






from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url







class 				UpperCAmelCase_  (		__lowerCamelCase		):
     __lowerCamelCase      				=  ''
     __lowerCamelCase      				=  'hf-legacy'  # "hf://"" is reserved for hffs




     def __init__(				self	,						_lowerCAmelCase = None	,						_lowerCAmelCase = None	,						**_lowerCAmelCase	,						):
          super().__init__(self	,						**_lowerCAmelCase		)
          UpperCAmelCase__      :  Optional[int]				      =			repo_info
          UpperCAmelCase__      :  Optional[int]				      =			token
          UpperCAmelCase__      :  Any				      =			None




     def   __UpperCAmelCase  (				self		):
          if self.dir_cache is None:
               UpperCAmelCase__      :  Optional[int]				      =			{}
               for hf_file in self.repo_info.siblings:
                    # TODO(QL): add sizes
                    UpperCAmelCase__      :  Any				      =			{
                        """name""": hf_file.rfilename,
                        """size""": None,
                        """type""": """file""",
                    }
                    self.dir_cache.update(
                        {
                            str(_lowerCAmelCase		): {"""name""": str(_lowerCAmelCase		), """size""": None, """type""": """directory"""}
                            for d in list(PurePosixPath(hf_file.rfilename		).parents		)[:-1]
                        }		)




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase	,						_lowerCAmelCase = "rb"	,						**_lowerCAmelCase	,						):
          if not isinstance(self.repo_info	,						_lowerCAmelCase		):
               raise NotImplementedError(f"Open is only implemented for dataset repositories, but got {self.repo_info}"		)
          UpperCAmelCase__      :  Optional[int]				      =			hf_hub_url(self.repo_info.id	,						_lowerCAmelCase	,						revision=self.repo_info.sha		)
          return fsspec.open(
              _lowerCAmelCase	,						mode=_lowerCAmelCase	,						headers=get_authentication_headers_for_url(_lowerCAmelCase	,						use_auth_token=self.token		)	,						client_kwargs={"""trust_env""": True}	,						).open()




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase	,						**_lowerCAmelCase		):
          self._get_dirs()
          UpperCAmelCase__      :  int				      =			self._strip_protocol(_lowerCAmelCase		)
          if path in self.dir_cache:
               return self.dir_cache[path]
          else:
               raise FileNotFoundError(_lowerCAmelCase		)




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase	,						_lowerCAmelCase=False	,						**_lowerCAmelCase		):
          self._get_dirs()
          UpperCAmelCase__      :  int				      =			PurePosixPath(path.strip("""/"""		)		)
          UpperCAmelCase__      :  Union[str, Any]				      =			{}
          for p, f in self.dir_cache.items():
               UpperCAmelCase__      :  List[Any]				      =			PurePosixPath(p.strip("""/"""		)		)
               UpperCAmelCase__      :  Any				      =			p.parent
               if root == path:
                    UpperCAmelCase__      :  Dict				      =			f
          UpperCAmelCase__      :  Optional[Any]				      =			list(paths.values()		)
          if detail:
               return out
          else:
               return sorted(f["""name"""] for f in out		)










'''simple docstring'''



import flax.linen as nn
import jax
import jax.numpy as jnp





class   UpperCAmelCase_    (nn.Module    ):





    """simple docstring"""






    lowerCamelCase    :   int
    lowerCamelCase    :   jnp.dtype					=     jnp.floataa







    def  lowercase_							(				self      )							->	Union[str, Any]:
         __lowerCamelCase  :      Optional[Any]														=						nn.Conv(
             self.out_channels     ,	kernel_size=(3, 3)     ,	strides=(1, 1)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)







    def __call__(				self     ,	SCREAMING_SNAKE_CASE_      )							->	Any:
         __lowerCamelCase							,			__lowerCamelCase							,			__lowerCamelCase							,			__lowerCamelCase  :      Optional[int]														=						hidden_states.shape
         __lowerCamelCase  :      Dict														=						jax.image.resize(
             SCREAMING_SNAKE_CASE_     ,	shape=(batch, height * 2, width * 2, channels)     ,	method='nearest'     ,	)
         __lowerCamelCase  :      Optional[Any]														=						self.conv(SCREAMING_SNAKE_CASE_      )
         return hidden_states







class   UpperCAmelCase_    (nn.Module    ):





