
from abc import ABC, abstractmethod
from typing import List, Optional





class        lowerCAmelCase__      (   snake_case__	):

						def __init__(			self				)					->      Tuple:


								'''simple docstring'''

								self.test()

						def  A_				(			self				)					->      str:


								'''simple docstring'''

								_UpperCamelCase						    =	0
								_UpperCamelCase						    =	False
								while not completed:
										if counter == 1:
												self.reset()
										_UpperCamelCase						    =	self.advance()
										if not self.does_advance(UpperCAmelCase_				):
												raise Exception(
												    """Custom Constraint is not defined correctly. self.does_advance(self.advance()) must be true."""				)

										_UpperCamelCase    ,	_UpperCamelCase    ,	_UpperCamelCase						    =	self.update(UpperCAmelCase_				)
										counter += 1

										if counter > 1_00_00:
												raise Exception("""update() does not fulfill the constraint."""				)

								if self.remaining() != 0:
										raise Exception("""Custom Constraint is not defined correctly."""				)

						@abstractmethod
						def  A_				(			self				)					->      Optional[Any]:


								'''simple docstring'''

								raise NotImplementedError(
								    F'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'				)

						@abstractmethod
						def  A_				(			self       ,							a				)					->      Tuple:


								'''simple docstring'''

								raise NotImplementedError(
								    F'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'				)

						@abstractmethod
						def  A_				(			self       ,							a				)					->      List[str]:


								'''simple docstring'''

								raise NotImplementedError(
								    F'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'				)

						@abstractmethod
						def  A_				(			self				)					->      int:


								'''simple docstring'''

								raise NotImplementedError(
								    F'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'				)

						@abstractmethod
						def  A_				(			self				)					->      List[str]:


								'''simple docstring'''

								raise NotImplementedError(
								    F'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'				)







						@abstractmethod
						def  A_				(			self       ,							a=False				)					->      List[Any]:


								'''simple docstring'''

								raise NotImplementedError(
								    F'{self.__class__} is an abstract class. Only classes inheriting this class can be called.'				)





class        lowerCAmelCase__      (   snake_case__	):

						def __init__(			self       ,							a				)					->      str:


								'''simple docstring'''

								super(UpperCAmelCase_       ,							self				).__init__()

								if not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				) or len(UpperCAmelCase_				) == 0:
										raise ValueError(F'`token_ids` has to be a non-empty list, but is {token_ids}.'				)
								if any((not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				) or token_id < 0) for token_id in token_ids				):
										raise ValueError(F'Each list in `token_ids` has to be a list of positive integers, but is {token_ids}.'				)

								_UpperCamelCase						    =	token_ids

								_UpperCamelCase						    =	len(self.token_ids				)
								_UpperCamelCase						    =	-1  # the index of the currently fulfilled step
								_UpperCamelCase						    =	False

						def  A_				(			self				)					->      Dict:


								'''simple docstring'''

								if self.completed:
										return None
								return self.token_ids[self.fulfilled_idx + 1]

						def  A_				(			self       ,							a				)					->      Optional[int]:


								'''simple docstring'''

								if not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
										raise ValueError(F'`token_id` has to be an `int`, but is {token_id} of type {type(UpperCAmelCase_				)}'				)

								if self.completed:
										return False

								return token_id == self.token_ids[self.fulfilled_idx + 1]

						def  A_				(			self       ,							a				)					->      List[Any]:


								'''simple docstring'''

								if not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
										raise ValueError(F'`token_id` has to be an `int`, but is {token_id} of type {type(UpperCAmelCase_				)}'				)

								_UpperCamelCase						    =	False
								_UpperCamelCase						    =	False
								_UpperCamelCase						    =	False

								if self.does_advance(UpperCAmelCase_				):
										self.fulfilled_idx += 1
										_UpperCamelCase						    =	True
										if self.fulfilled_idx == (self.seqlen - 1):
												_UpperCamelCase						    =	True
										_UpperCamelCase						    =	completed
								else:
										# failed to make progress.
										_UpperCamelCase						    =	True
										self.reset()
								return stepped, completed, reset

						def  A_				(			self				)					->      Optional[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	False
								_UpperCamelCase						    =	0

						def  A_				(			self				)					->      Dict:


