





import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin





class      lowercase__    (							__A     ,					__A     ,					__A  ):







  @register_to_config
  def __init__(	self    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase    ,						_lowercase = False    ,						):
       super().__init__()

       lowerCAmelCase_					:       Any    =		nn.Embedding(_lowercase    ,						_lowercase						)

       lowerCAmelCase_					:       Optional[int]    =		nn.Embedding(_lowercase    ,						_lowercase						)
       lowerCAmelCase_					:       List[str]    =		False

       lowerCAmelCase_					:       List[str]    =		nn.Dropout(p=_lowercase						)

       lowerCAmelCase_					:       Tuple    =		TaConfig(
           vocab_size=_lowercase    ,						d_model=_lowercase    ,						num_heads=_lowercase    ,						d_kv=_lowercase    ,						d_ff=_lowercase    ,						dropout_rate=_lowercase    ,						feed_forward_proj=_lowercase    ,						is_decoder=_lowercase    ,						is_encoder_decoder=_lowercase    ,						)

       lowerCAmelCase_					:       int    =		nn.ModuleList()
       for lyr_num in range(_lowercase						):
            lowerCAmelCase_					:       str    =		TaBlock(_lowercase						)
            self.encoders.append(_lowercase						)

       lowerCAmelCase_					:       List[str]    =		TaLayerNorm(_lowercase						)
       lowerCAmelCase_					:       int    =		nn.Dropout(p=_lowercase						)







  def 	UpperCAmelCase__		(	self    ,						_lowercase    ,						_lowercase						):
       lowerCAmelCase_					:       List[Any]    =		self.token_embedder(_lowercase						)

       lowerCAmelCase_					:       Dict    =		encoder_input_tokens.shape[1]
       lowerCAmelCase_					:       List[str]    =		torch.arange(_lowercase    ,						device=encoder_input_tokens.device						)
       x += self.position_encoding(_lowercase						)

       lowerCAmelCase_					:       List[Any]    =		self.dropout_pre(_lowercase						)

       # inverted the attention mask
       lowerCAmelCase_					:       int    =		encoder_input_tokens.size()
       lowerCAmelCase_					:       List[Any]    =		self.get_extended_attention_mask(_lowercase    ,						_lowercase						)

       for lyr in self.encoders:
            lowerCAmelCase_					:       List[str]    =		lyr(_lowercase    ,						_lowercase						)[0]
       lowerCAmelCase_					:       List[str]    =		self.layer_norm(_lowercase						)

       return self.dropout_post(_lowercase						), encoder_inputs_mask







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


UpperCAmelCase_					:   Tuple 							=						logging.get_logger(__name__)

UpperCAmelCase_					:   List[str] 							=						{
    """google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
    """google/fnet-large""": """https://huggingface.co/google/fnet-large/resolve/main/config.json"""
    # See all FNet models at https://huggingface.co/models?filter=fnet
}





class      lowercase__    (							__A  ):
  __UpperCamelCase	     =  """fnet"""







  def __init__(	self    ,						_lowercase=32_000    ,						_lowercase=768    ,						_lowercase=12    ,						_lowercase=3_072    ,						_lowercase="gelu_new"    ,						_lowercase=0.1    ,						_lowercase=512    ,						_lowercase=4    ,						_lowercase=0.02    ,						_lowercase=1e-12    ,						_lowercase=False    ,						_lowercase=512    ,						_lowercase=3    ,						_lowercase=1    ,						_lowercase=2    ,						**_lowercase    ,						):
       super().__init__(pad_token_id=_lowercase    ,						bos_token_id=_lowercase    ,						eos_token_id=_lowercase    ,						**_lowercase						)

       lowerCAmelCase_					:       Optional[Any]    =		vocab_size
       lowerCAmelCase_					:       List[str]    =		max_position_embeddings
       lowerCAmelCase_					:       str    =		hidden_size
       lowerCAmelCase_					:       Any    =		num_hidden_layers
       lowerCAmelCase_					:       Optional[int]    =		intermediate_size
       lowerCAmelCase_					:       int    =		hidden_act
       lowerCAmelCase_					:       List[str]    =		hidden_dropout_prob
       lowerCAmelCase_					:       Tuple    =		initializer_range
       lowerCAmelCase_					:       int    =		type_vocab_size
       lowerCAmelCase_					:       str    =		layer_norm_eps
       lowerCAmelCase_					:       Optional[Any]    =		use_tpu_fourier_optimizations
       lowerCAmelCase_					:       Union[str, Any]    =		tpu_short_seq_length