    """simple docstring"""






    lowerCamelCase    :   int
    lowerCamelCase    :   jnp.dtype					=     jnp.floataa







    def  lowercase_							(				self      )							->	List[str]:
         __lowerCamelCase  :      str														=						nn.Conv(
             self.out_channels     ,	kernel_size=(3, 3)     ,	strides=(2, 2)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)







    def __call__(				self     ,	SCREAMING_SNAKE_CASE_      )							->	List[str]:
         # pad = ((0, 0), (0, 1), (0, 1), (0, 0))  # pad height and width dim
         # hidden_states = jnp.pad(hidden_states, pad_width=pad)
         __lowerCamelCase  :      str														=						self.conv(SCREAMING_SNAKE_CASE_      )
         return hidden_states







class   UpperCAmelCase_    (nn.Module    ):





    """simple docstring"""






    lowerCamelCase    :   int
    lowerCamelCase    :   int					=     None
    lowerCamelCase    :   float					=     0.0
    lowerCamelCase    :   bool					=     None
    lowerCamelCase    :   jnp.dtype					=     jnp.floataa







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      Optional[Any]														=						self.in_channels if self.out_channels is None else self.out_channels

         __lowerCamelCase  :      Optional[Any]														=						nn.GroupNorm(num_groups=32     ,	epsilon=1E-5      )
         __lowerCamelCase  :      Tuple														=						nn.Conv(
             SCREAMING_SNAKE_CASE_     ,	kernel_size=(3, 3)     ,	strides=(1, 1)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)

         __lowerCamelCase  :      List[str]														=						nn.Dense(SCREAMING_SNAKE_CASE_     ,	dtype=self.dtype      )

         __lowerCamelCase  :      Dict														=						nn.GroupNorm(num_groups=32     ,	epsilon=1E-5      )
         __lowerCamelCase  :      int														=						nn.Dropout(self.dropout_prob      )
         __lowerCamelCase  :      Union[str, Any]														=						nn.Conv(
             SCREAMING_SNAKE_CASE_     ,	kernel_size=(3, 3)     ,	strides=(1, 1)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)

         __lowerCamelCase  :      Optional[int]														=						self.in_channels != out_channels if self.use_nin_shortcut is None else self.use_nin_shortcut

         __lowerCamelCase  :      List[Any]														=						None
         if use_nin_shortcut:
              __lowerCamelCase  :      Any														=						nn.Conv(
                  SCREAMING_SNAKE_CASE_     ,	kernel_size=(1, 1)     ,	strides=(1, 1)     ,	padding='VALID'     ,	dtype=self.dtype     ,	)







    def __call__(				self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_=True      )							->	Tuple:
         __lowerCamelCase  :      List[Any]														=						hidden_states
         __lowerCamelCase  :      str														=						self.norma(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						nn.swish(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						self.conva(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      str														=						self.time_emb_proj(nn.swish(SCREAMING_SNAKE_CASE_      )      )
         __lowerCamelCase  :      List[str]														=						jnp.expand_dims(jnp.expand_dims(SCREAMING_SNAKE_CASE_     ,	1      )     ,	1      )
         __lowerCamelCase  :      Optional[int]														=						hidden_states + temb

         __lowerCamelCase  :      List[Any]														=						self.norma(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Any														=						nn.swish(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      List[Any]														=						self.dropout(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      List[Any]														=						self.conva(SCREAMING_SNAKE_CASE_      )

         if self.conv_shortcut is not None:
              __lowerCamelCase  :      List[str]														=						self.conv_shortcut(SCREAMING_SNAKE_CASE_      )

         return hidden_states + residual