								'''simple docstring'''

								return self.seqlen - (self.fulfilled_idx + 1)







						def  A_				(			self       ,							a=False				)					->      List[str]:


								'''simple docstring'''

								_UpperCamelCase						    =	PhrasalConstraint(self.token_ids				)

								if stateful:
										_UpperCamelCase						    =	self.seqlen
										_UpperCamelCase						    =	self.fulfilled_idx
										_UpperCamelCase						    =	self.completed

								return new_constraint





class        lowerCAmelCase__      :

						def __init__(			self       ,							a       ,							a=True				)					->      Union[str, Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	max([len(UpperCAmelCase_				) for one in nested_token_ids]				)

								_UpperCamelCase						    =	{}
								for token_ids in nested_token_ids:
										_UpperCamelCase						    =	root
										for tidx, token_id in enumerate(UpperCAmelCase_				):
												if token_id not in level:
														_UpperCamelCase						    =	{}

												_UpperCamelCase						    =	level[token_id]

								if no_subsets and self.has_subsets(UpperCAmelCase_       ,							UpperCAmelCase_				):
										raise ValueError(
										    """Each list in `nested_token_ids` can't be a complete subset of another list, but is"""
										    F' {nested_token_ids}.'				)

								_UpperCamelCase						    =	root

						def  A_				(			self       ,							a				)					->      Optional[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	self.trie

								for current_token in current_seq:
										_UpperCamelCase						    =	start[current_token]

								_UpperCamelCase						    =	list(start.keys()				)

								return next_tokens

						def  A_				(			self       ,							a				)					->      Optional[int]:


								'''simple docstring'''

								_UpperCamelCase						    =	self.next_tokens(UpperCAmelCase_				)

								return len(UpperCAmelCase_				) == 0

						def  A_				(			self       ,							a				)					->      List[str]:


								'''simple docstring'''

								_UpperCamelCase						    =	list(root.values()				)
								if len(UpperCAmelCase_				) == 0:
										return 1
								else:
										return sum([self.count_leaves(UpperCAmelCase_				) for nn in next_nodes]				)







						def  A_				(			self       ,							a       ,							a				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	self.count_leaves(UpperCAmelCase_				)
								return len(UpperCAmelCase_				) != leaf_count





class        lowerCAmelCase__      (   snake_case__	):

						def __init__(			self       ,							a				)					->      List[str]:


								'''simple docstring'''

								super(UpperCAmelCase_       ,							self				).__init__()

								if not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				) or len(UpperCAmelCase_				) == 0:
										raise ValueError(F'`nested_token_ids` has to be a non-empty list, but is {nested_token_ids}.'				)
								if any(not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				) for token_ids in nested_token_ids				):
										raise ValueError(F'`nested_token_ids` has to be a list of lists, but is {nested_token_ids}.'				)
								if any(
								    any((not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				) or token_id < 0) for token_id in token_ids				)
								    for token_ids in nested_token_ids				):
										raise ValueError(
										    F'Each list in `nested_token_ids` has to be a list of positive integers, but is {nested_token_ids}.'				)

								_UpperCamelCase						    =	DisjunctiveTrie(UpperCAmelCase_				)
								_UpperCamelCase						    =	nested_token_ids

								_UpperCamelCase						    =	self.trie.max_height
								_UpperCamelCase						    =	[]
								_UpperCamelCase						    =	False

						def  A_				(			self				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	self.trie.next_tokens(self.current_seq				)

								if len(UpperCAmelCase_				) == 0:
										return None
								else:
										return token_list

						def  A_				(			self       ,							a				)					->      int:


