpperCAmelCase_			,	*UpperCAmelCase_    ), None
       except Exception as e:
              return None, e


__SCREAMING_SNAKE_CASE       :     List[str]     =  (
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
)

__SCREAMING_SNAKE_CASE       :     int     =  [
    _set("""key_a""", """val_a"""),
    _set("""key_a""", """val_b"""),
]

__SCREAMING_SNAKE_CASE       :     Tuple     =  [
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
    _del("""key_a"""),
    _del("""key_b"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
]

__SCREAMING_SNAKE_CASE       :     Optional[Any]     =  [
    _get("""key_a"""),
    _del("""key_a"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
    _del("""key_a"""),
    _get("""key_a"""),
]

__SCREAMING_SNAKE_CASE       :     int     =  [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

__SCREAMING_SNAKE_CASE       :     List[Any]     =  [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set("""key_a""", """val_b"""),
]

@pytest.mark.parametrize(
    "operations"			,	(
        pytest.param(_add_items			,	id="add items"    ),
        pytest.param(_overwrite_items			,	id="overwrite items"    ),
        pytest.param(_delete_items			,	id="delete items"    ),
        pytest.param(_access_absent_items			,	id="access absent items"    ),
        pytest.param(_add_with_resize_up			,	id="add with resize up"    ),
        pytest.param(_add_with_resize_down			,	id="add with resize down"    ),
    )			,	)
def 	UpperCamelCase_							(					_UpperCAmelCase  :      int    )    ->    Dict:


       """simple docstring"""







       _UpperCAmelCase     :  Tuple							      =    HashMap(initial_block_size=4    )
       _UpperCAmelCase     :  Dict							      =    {}
       for _, (fun, *args) in enumerate(UpperCAmelCase_    ):
              _UpperCAmelCase      ,  _UpperCAmelCase     :  Tuple							      =    _run_operation(UpperCAmelCase_			,	UpperCAmelCase_			,	*UpperCAmelCase_    )
              _UpperCAmelCase      ,  _UpperCAmelCase     :  Optional[int]							      =    _run_operation(UpperCAmelCase_			,	UpperCAmelCase_			,	*UpperCAmelCase_    )
              assert my_res == py_res
              assert str(UpperCAmelCase_    ) == str(UpperCAmelCase_    )
              assert set(UpperCAmelCase_    ) == set(UpperCAmelCase_    )
              assert len(UpperCAmelCase_    ) == len(UpperCAmelCase_    )
              assert set(my.items()    ) == set(py.items()    )


def 	UpperCamelCase_							(					)    ->    int:


       """simple docstring"""







       def is_public(_UpperCAmelCase  :      str    ) -> bool:
              return not name.startswith("_"    )

       _UpperCAmelCase     :  Dict							      =    {name for name in dir({}    ) if is_public(UpperCAmelCase_    )}
       _UpperCAmelCase     :  Tuple							      =    {name for name in dir(HashMap()    ) if is_public(UpperCAmelCase_    )}

       assert dict_public_names > hash_public_names





'''simple docstring'''

import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union

import torch
from torch import nn

from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging


a_  :				Dict						= logging.get_logger(__name__)





class      snake_case    (    lowercase			):





  """simple docstring"""




  def __init__(    self			,  UpperCamelCase     ):







   """simple docstring"""
   super().__init__()
   lowerCamelCase_      =  nn.ModuleList(UpperCamelCase     )






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase = None			,  UpperCamelCase = None			,  UpperCamelCase = None			,  UpperCamelCase = None			,  UpperCamelCase = False			,  UpperCamelCase = True			,  ):







   """simple docstring"""
   for i, (image, scale, controlnet) in enumerate(zip(UpperCamelCase			,  UpperCamelCase			,  self.nets     )     ):
    lowerCamelCase_ ,lowerCamelCase_      =  controlnet(
        UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  )

    # merge samples
    if i == 0:
     lowerCamelCase_ ,lowerCamelCase_      =  down_samples, mid_sample
    else:
     lowerCamelCase_      =  [
         samples_prev + samples_curr
         for samples_prev, samples_curr in zip(UpperCamelCase			,  UpperCamelCase     )
     ]
     mid_block_res_sample += mid_sample

   return down_block_res_samples, mid_block_res_sample






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase = True			,  UpperCamelCase = None			,  UpperCamelCase = False			,  UpperCamelCase = None			,  ):







   """simple docstring"""
   lowerCamelCase_      =  0
   lowerCamelCase_      =  save_directory
   for controlnet in self.nets:
    controlnet.save_pretrained(
        UpperCamelCase			,  is_main_process=UpperCamelCase			,  save_function=UpperCamelCase			,  safe_serialization=UpperCamelCase			,  variant=UpperCamelCase			,  )

    idx += 1
    lowerCamelCase_      =  model_path_to_save + f'''_{idx}'''







  @classmethod
  def   snake_case		(    cls			,  UpperCamelCase			,  **UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  0
   lowerCamelCase_      =  []

   # load controlnet and append to list until no controlnet directory exists anymore
   # first controlnet has to be saved under `./mydirectory/controlnet` to be compliant with `DiffusionPipeline.from_prertained`
   # second, third, ... controlnets have to be saved under `./mydirectory/controlnet_1`, `./mydirectory/controlnet_2`, ...
   lowerCamelCase_      =  pretrained_model_path
   while os.path.isdir(UpperCamelCase     ):
    lowerCamelCase_      =  ControlNetModel.from_pretrained(UpperCamelCase			,  **UpperCamelCase     )
    controlnets.append(UpperCamelCase     )

    idx += 1
    lowerCamelCase_      =  pretrained_model_path + f'''_{idx}'''

   logger.info(f'''{len(UpperCamelCase     )} controlnets loaded from {pretrained_model_path}.'''     )

   if len(UpperCamelCase     ) == 0:
    raise ValueError(
        f'''No ControlNets found under {os.path.dirname(UpperCamelCase     )}. Expected at least {pretrained_model_path + "_0"}.'''     )

   return cls(UpperCamelCase     )



