
"""simple docstring"""

import inspect

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
   import jax
@require_flax
class        _UpperCAmelCase							:




      def       a_ (							self							)  ->   Tuple:
          UpperCAmelCase     ,							UpperCAmelCase       =   self.prepare_init_args_and_inputs_for_common()

          UpperCAmelCase       =   self.model_class(**lowercase_							)
          UpperCAmelCase       =   model.init(inputs_dict['prng_key']				,    inputs_dict['sample']							)
          jax.lax.stop_gradient(lowercase_							)

          UpperCAmelCase       =   model.apply(lowercase_				,    inputs_dict['sample']							)

          if isinstance(lowercase_				,    lowercase_							):
              UpperCAmelCase       =   output.sample

          self.assertIsNotNone(lowercase_							)
          UpperCAmelCase       =   inputs_dict['sample'].shape
          self.assertEqual(output.shape				,    lowercase_				,    'Input and output shapes do not match'							)




      def       a_ (							self							)  ->   Optional[Any]:
          UpperCAmelCase     ,							UpperCAmelCase       =   self.prepare_init_args_and_inputs_for_common()

          UpperCAmelCase       =   1_6
          UpperCAmelCase       =   (1_6, 3_2)

          UpperCAmelCase       =   self.model_class(**lowercase_							)
          UpperCAmelCase       =   model.init(inputs_dict['prng_key']				,    inputs_dict['sample']							)
          jax.lax.stop_gradient(lowercase_							)

          UpperCAmelCase       =   model.apply(lowercase_				,    inputs_dict['sample']							)

          if isinstance(lowercase_				,    lowercase_							):
              UpperCAmelCase       =   output.sample

          self.assertIsNotNone(lowercase_							)
          UpperCAmelCase       =   inputs_dict['sample'].shape
          self.assertEqual(output.shape				,    lowercase_				,    'Input and output shapes do not match'							)




      def       a_ (							self							)  ->   List[Any]:
          UpperCAmelCase       =   'kwargs' in inspect.signature(self.model_class.__init__							).parameters
          UpperCAmelCase       =   len(self.model_class._deprecated_kwargs							) > 0

          if has_kwarg_in_model_class and not has_deprecated_kwarg:
              raise ValueError(
                  F"{self.model_class} has `**kwargs` in its __init__ method but has not defined any deprecated kwargs"
                  ' under the `_deprecated_kwargs` class attribute. Make sure to either remove `**kwargs` if there are'
                  ' no deprecated arguments or add the deprecated argument with `_deprecated_kwargs ='
                  ' [<deprecated_argument>]`'							)

          if not has_kwarg_in_model_class and has_deprecated_kwarg:
              raise ValueError(
                  F"{self.model_class} doesn't have `**kwargs` in its __init__ method but has defined deprecated kwargs"
                  ' under the `_deprecated_kwargs` class attribute. Make sure to either add the `**kwargs` argument to'
                  F" {self.model_class}.__init__ if there are deprecated arguments or remove the deprecated argument"
                  ' from `_deprecated_kwargs = [<deprecated_argument>]`'							)





"""simple docstring"""

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        _UpperCAmelCase							(						SCREAMING_SNAKE_CASE_       ,     SCREAMING_SNAKE_CASE_       ,     SCREAMING_SNAKE_CASE_							):




      @register_to_config
      def __init__(							self				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_ = False				,    )  ->   List[Any]:
          super().__init__()

          UpperCAmelCase       =   nn.Linear(lowercase_				,    lowercase_				,    bias=lowercase_							)

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

          UpperCAmelCase       =   nn.Dropout(p=lowercase_							)

          UpperCAmelCase       =   TaConfig(
              d_model=lowercase_				,    num_heads=lowercase_				,    d_kv=lowercase_				,    d_ff=lowercase_				,    feed_forward_proj=lowercase_				,    dropout_rate=lowercase_				,    is_decoder=lowercase_				,    is_encoder_decoder=lowercase_				,    )
          UpperCAmelCase       =   nn.ModuleList()
          for lyr_num in range(lowercase_							):
              UpperCAmelCase       =   TaBlock(lowercase_							)
              self.encoders.append(lowercase_							)

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




      def       a_ (							self				,    lowercase_				,    lowercase_							)  ->   Union[str, Any]:
          UpperCAmelCase       =   self.input_proj(lowercase_							)

          # terminal relative positional encodings
          UpperCAmelCase       =   encoder_inputs.shape[1]
          UpperCAmelCase       =   torch.arange(lowercase_				,    device=encoder_inputs.device							)

          UpperCAmelCase       =   encoder_inputs_mask.sum(-1							)
          UpperCAmelCase       =   torch.roll(input_positions.unsqueeze(0							)				,    tuple(seq_lens.tolist()							)				,    dims=0							)
          x += self.position_encoding(lowercase_							)

          UpperCAmelCase       =   self.dropout_pre(lowercase_							)

          # inverted the attention mask
          UpperCAmelCase       =   encoder_inputs.size()
          UpperCAmelCase       =   self.get_extended_attention_mask(lowercase_				,    lowercase_							)

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

          return self.dropout_post(lowercase_							), encoder_inputs_mask