								'''simple docstring'''

								if not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
										raise ValueError(F'`token_id` is supposed to be type `int`, but is {token_id} of type {type(UpperCAmelCase_				)}'				)

								_UpperCamelCase						    =	self.trie.next_tokens(self.current_seq				)

								return token_id in next_tokens

						def  A_				(			self       ,							a				)					->      Dict:


								'''simple docstring'''

								if not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
										raise ValueError(F'`token_id` is supposed to be type `int`, but is {token_id} of type {type(UpperCAmelCase_				)}'				)

								_UpperCamelCase						    =	False
								_UpperCamelCase						    =	False
								_UpperCamelCase						    =	False

								if self.does_advance(UpperCAmelCase_				):
										self.current_seq.append(UpperCAmelCase_				)
										_UpperCamelCase						    =	True
								else:
										_UpperCamelCase						    =	True
										self.reset()

								_UpperCamelCase						    =	self.trie.reached_leaf(self.current_seq				)
								_UpperCamelCase						    =	completed

								return stepped, completed, reset

						def  A_				(			self				)					->      Dict:


								'''simple docstring'''

								_UpperCamelCase						    =	False
								_UpperCamelCase						    =	[]

						def  A_				(			self				)					->      int:


								'''simple docstring'''

								if self.completed:
										# since this can be completed without reaching max height
										return 0
								else:
										return self.seqlen - len(self.current_seq				)







						def  A_				(			self       ,							a=False				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	DisjunctiveConstraint(self.token_ids				)

								if stateful:
										_UpperCamelCase						    =	self.seqlen
										_UpperCamelCase						    =	self.current_seq
										_UpperCamelCase						    =	self.completed

								return new_constraint





class        lowerCAmelCase__      :

						def __init__(			self       ,							a				)					->      Any:


								'''simple docstring'''

								_UpperCamelCase						    =	constraints

								# max # of steps required to fulfill a given constraint
								_UpperCamelCase						    =	max([c.seqlen for c in constraints]				)
								_UpperCamelCase						    =	len(UpperCAmelCase_				)
								_UpperCamelCase						    =	False

								self.init_state()

						def  A_				(			self				)					->      Dict:


								'''simple docstring'''

								_UpperCamelCase						    =	[]
								_UpperCamelCase						    =	None
								_UpperCamelCase						    =	[constraint.copy(stateful=UpperCAmelCase_				) for constraint in self.constraints]

						def  A_				(			self				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	0
								if self.inprogress_constraint:
										# extra points for having a constraint mid-fulfilled
										add += self.max_seqlen - self.inprogress_constraint.remaining()

								return (len(self.complete_constraints				) * self.max_seqlen) + add

						def  A_				(			self				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	[]
								if self.inprogress_constraint is None:
										for constraint in self.pending_constraints:  # "pending" == "unfulfilled yet"
												_UpperCamelCase						    =	constraint.advance()
												if isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
														token_list.append(UpperCAmelCase_				)
												elif isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
														token_list.extend(UpperCAmelCase_				)
								else:
										_UpperCamelCase						    =	self.inprogress_constraint.advance()
										if isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
												token_list.append(UpperCAmelCase_				)
										elif isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
												token_list.extend(UpperCAmelCase_				)

								if len(UpperCAmelCase_				) == 0:
										return None
								else:
										return token_list

						def  A_				(			self       ,							a				)					->      Dict:


								'''simple docstring'''

								self.init_state()

								if token_ids is not None:
										for token in token_ids:
												# completes or steps **one** constraint
												_UpperCamelCase    ,	_UpperCamelCase						    =	self.add(UpperCAmelCase_				)

												# the entire list of constraints are fulfilled
												if self.completed:
														break

						def  A_				(			self       ,							a				)					->      List[Any]:


								'''simple docstring'''

								if not isinstance(UpperCAmelCase_       ,							UpperCAmelCase_				):
										raise ValueError(F'`token_id` should be an `int`, but is `{token_id}`.'				)

