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


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



		def __UpperCamelCase			(			self	)  -> List[str]:
				"""simple docstring"""
				UpperCamelCase          =					nn.Conv(
				    self.out_channels    ,				kernel_size=(3, 3)    ,				strides=(1, 1)    ,				padding=((1, 1), (1, 1))    ,				dtype=self.dtype    ,				)



		def __call__(			self    ,				A_	)  -> Any:
				"""simple docstring"""
				UpperCamelCase          =					hidden_states.shape
				UpperCamelCase          =					jax.image.resize(
				    _a    ,				shape=(batch, height * 2, width * 2, channels)    ,				method='nearest'    ,				)
				UpperCamelCase          =					self.conv(_a	)
				return hidden_states






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



		def __UpperCamelCase			(			self	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					nn.Conv(
				    self.out_channels    ,				kernel_size=(3, 3)    ,				strides=(2, 2)    ,				padding=((1, 1), (1, 1))    ,				dtype=self.dtype    ,				)



		def __call__(			self    ,				A_	)  -> str:
				"""simple docstring"""
				# pad = ((0, 0), (0, 1), (0, 1), (0, 0))  # pad height and width dim
				# hidden_states = jnp.pad(hidden_states, pad_width=pad)
				UpperCamelCase          =					self.conv(_a	)
				return hidden_states






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



		def __UpperCamelCase			(			self	)  -> str:
				"""simple docstring"""
				UpperCamelCase          =					self.in_channels if self.out_channels is None else self.out_channels

				UpperCamelCase          =					nn.GroupNorm(num_groups=32    ,				epsilon=1e-5	)
				UpperCamelCase          =					nn.Conv(
				    _a    ,				kernel_size=(3, 3)    ,				strides=(1, 1)    ,				padding=((1, 1), (1, 1))    ,				dtype=self.dtype    ,				)

				UpperCamelCase          =					nn.Dense(_a    ,				dtype=self.dtype	)

				UpperCamelCase          =					nn.GroupNorm(num_groups=32    ,				epsilon=1e-5	)
				UpperCamelCase          =					nn.Dropout(self.dropout_prob	)
				UpperCamelCase          =					nn.Conv(
				    _a    ,				kernel_size=(3, 3)    ,				strides=(1, 1)    ,				padding=((1, 1), (1, 1))    ,				dtype=self.dtype    ,				)

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

				UpperCamelCase          =					None
				if use_nin_shortcut:
						UpperCamelCase          =					nn.Conv(
						    _a    ,				kernel_size=(1, 1)    ,				strides=(1, 1)    ,				padding='VALID'    ,				dtype=self.dtype    ,				)



		def __call__(			self    ,				A_    ,				A_    ,				A_=True	)  -> Dict:
				"""simple docstring"""
				UpperCamelCase          =					hidden_states
				UpperCamelCase          =					self.norma(_a	)
				UpperCamelCase          =					nn.swish(_a	)
				UpperCamelCase          =					self.conva(_a	)

				UpperCamelCase          =					self.time_emb_proj(nn.swish(_a	)	)
				UpperCamelCase          =					jnp.expand_dims(jnp.expand_dims(_a    ,				1	)    ,				1	)
				UpperCamelCase          =					hidden_states + temb

				UpperCamelCase          =					self.norma(_a	)
				UpperCamelCase          =					nn.swish(_a	)
				UpperCamelCase          =					self.dropout(_a    ,				_a	)
				UpperCamelCase          =					self.conva(_a	)

				if self.conv_shortcut is not None:
						UpperCamelCase          =					self.conv_shortcut(_a	)

				return hidden_states + residual


from __future__ import annotations


class     lowercase :



		def __init__(			self    ,				A_    ,				A_	)  -> Any:
				"""simple docstring"""
				UpperCamelCase     ,  UpperCamelCase          =					text, pattern
				UpperCamelCase     ,  UpperCamelCase          =					len(A_	), len(A_	)



		def __UpperCamelCase			(			self    ,				A_	)  -> int:
				"""simple docstring"""

				for i in range(self.patLen - 1    ,				-1    ,				-1	):
						if char == self.pattern[i]:
								return i
				return -1



		def __UpperCamelCase			(			self    ,				A_	)  -> int:
				"""simple docstring"""

				for i in range(self.patLen - 1    ,				-1    ,				-1	):
						if self.pattern[i] != self.text[current_pos + i]:
								return current_pos + i
				return -1



		def __UpperCamelCase			(			self	)  -> list[int]:
				"""simple docstring"""
				# searches pattern in text and returns index positions
				UpperCamelCase          =					[]
				for i in range(self.textLen - self.patLen + 1	):
						UpperCamelCase          =					self.mismatch_in_text(A_	)
						if mismatch_index == -1:
								positions.append(A_	)
						else:
								UpperCamelCase          =					self.match_in_pattern(self.text[mismatch_index]	)
								UpperCamelCase          =					(
								    mismatch_index - match_index
								)  # shifting index lgtm [py/multiple-definition]
				return positions






_UpperCAmelCase :			Union[str, Any]              =	"ABAABA"
_UpperCAmelCase :			Any              =	"AB"
_UpperCAmelCase :			Dict              =	BoyerMooreSearch(text, pattern)
_UpperCAmelCase :			Optional[int]              =	bms.bad_character_heuristic()

if len(positions) == 0:
					print("No match found")
else:
					print("Pattern found in following positions: ")
					print(positions)
