


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					(	__snake_case			,       __snake_case			,       __snake_case	):





      @register_to_config
      def __init__(		self    :       Any       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       float       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       str       ,							__lowerCamelCase    :       bool = False       ,							)     -> Any:






         """simple docstring"""







         super().__init__()

         UpperCAmelCase      					=  nn.Embedding(__lowerCamelCase       ,							__lowerCamelCase							)

         UpperCAmelCase      					=  nn.Embedding(__lowerCamelCase       ,							__lowerCamelCase							)
         UpperCAmelCase      					=  False

         UpperCAmelCase      					=  nn.Dropout(p=__lowerCamelCase							)

         UpperCAmelCase      					=  TaConfig(
             vocab_size=__lowerCamelCase       ,							d_model=__lowerCamelCase       ,							num_heads=__lowerCamelCase       ,							d_kv=__lowerCamelCase       ,							d_ff=__lowerCamelCase       ,							dropout_rate=__lowerCamelCase       ,							feed_forward_proj=__lowerCamelCase       ,							is_decoder=__lowerCamelCase       ,							is_encoder_decoder=__lowerCamelCase       ,							)

         UpperCAmelCase      					=  nn.ModuleList()
         for lyr_num in range(__lowerCamelCase							):
            UpperCAmelCase      					=  TaBlock(__lowerCamelCase							)
            self.encoders.append(__lowerCamelCase							)

         UpperCAmelCase      					=  TaLayerNorm(__lowerCamelCase							)
         UpperCAmelCase      					=  nn.Dropout(p=__lowerCamelCase							)





      def 							_lowercase					(		self    :       List[str]       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       Tuple							)     -> int:






         """simple docstring"""







         UpperCAmelCase      					=  self.token_embedder(__lowerCamelCase							)

         UpperCAmelCase      					=  encoder_input_tokens.shape[1]
         UpperCAmelCase      					=  torch.arange(__lowerCamelCase       ,							device=encoder_input_tokens.device							)
         x += self.position_encoding(__lowerCamelCase							)

         UpperCAmelCase      					=  self.dropout_pre(__lowerCamelCase							)

         # inverted the attention mask
         UpperCAmelCase      					=  encoder_input_tokens.size()
         UpperCAmelCase      					=  self.get_extended_attention_mask(__lowerCamelCase       ,							__lowerCamelCase							)

         for lyr in self.encoders:
            UpperCAmelCase      					=  lyr(__lowerCamelCase       ,							__lowerCamelCase							)[0]
         UpperCAmelCase      					=  self.layer_norm(__lowerCamelCase							)

         return self.dropout_post(__lowerCamelCase							), encoder_inputs_mask











# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel  # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    '''stable diffusion controlnet''',
    '''0.22.0''',
    '''Importing `StableDiffusionControlNetPipeline` or `MultiControlNetModel` from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import StableDiffusionControlNetPipeline` instead.''',
    standard_warn=False,
    stacklevel=3,
)