




'''simple docstring'''



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





class      lowerCAmelCase (			nn.Module):
       __lowercase	:   int
       __lowercase	:   jnp.dtype										=      jnp.floataa


       def    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            __snake_case            =	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	)   ->	Union[str, Any]:



            '''simple docstring'''




            __snake_case       ,     __snake_case       ,     __snake_case       ,     __snake_case            =	hidden_states.shape
            __snake_case            =	jax.image.resize(
                __SCREAMING_SNAKE_CASE     ,	shape=(batch, height * 2, width * 2, channels)     ,	method='''nearest'''     ,	)
            __snake_case            =	self.conv(__SCREAMING_SNAKE_CASE	)
            return hidden_states





class      lowerCAmelCase (			nn.Module):
       __lowercase	:   int
       __lowercase	:   jnp.dtype										=      jnp.floataa


       def    lowerCAmelCase   ( self	)   ->	int:



            '''simple docstring'''




            __snake_case            =	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]:



            '''simple docstring'''




            __snake_case            =	self.conv(__SCREAMING_SNAKE_CASE	)
            return hidden_states





class      lowerCAmelCase (			nn.Module):
       __lowercase	:   int
       __lowercase	:   int										=      None
       __lowercase	:   float										=      0.0
       __lowercase	:   bool										=      None
       __lowercase	:   jnp.dtype										=      jnp.floataa


       def    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            __snake_case            =	self.in_channels if self.out_channels is None else self.out_channels

            __snake_case            =	nn.GroupNorm(num_groups=32     ,	epsilon=1E-5	)
            __snake_case            =	nn.Conv(
                __SCREAMING_SNAKE_CASE     ,	kernel_size=(3, 3)     ,	strides=(1, 1)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)

            __snake_case            =	nn.Dense(__SCREAMING_SNAKE_CASE     ,	dtype=self.dtype	)

            __snake_case            =	nn.GroupNorm(num_groups=32     ,	epsilon=1E-5	)
            __snake_case            =	nn.Dropout(self.dropout_prob	)
            __snake_case            =	nn.Conv(
                __SCREAMING_SNAKE_CASE     ,	kernel_size=(3, 3)     ,	strides=(1, 1)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)

            __snake_case            =	self.in_channels != out_channels if self.use_nin_shortcut is None else self.use_nin_shortcut

            __snake_case            =	None
            if use_nin_shortcut:
                 __snake_case            =	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	)   ->	int:



            '''simple docstring'''




            __snake_case            =	hidden_states
            __snake_case            =	self.norma(__SCREAMING_SNAKE_CASE	)
            __snake_case            =	nn.swish(__SCREAMING_SNAKE_CASE	)
            __snake_case            =	self.conva(__SCREAMING_SNAKE_CASE	)

            __snake_case            =	self.time_emb_proj(nn.swish(__SCREAMING_SNAKE_CASE	)	)
            __snake_case            =	jnp.expand_dims(jnp.expand_dims(__SCREAMING_SNAKE_CASE     ,	1	)     ,	1	)
            __snake_case            =	hidden_states + temb

            __snake_case            =	self.norma(__SCREAMING_SNAKE_CASE	)
            __snake_case            =	nn.swish(__SCREAMING_SNAKE_CASE	)
            __snake_case            =	self.dropout(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE	)
            __snake_case            =	self.conva(__SCREAMING_SNAKE_CASE	)

            if self.conv_shortcut is not None:
                 __snake_case            =	self.conv_shortcut(__SCREAMING_SNAKE_CASE	)

            return hidden_states + residual












'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase_							:	int	     =		logging.get_logger(__name__)

UpperCAmelCase_							:	Dict	     =		{
    '''microsoft/swin-tiny-patch4-window7-224''': (
        '''https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json'''
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}





class      lowerCAmelCase (			__lowerCAmelCase					, __lowerCAmelCase):
       __lowercase	:   List[Any]										=      '''swin'''

       __lowercase	:   str										=      {
           '''num_attention_heads''': '''num_heads''',
           '''num_hidden_layers''': '''num_layers''',
       }


       def __init__( self     ,	__SCREAMING_SNAKE_CASE=224     ,	__SCREAMING_SNAKE_CASE=4     ,	__SCREAMING_SNAKE_CASE=3     ,	__SCREAMING_SNAKE_CASE=96     ,	__SCREAMING_SNAKE_CASE=[2, 2, 6, 2]     ,	__SCREAMING_SNAKE_CASE=[3, 6, 12, 24]     ,	__SCREAMING_SNAKE_CASE=7     ,	__SCREAMING_SNAKE_CASE=4.0     ,	__SCREAMING_SNAKE_CASE=True     ,	__SCREAMING_SNAKE_CASE=0.0     ,	__SCREAMING_SNAKE_CASE=0.0     ,	__SCREAMING_SNAKE_CASE=0.1     ,	__SCREAMING_SNAKE_CASE="gelu"     ,	__SCREAMING_SNAKE_CASE=False     ,	__SCREAMING_SNAKE_CASE=0.02     ,	__SCREAMING_SNAKE_CASE=1E-5     ,	__SCREAMING_SNAKE_CASE=32     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=None     ,	**__SCREAMING_SNAKE_CASE     ,	)   ->	int:



            '''simple docstring'''




            super().__init__(**__SCREAMING_SNAKE_CASE	)

            __snake_case            =	image_size
            __snake_case            =	patch_size
            __snake_case            =	num_channels
            __snake_case            =	embed_dim
            __snake_case            =	depths
            __snake_case            =	len(__SCREAMING_SNAKE_CASE	)
            __snake_case            =	num_heads
            __snake_case            =	window_size
            __snake_case            =	mlp_ratio
            __snake_case            =	qkv_bias
            __snake_case            =	hidden_dropout_prob
            __snake_case            =	attention_probs_dropout_prob
            __snake_case            =	drop_path_rate
            __snake_case            =	hidden_act
            __snake_case            =	use_absolute_embeddings
            __snake_case            =	layer_norm_eps
            __snake_case            =	initializer_range
            __snake_case            =	encoder_stride
            # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
            # this indicates the channel dimension after the last stage of the model
            __snake_case            =	int(embed_dim * 2 ** (len(__SCREAMING_SNAKE_CASE	) - 1)	)
            __snake_case            =	['''stem'''] + [F'''stage{idx}''' for idx in range(1     ,	len(__SCREAMING_SNAKE_CASE	) + 1	)]
            __snake_case       ,     __snake_case            =	get_aligned_output_features_output_indices(
                out_features=__SCREAMING_SNAKE_CASE     ,	out_indices=__SCREAMING_SNAKE_CASE     ,	stage_names=self.stage_names	)





class      lowerCAmelCase (			__lowerCAmelCase):
       __lowercase	:   Optional[int]										=      version.parse('''1.11''')


       @property
       def    lowerCAmelCase   ( self	)   ->	Mapping[str, Mapping[int, str]]:



            '''simple docstring'''




            return OrderedDict(
                [
                    ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
                ]	)




       @property
       def    lowerCAmelCase   ( self	)   ->	float:



            '''simple docstring'''




            return 1E-4