								_UpperCamelCase    ,	_UpperCamelCase						    =	False, False

								if self.completed:
										_UpperCamelCase						    =	True
										_UpperCamelCase						    =	False
										return complete, stepped

								if self.inprogress_constraint is not None:
										# In the middle of fulfilling a constraint. If the `token_id` *does* makes an incremental progress to current
										# job, simply update the state

										_UpperCamelCase    ,	_UpperCamelCase    ,	_UpperCamelCase						    =	self.inprogress_constraint.update(UpperCAmelCase_				)
										if reset:
												# 1. If the next token breaks the progress, then we must restart.
												#     e.g. constraint = "I love pies" and sequence so far is "I love" but `token_id` == "books".

												#     But that doesn't mean we self.init_state(), since we only reset the state for this particular
												#     constraint, not the full list of constraints.

												self.pending_constraints.append(self.inprogress_constraint.copy(stateful=UpperCAmelCase_				)				)
												_UpperCamelCase						    =	None

										if complete:
												# 2. If the next token completes the constraint, move it to completed list, set
												#     inprogress to None. If there are no pending constraints either, then this full list of constraints
												#     is complete.

												self.complete_constraints.append(self.inprogress_constraint				)
												_UpperCamelCase						    =	None

												if len(self.pending_constraints				) == 0:
														# we're done!
														_UpperCamelCase						    =	True

								else:
										# Not in the middle of fulfilling a constraint. So does this `token_id` helps us step towards any of our list
										# of constraints?

										for cidx, pending_constraint in enumerate(self.pending_constraints				):
												if pending_constraint.does_advance(UpperCAmelCase_				):
														_UpperCamelCase    ,	_UpperCamelCase    ,	_UpperCamelCase						    =	pending_constraint.update(UpperCAmelCase_				)

														if not stepped:
																raise Exception(
																    """`constraint.update(token_id)` is not yielding incremental progress, """
																    """even though `constraint.does_advance(token_id)` is true."""				)

														if complete:
																self.complete_constraints.append(UpperCAmelCase_				)
																_UpperCamelCase						    =	None

														if not complete and stepped:
																_UpperCamelCase						    =	pending_constraint

														if complete or stepped:
																# If we made any progress at all, then it's at least not a "pending constraint".

																_UpperCamelCase						    =	(
																    self.pending_constraints[:cidx] + self.pending_constraints[cidx + 1 :]
																)

																if len(self.pending_constraints				) == 0 and self.inprogress_constraint is None:
																		# If there's no longer any pending after this and no inprogress either, then we must be
																		# complete.

																		_UpperCamelCase						    =	True

																break  # prevent accidentally stepping through multiple constraints with just one token.

								return complete, stepped







						def  A_				(			self       ,							a=True				)					->      Optional[int]:


								'''simple docstring'''

								_UpperCamelCase						    =	ConstraintListState(self.constraints				)  # we actually never though self.constraints objects
								# throughout this process. So it's at initialization state.

								if stateful:
										_UpperCamelCase						    =	[
										    constraint.copy(stateful=UpperCAmelCase_				) for constraint in self.complete_constraints
										]
										if self.inprogress_constraint is not None:
												_UpperCamelCase						    =	self.inprogress_constraint.copy(stateful=UpperCAmelCase_				)
										_UpperCamelCase						    =	[constraint.copy() for constraint in self.pending_constraints]

								return new_state





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowerCamelCase__	=							logging.get_logger(__name__)

lowerCamelCase__	=							{
    "ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}







class        lowerCAmelCase__      (   __lowercase	):
						UpperCamelCase_							: int	=		"deta"
						UpperCamelCase_							: Union[str, Any]	=		{
						    "hidden_size": "d_model",
						    "num_attention_heads": "encoder_attention_heads",
						}

