


from functools import partial
from typing import Any, Callable, Dict, List, Type, TypeVar, Union, overload

import torch
import torch.nn as nn
import torch.types
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    torch.Tensor:







 """simple docstring"""


 if not inplace:
  _lowercase							   =ma + ma
 else:
  ma += ma

 return ma
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case		)  ->    torch.Tensor:







 """simple docstring"""


 _lowercase							   =-1 * len(__snake_case		)
 _lowercase							   =list(range(len(tensor.shape[:zero_index]		)		)		)
 return tensor.permute(first_inds + [zero_index + i for i in inds]		)
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case		)  ->    torch.Tensor:







 """simple docstring"""


 return t.reshape(t.shape[:-no_dims] + (-1,)		)
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case  ,		__snake_case = 1e-4		)  ->    torch.Tensor:







 """simple docstring"""


 _lowercase							   =mask.expand(*value.shape		)
 return torch.sum(mask * value  ,		dim=__snake_case		) / (eps + torch.sum(__snake_case  ,		dim=__snake_case		))
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case = 2.31_25  ,		__snake_case = 21.68_75  ,		__snake_case = 64		)  ->    torch.Tensor:







 """simple docstring"""


 _lowercase							   =torch.linspace(__snake_case  ,		__snake_case  ,		no_bins - 1  ,		device=pts.device		)
 _lowercase							   =torch.sqrt(torch.sum((pts.unsqueeze(-2		) - pts.unsqueeze(-3		)) ** 2  ,		dim=-1		)		)
 return torch.bucketize(__snake_case  ,		__snake_case		)
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case		)  ->    dict:







 """simple docstring"""


 _lowercase							   =dicts[0]
 _lowercase							   ={}
 for k, v in first.items():
  _lowercase							   =[d[k] for d in dicts]
  if isinstance(__snake_case  ,		__snake_case		):
   _lowercase							   =dict_multimap(__snake_case  ,		__snake_case		)
  else:
   _lowercase							   =fn(__snake_case		)

 return new_dict
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case		)  ->    torch.Tensor:







 """simple docstring"""


 _lowercase							   =v_bins.view(((1,) * len(x.shape		)) + (len(__snake_case		),)		)
 _lowercase							   =x[..., None] - reshaped_bins
 _lowercase							   =torch.argmin(torch.abs(__snake_case		)  ,		dim=-1		)
 return nn.functional.one_hot(__snake_case  ,		num_classes=len(__snake_case		)		).float()
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case = 0  ,		__snake_case = 0		)  ->    torch.Tensor:







 """simple docstring"""


 _lowercase							   =[]
 for i, s in enumerate(data.shape[:no_batch_dims]		):
  _lowercase							   =torch.arange(__snake_case		)
  _lowercase							   =r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape		) - i - 1)))		)
  ranges.append(__snake_case		)

 _lowercase							   =[slice(__snake_case		) for _ in range(len(data.shape		) - no_batch_dims		)]
 _lowercase							   =inds
 ranges.extend(__snake_case		)
 # Matt note: Editing this to get around the behaviour of using a list as an array index changing
 # in recent Numpy versions
 return data[tuple(__snake_case		)]


UpperCAmelCase__     			=							TypeVar('''T''')
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    Dict[Any, Union[dict, list, tuple, Any]]:







 """simple docstring"""


 _lowercase							   ={}
 for k, v in dic.items():
  if isinstance(__snake_case  ,		__snake_case		):
   _lowercase							   =dict_map(__snake_case  ,		__snake_case  ,		__snake_case		)
  else:
   _lowercase							   =tree_map(__snake_case  ,		__snake_case  ,		__snake_case		)

 return new_dict
@overload
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    Any:







 """simple docstring"""


 ...
@overload
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    dict:







 """simple docstring"""


 ...
@overload
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    list:







 """simple docstring"""


 ...
@overload
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    tuple:







 """simple docstring"""


 ...
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    Tuple:







 """simple docstring"""


 if isinstance(__snake_case  ,		__snake_case		):
  return dict_map(__snake_case  ,		__snake_case  ,		__snake_case		)
 elif isinstance(__snake_case  ,		__snake_case		):
  return [tree_map(__snake_case  ,		__snake_case  ,		__snake_case		) for x in tree]
 elif isinstance(__snake_case  ,		__snake_case		):
  return tuple(tree_map(__snake_case  ,		__snake_case  ,		__snake_case		) for x in tree		)
 elif isinstance(__snake_case  ,		__snake_case		):
  return fn(__snake_case		)
 else:
  print(type(__snake_case		)		)
  raise ValueError('''Not supported'''		)



UpperCAmelCase__     			=							partial(tree_map, leaf_type=torch.Tensor)





from ..utils import DummyObject, requires_backends







class    lowerCamelCase__     ( metaclass=lowerCAmelCase):
     SCREAMING_SNAKE_CASE__       =    ['''tensorflow_text''']





     def __init__(self	,  *UpperCAmelCase	,  **UpperCAmelCase )  ->     Any:
      requires_backends(self	,  ['''tensorflow_text'''] )