						def __init__(			self       ,							a=None       ,							a=9_00       ,							a=20_48       ,							a=6       ,							a=20_48       ,							a=8       ,							a=6       ,							a=10_24       ,							a=8       ,							a=0.0       ,							a=True       ,							a="relu"       ,							a=2_56       ,							a=0.1       ,							a=0.0       ,							a=0.0       ,							a=0.02       ,							a=1.0       ,							a=True       ,							a=False       ,							a="sine"       ,							a=5       ,							a=4       ,							a=4       ,							a=True       ,							a=3_00       ,							a=True       ,							a=True       ,							a=1       ,							a=5       ,							a=2       ,							a=1       ,							a=1       ,							a=5       ,							a=2       ,							a=0.1       ,							a=0.25       ,							**a       ,							)					->      Dict:


								'''simple docstring'''

								if backbone_config is None:
										logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""				)
										_UpperCamelCase						    =	CONFIG_MAPPING["""resnet"""](out_features=["""stage2""", """stage3""", """stage4"""]				)
								else:
										if isinstance(a       ,							a				):
												_UpperCamelCase						    =	backbone_config.pop("""model_type"""				)
												_UpperCamelCase						    =	CONFIG_MAPPING[backbone_model_type]
												_UpperCamelCase						    =	config_class.from_dict(a				)

								_UpperCamelCase						    =	backbone_config
								_UpperCamelCase						    =	num_queries
								_UpperCamelCase						    =	max_position_embeddings
								_UpperCamelCase						    =	d_model
								_UpperCamelCase						    =	encoder_ffn_dim
								_UpperCamelCase						    =	encoder_layers
								_UpperCamelCase						    =	encoder_attention_heads
								_UpperCamelCase						    =	decoder_ffn_dim
								_UpperCamelCase						    =	decoder_layers
								_UpperCamelCase						    =	decoder_attention_heads
								_UpperCamelCase						    =	dropout
								_UpperCamelCase						    =	attention_dropout
								_UpperCamelCase						    =	activation_dropout
								_UpperCamelCase						    =	activation_function
								_UpperCamelCase						    =	init_std
								_UpperCamelCase						    =	init_xavier_std
								_UpperCamelCase						    =	encoder_layerdrop
								_UpperCamelCase						    =	auxiliary_loss
								_UpperCamelCase						    =	position_embedding_type
								# deformable attributes
								_UpperCamelCase						    =	num_feature_levels
								_UpperCamelCase						    =	encoder_n_points
								_UpperCamelCase						    =	decoder_n_points
								_UpperCamelCase						    =	two_stage
								_UpperCamelCase						    =	two_stage_num_proposals
								_UpperCamelCase						    =	with_box_refine
								_UpperCamelCase						    =	assign_first_stage
								if two_stage is True and with_box_refine is False:
										raise ValueError("""If two_stage is True, with_box_refine must be True."""				)
								# Hungarian matcher
								_UpperCamelCase						    =	class_cost
								_UpperCamelCase						    =	bbox_cost
								_UpperCamelCase						    =	giou_cost
								# Loss coefficients
								_UpperCamelCase						    =	mask_loss_coefficient
								_UpperCamelCase						    =	dice_loss_coefficient
								_UpperCamelCase						    =	bbox_loss_coefficient
								_UpperCamelCase						    =	giou_loss_coefficient
								_UpperCamelCase						    =	eos_coefficient
								_UpperCamelCase						    =	focal_alpha
								super().__init__(is_encoder_decoder=a       ,							**a				)

						@property
						def  A_				(			self				)					->      int:


								'''simple docstring'''

								return self.encoder_attention_heads

						@property
						def  A_				(			self				)					->      int:


								'''simple docstring'''

								return self.d_model







						def  A_				(			self				)					->      Tuple:


								'''simple docstring'''

								_UpperCamelCase						    =	copy.deepcopy(self.__dict__				)
								_UpperCamelCase						    =	self.backbone_config.to_dict()
								_UpperCamelCase						    =	self.__class__.model_type
								return output



